Background: #fff
Foreground: #000
PrimaryPale: #8cf
PrimaryLight: #18f
PrimaryMid: #04b
PrimaryDark: #014
SecondaryPale: #ffc
SecondaryLight: #fe8
SecondaryMid: #db4
SecondaryDark: #841
TertiaryPale: #eee
TertiaryLight: #ccc
TertiaryMid: #999
TertiaryDark: #666
Error: #f88
<!--{{{-->
<div class='toolbar' macro='toolbar [[ToolbarCommands::EditToolbar]]'></div>
<div class='title' macro='view title'></div>
<div class='editor' macro='edit title'></div>
<div macro='annotations'></div>
<div class='editor' macro='edit text'></div>
<div class='editor' macro='edit tags'></div><div class='editorFooter'><span macro='message views.editor.tagPrompt'></span><span macro='tagChooser excludeLists'></span></div>
<!--}}}-->
To get started with this blank [[TiddlyWiki]], you'll need to modify the following tiddlers:
* [[SiteTitle]] & [[SiteSubtitle]]: The title and subtitle of the site, as shown above (after saving, they will also appear in the browser title bar)
* [[MainMenu]]: The menu (usually on the left)
* [[DefaultTiddlers]]: Contains the names of the tiddlers that you want to appear when the TiddlyWiki is opened
You'll also need to enter your username for signing your edits: <<option txtUserName>>
<<importTiddlers>>
<!--{{{-->
<link rel='alternate' type='application/rss+xml' title='RSS' href='index.xml' />
<!--}}}-->
These [[InterfaceOptions]] for customising [[TiddlyWiki]] are saved in your browser

Your username for signing your edits. Write it as a [[WikiWord]] (eg [[JoeBloggs]])

<<option txtUserName>>
<<option chkSaveBackups>> [[SaveBackups]]
<<option chkAutoSave>> [[AutoSave]]
<<option chkRegExpSearch>> [[RegExpSearch]]
<<option chkCaseSensitiveSearch>> [[CaseSensitiveSearch]]
<<option chkAnimate>> [[EnableAnimations]]

----
Also see [[AdvancedOptions]]
<!--{{{-->
<div class='header' role='banner' macro='gradient vert [[ColorPalette::PrimaryLight]] [[ColorPalette::PrimaryMid]]'>
<div class='headerShadow'>
<span class='siteTitle' refresh='content' tiddler='SiteTitle'></span>&nbsp;
<span class='siteSubtitle' refresh='content' tiddler='SiteSubtitle'></span>
</div>
<div class='headerForeground'>
<span class='siteTitle' refresh='content' tiddler='SiteTitle'></span>&nbsp;
<span class='siteSubtitle' refresh='content' tiddler='SiteSubtitle'></span>
</div>
</div>
<div id='mainMenu' role='navigation' refresh='content' tiddler='MainMenu'></div>
<div id='sidebar'>
<div id='sidebarOptions' role='navigation' refresh='content' tiddler='SideBarOptions'></div>
<div id='sidebarTabs' role='complementary' refresh='content' force='true' tiddler='SideBarTabs'></div>
</div>
<div id='displayArea' role='main'>
<div id='messageArea'></div>
<div id='tiddlerDisplay'></div>
</div>
<!--}}}-->
/*{{{*/
body {background:[[ColorPalette::Background]]; color:[[ColorPalette::Foreground]];}

a {color:[[ColorPalette::PrimaryMid]];}
a:hover {background-color:[[ColorPalette::PrimaryMid]]; color:[[ColorPalette::Background]];}
a img {border:0;}

h1,h2,h3,h4,h5,h6 {color:[[ColorPalette::SecondaryDark]]; background:transparent;}
h1 {border-bottom:2px solid [[ColorPalette::TertiaryLight]];}
h2,h3 {border-bottom:1px solid [[ColorPalette::TertiaryLight]];}

.button {color:[[ColorPalette::PrimaryDark]]; border:1px solid [[ColorPalette::Background]];}
.button:hover {color:[[ColorPalette::PrimaryDark]]; background:[[ColorPalette::SecondaryLight]]; border-color:[[ColorPalette::SecondaryMid]];}
.button:active {color:[[ColorPalette::Background]]; background:[[ColorPalette::SecondaryMid]]; border:1px solid [[ColorPalette::SecondaryDark]];}

.header {background:[[ColorPalette::PrimaryMid]];}
.headerShadow {color:[[ColorPalette::Foreground]];}
.headerShadow a {font-weight:normal; color:[[ColorPalette::Foreground]];}
.headerForeground {color:[[ColorPalette::Background]];}
.headerForeground a {font-weight:normal; color:[[ColorPalette::PrimaryPale]];}

.tabSelected {color:[[ColorPalette::PrimaryDark]];
	background:[[ColorPalette::TertiaryPale]];
	border-left:1px solid [[ColorPalette::TertiaryLight]];
	border-top:1px solid [[ColorPalette::TertiaryLight]];
	border-right:1px solid [[ColorPalette::TertiaryLight]];
}
.tabUnselected {color:[[ColorPalette::Background]]; background:[[ColorPalette::TertiaryMid]];}
.tabContents {color:[[ColorPalette::PrimaryDark]]; background:[[ColorPalette::TertiaryPale]]; border:1px solid [[ColorPalette::TertiaryLight]];}
.tabContents .button {border:0;}

#sidebar {}
#sidebarOptions input {border:1px solid [[ColorPalette::PrimaryMid]];}
#sidebarOptions .sliderPanel {background:[[ColorPalette::PrimaryPale]];}
#sidebarOptions .sliderPanel a {border:none;color:[[ColorPalette::PrimaryMid]];}
#sidebarOptions .sliderPanel a:hover {color:[[ColorPalette::Background]]; background:[[ColorPalette::PrimaryMid]];}
#sidebarOptions .sliderPanel a:active {color:[[ColorPalette::PrimaryMid]]; background:[[ColorPalette::Background]];}

.wizard {background:[[ColorPalette::PrimaryPale]]; border:1px solid [[ColorPalette::PrimaryMid]];}
.wizard h1 {color:[[ColorPalette::PrimaryDark]]; border:none;}
.wizard h2 {color:[[ColorPalette::Foreground]]; border:none;}
.wizardStep {background:[[ColorPalette::Background]]; color:[[ColorPalette::Foreground]];
	border:1px solid [[ColorPalette::PrimaryMid]];}
.wizardStep.wizardStepDone {background:[[ColorPalette::TertiaryLight]];}
.wizardFooter {background:[[ColorPalette::PrimaryPale]];}
.wizardFooter .status {background:[[ColorPalette::PrimaryDark]]; color:[[ColorPalette::Background]];}
.wizard .button {color:[[ColorPalette::Foreground]]; background:[[ColorPalette::SecondaryLight]]; border: 1px solid;
	border-color:[[ColorPalette::SecondaryPale]] [[ColorPalette::SecondaryDark]] [[ColorPalette::SecondaryDark]] [[ColorPalette::SecondaryPale]];}
.wizard .button:hover {color:[[ColorPalette::Foreground]]; background:[[ColorPalette::Background]];}
.wizard .button:active {color:[[ColorPalette::Background]]; background:[[ColorPalette::Foreground]]; border: 1px solid;
	border-color:[[ColorPalette::PrimaryDark]] [[ColorPalette::PrimaryPale]] [[ColorPalette::PrimaryPale]] [[ColorPalette::PrimaryDark]];}

.wizard .notChanged {background:transparent;}
.wizard .changedLocally {background:#80ff80;}
.wizard .changedServer {background:#8080ff;}
.wizard .changedBoth {background:#ff8080;}
.wizard .notFound {background:#ffff80;}
.wizard .putToServer {background:#ff80ff;}
.wizard .gotFromServer {background:#80ffff;}

#messageArea {border:1px solid [[ColorPalette::SecondaryMid]]; background:[[ColorPalette::SecondaryLight]]; color:[[ColorPalette::Foreground]];}
#messageArea .button {color:[[ColorPalette::PrimaryMid]]; background:[[ColorPalette::SecondaryPale]]; border:none;}

.popupTiddler {background:[[ColorPalette::TertiaryPale]]; border:2px solid [[ColorPalette::TertiaryMid]];}

.popup {background:[[ColorPalette::TertiaryPale]]; color:[[ColorPalette::TertiaryDark]]; border-left:1px solid [[ColorPalette::TertiaryMid]]; border-top:1px solid [[ColorPalette::TertiaryMid]]; border-right:2px solid [[ColorPalette::TertiaryDark]]; border-bottom:2px solid [[ColorPalette::TertiaryDark]];}
.popup hr {color:[[ColorPalette::PrimaryDark]]; background:[[ColorPalette::PrimaryDark]]; border-bottom:1px;}
.popup li.disabled {color:[[ColorPalette::TertiaryMid]];}
.popup li a, .popup li a:visited {color:[[ColorPalette::Foreground]]; border: none;}
.popup li a:hover {background:[[ColorPalette::SecondaryLight]]; color:[[ColorPalette::Foreground]]; border: none;}
.popup li a:active {background:[[ColorPalette::SecondaryPale]]; color:[[ColorPalette::Foreground]]; border: none;}
.popupHighlight {background:[[ColorPalette::Background]]; color:[[ColorPalette::Foreground]];}
.listBreak div {border-bottom:1px solid [[ColorPalette::TertiaryDark]];}

.tiddler .defaultCommand {font-weight:bold;}

.shadow .title {color:[[ColorPalette::TertiaryDark]];}

.title {color:[[ColorPalette::SecondaryDark]];}
.subtitle {color:[[ColorPalette::TertiaryDark]];}

.toolbar {color:[[ColorPalette::PrimaryMid]];}
.toolbar a {color:[[ColorPalette::TertiaryLight]];}
.selected .toolbar a {color:[[ColorPalette::TertiaryMid]];}
.selected .toolbar a:hover {color:[[ColorPalette::Foreground]];}

.tagging, .tagged {border:1px solid [[ColorPalette::TertiaryPale]]; background-color:[[ColorPalette::TertiaryPale]];}
.selected .tagging, .selected .tagged {background-color:[[ColorPalette::TertiaryLight]]; border:1px solid [[ColorPalette::TertiaryMid]];}
.tagging .listTitle, .tagged .listTitle {color:[[ColorPalette::PrimaryDark]];}
.tagging .button, .tagged .button {border:none;}

.footer {color:[[ColorPalette::TertiaryLight]];}
.selected .footer {color:[[ColorPalette::TertiaryMid]];}

.error, .errorButton {color:[[ColorPalette::Foreground]]; background:[[ColorPalette::Error]];}
.warning {color:[[ColorPalette::Foreground]]; background:[[ColorPalette::SecondaryPale]];}
.lowlight {background:[[ColorPalette::TertiaryLight]];}

.zoomer {background:none; color:[[ColorPalette::TertiaryMid]]; border:3px solid [[ColorPalette::TertiaryMid]];}

.imageLink, #displayArea .imageLink {background:transparent;}

.annotation {background:[[ColorPalette::SecondaryLight]]; color:[[ColorPalette::Foreground]]; border:2px solid [[ColorPalette::SecondaryMid]];}

.viewer .listTitle {list-style-type:none; margin-left:-2em;}
.viewer .button {border:1px solid [[ColorPalette::SecondaryMid]];}
.viewer blockquote {border-left:3px solid [[ColorPalette::TertiaryDark]];}

.viewer table, table.twtable {border:2px solid [[ColorPalette::TertiaryDark]];}
.viewer th, .viewer thead td, .twtable th, .twtable thead td {background:[[ColorPalette::SecondaryMid]]; border:1px solid [[ColorPalette::TertiaryDark]]; color:[[ColorPalette::Background]];}
.viewer td, .viewer tr, .twtable td, .twtable tr {border:1px solid [[ColorPalette::TertiaryDark]];}

.viewer pre {border:1px solid [[ColorPalette::SecondaryLight]]; background:[[ColorPalette::SecondaryPale]];}
.viewer code {color:[[ColorPalette::SecondaryDark]];}
.viewer hr {border:0; border-top:dashed 1px [[ColorPalette::TertiaryDark]]; color:[[ColorPalette::TertiaryDark]];}

.highlight, .marked {background:[[ColorPalette::SecondaryLight]];}

.editor input {border:1px solid [[ColorPalette::PrimaryMid]];}
.editor textarea {border:1px solid [[ColorPalette::PrimaryMid]]; width:100%;}
.editorFooter {color:[[ColorPalette::TertiaryMid]];}
.readOnly {background:[[ColorPalette::TertiaryPale]];}

#backstageArea {background:[[ColorPalette::Foreground]]; color:[[ColorPalette::TertiaryMid]];}
#backstageArea a {background:[[ColorPalette::Foreground]]; color:[[ColorPalette::Background]]; border:none;}
#backstageArea a:hover {background:[[ColorPalette::SecondaryLight]]; color:[[ColorPalette::Foreground]]; }
#backstageArea a.backstageSelTab {background:[[ColorPalette::Background]]; color:[[ColorPalette::Foreground]];}
#backstageButton a {background:none; color:[[ColorPalette::Background]]; border:none;}
#backstageButton a:hover {background:[[ColorPalette::Foreground]]; color:[[ColorPalette::Background]]; border:none;}
#backstagePanel {background:[[ColorPalette::Background]]; border-color: [[ColorPalette::Background]] [[ColorPalette::TertiaryDark]] [[ColorPalette::TertiaryDark]] [[ColorPalette::TertiaryDark]];}
.backstagePanelFooter .button {border:none; color:[[ColorPalette::Background]];}
.backstagePanelFooter .button:hover {color:[[ColorPalette::Foreground]];}
#backstageCloak {background:[[ColorPalette::Foreground]]; opacity:0.6; filter:alpha(opacity=60);}
/*}}}*/
/*{{{*/
* html .tiddler {height:1%;}

body {font-size:.75em; font-family:arial,helvetica; margin:0; padding:0;}

h1,h2,h3,h4,h5,h6 {font-weight:bold; text-decoration:none;}
h1,h2,h3 {padding-bottom:1px; margin-top:1.2em;margin-bottom:0.3em;}
h4,h5,h6 {margin-top:1em;}
h1 {font-size:1.35em;}
h2 {font-size:1.25em;}
h3 {font-size:1.1em;}
h4 {font-size:1em;}
h5 {font-size:.9em;}

hr {height:1px;}

a {text-decoration:none;}

dt {font-weight:bold;}

ol {list-style-type:decimal;}
ol ol {list-style-type:lower-alpha;}
ol ol ol {list-style-type:lower-roman;}
ol ol ol ol {list-style-type:decimal;}
ol ol ol ol ol {list-style-type:lower-alpha;}
ol ol ol ol ol ol {list-style-type:lower-roman;}
ol ol ol ol ol ol ol {list-style-type:decimal;}

.txtOptionInput {width:11em;}

#contentWrapper .chkOptionInput {border:0;}

.externalLink {text-decoration:underline;}

.indent {margin-left:3em;}
.outdent {margin-left:3em; text-indent:-3em;}
code.escaped {white-space:nowrap;}

.tiddlyLinkExisting {font-weight:bold;}
.tiddlyLinkNonExisting {font-style:italic;}

/* the 'a' is required for IE, otherwise it renders the whole tiddler in bold */
a.tiddlyLinkNonExisting.shadow {font-weight:bold;}

#mainMenu .tiddlyLinkExisting,
	#mainMenu .tiddlyLinkNonExisting,
	#sidebarTabs .tiddlyLinkNonExisting {font-weight:normal; font-style:normal;}
#sidebarTabs .tiddlyLinkExisting {font-weight:bold; font-style:normal;}

.header {position:relative;}
.header a:hover {background:transparent;}
.headerShadow {position:relative; padding:4.5em 0 1em 1em; left:-1px; top:-1px;}
.headerForeground {position:absolute; padding:4.5em 0 1em 1em; left:0; top:0;}

.siteTitle {font-size:3em;}
.siteSubtitle {font-size:1.2em;}

#mainMenu {position:absolute; left:0; width:10em; text-align:right; line-height:1.6em; padding:1.5em 0.5em 0.5em 0.5em; font-size:1.1em;}

#sidebar {position:absolute; right:3px; width:16em; font-size:.9em;}
#sidebarOptions {padding-top:0.3em;}
#sidebarOptions a {margin:0 0.2em; padding:0.2em 0.3em; display:block;}
#sidebarOptions input {margin:0.4em 0.5em;}
#sidebarOptions .sliderPanel {margin-left:1em; padding:0.5em; font-size:.85em;}
#sidebarOptions .sliderPanel a {font-weight:bold; display:inline; padding:0;}
#sidebarOptions .sliderPanel input {margin:0 0 0.3em 0;}
#sidebarTabs .tabContents {width:15em; overflow:hidden;}

.wizard {padding:0.1em 1em 0 2em;}
.wizard h1 {font-size:2em; font-weight:bold; background:none; padding:0; margin:0.4em 0 0.2em;}
.wizard h2 {font-size:1.2em; font-weight:bold; background:none; padding:0; margin:0.4em 0 0.2em;}
.wizardStep {padding:1em 1em 1em 1em;}
.wizard .button {margin:0.5em 0 0; font-size:1.2em;}
.wizardFooter {padding:0.8em 0.4em 0.8em 0;}
.wizardFooter .status {padding:0 0.4em; margin-left:1em;}
.wizard .button {padding:0.1em 0.2em;}

#messageArea {position:fixed; top:2em; right:0; margin:0.5em; padding:0.5em; z-index:2000; _position:absolute;}
.messageToolbar {display:block; text-align:right; padding:0.2em;}
#messageArea a {text-decoration:underline;}

.tiddlerPopupButton {padding:0.2em;}
.popupTiddler {position: absolute; z-index:300; padding:1em; margin:0;}

.popup {position:absolute; z-index:300; font-size:.9em; padding:0; list-style:none; margin:0;}
.popup .popupMessage {padding:0.4em;}
.popup hr {display:block; height:1px; width:auto; padding:0; margin:0.2em 0;}
.popup li.disabled {padding:0.4em;}
.popup li a {display:block; padding:0.4em; font-weight:normal; cursor:pointer;}
.listBreak {font-size:1px; line-height:1px;}
.listBreak div {margin:2px 0;}

.tabset {padding:1em 0 0 0.5em;}
.tab {margin:0 0 0 0.25em; padding:2px;}
.tabContents {padding:0.5em;}
.tabContents ul, .tabContents ol {margin:0; padding:0;}
.txtMainTab .tabContents li {list-style:none;}
.tabContents li.listLink { margin-left:.75em;}

#contentWrapper {display:block;}
#splashScreen {display:none;}

#displayArea {margin:1em 17em 0 14em;}

.toolbar {text-align:right; font-size:.9em;}

.tiddler {padding:1em 1em 0;}

.missing .viewer,.missing .title {font-style:italic;}

.title {font-size:1.6em; font-weight:bold;}

.missing .subtitle {display:none;}
.subtitle {font-size:1.1em;}

.tiddler .button {padding:0.2em 0.4em;}

.tagging {margin:0.5em 0.5em 0.5em 0; float:left; display:none;}
.isTag .tagging {display:block;}
.tagged {margin:0.5em; float:right;}
.tagging, .tagged {font-size:0.9em; padding:0.25em;}
.tagging ul, .tagged ul {list-style:none; margin:0.25em; padding:0;}
.tagClear {clear:both;}

.footer {font-size:.9em;}
.footer li {display:inline;}

.annotation {padding:0.5em; margin:0.5em;}

* html .viewer pre {width:99%; padding:0 0 1em 0;}
.viewer {line-height:1.4em; padding-top:0.5em;}
.viewer .button {margin:0 0.25em; padding:0 0.25em;}
.viewer blockquote {line-height:1.5em; padding-left:0.8em;margin-left:2.5em;}
.viewer ul, .viewer ol {margin-left:0.5em; padding-left:1.5em;}

.viewer table, table.twtable {border-collapse:collapse; margin:0.8em 1.0em;}
.viewer th, .viewer td, .viewer tr,.viewer caption,.twtable th, .twtable td, .twtable tr,.twtable caption {padding:3px;}
table.listView {font-size:0.85em; margin:0.8em 1.0em;}
table.listView th, table.listView td, table.listView tr {padding:0 3px 0 3px;}

.viewer pre {padding:0.5em; margin-left:0.5em; font-size:1.2em; line-height:1.4em; overflow:auto;}
.viewer code {font-size:1.2em; line-height:1.4em;}

.editor {font-size:1.1em;}
.editor input, .editor textarea {display:block; width:100%; font:inherit;}
.editorFooter {padding:0.25em 0; font-size:.9em;}
.editorFooter .button {padding-top:0; padding-bottom:0;}

.fieldsetFix {border:0; padding:0; margin:1px 0px;}

.zoomer {font-size:1.1em; position:absolute; overflow:hidden;}
.zoomer div {padding:1em;}

* html #backstage {width:99%;}
* html #backstageArea {width:99%;}
#backstageArea {display:none; position:relative; overflow: hidden; z-index:150; padding:0.3em 0.5em;}
#backstageToolbar {position:relative;}
#backstageArea a {font-weight:bold; margin-left:0.5em; padding:0.3em 0.5em;}
#backstageButton {display:none; position:absolute; z-index:175; top:0; right:0;}
#backstageButton a {padding:0.1em 0.4em; margin:0.1em;}
#backstage {position:relative; width:100%; z-index:50;}
#backstagePanel {display:none; z-index:100; position:absolute; width:90%; margin-left:3em; padding:1em;}
.backstagePanelFooter {padding-top:0.2em; float:right;}
.backstagePanelFooter a {padding:0.2em 0.4em;}
#backstageCloak {display:none; z-index:20; position:absolute; width:100%; height:100px;}

.whenBackstage {display:none;}
.backstageVisible .whenBackstage {display:block;}
/*}}}*/
/***
StyleSheet for use when a translation requires any css style changes.
This StyleSheet can be used directly by languages such as Chinese, Japanese and Korean which need larger font sizes.
***/
/*{{{*/
body {font-size:0.8em;}
#sidebarOptions {font-size:1.05em;}
#sidebarOptions a {font-style:normal;}
#sidebarOptions .sliderPanel {font-size:0.95em;}
.subtitle {font-size:0.8em;}
.viewer table.listView {font-size:0.95em;}
/*}}}*/
/*{{{*/
@media print {
#mainMenu, #sidebar, #messageArea, .toolbar, #backstageButton, #backstageArea {display: none !important;}
#displayArea {margin: 1em 1em 0em;}
noscript {display:none;} /* Fixes a feature in Firefox 1.5.0.2 where print preview displays the noscript content */
}
/*}}}*/
<!--{{{-->
<div class='toolbar' role='navigation' macro='toolbar [[ToolbarCommands::ViewToolbar]]'></div>
<div class='title' macro='view title'></div>
<div class='subtitle'><span macro='view modifier link'></span>, <span macro='view modified date'></span> (<span macro='message views.wikified.createdPrompt'></span> <span macro='view created date'></span>)</div>
<div class='tagging' macro='tagging'></div>
<div class='tagged' macro='tags'></div>
<div class='viewer' macro='view text wikified'></div>
<div class='tagClear'></div>
<!--}}}-->
/***
|''Name''|RefreshTiddlerCommand|
|''Version''|0.3.0|
***/
//{{{
(function($) {

var cmd = config.commands.refreshTiddler = {
	text: "refresh",
	locale: {
		refreshing: "Refreshing tiddler..."
	},
	tooltip: "refresh this tiddler to be the one on the server",
	handler: function(ev, src, title) {
		var tiddler = store.getTiddler(title);
		if(!tiddler) {
			tiddler = new Tiddler(title);
			merge(tiddler.fields, config.defaultCustomFields);
		}
		$(story.getTiddler(title)).find(".viewer").
			empty().text(cmd.locale.refreshing);
		var dirtyStatus = store.isDirty();
		story.loadMissingTiddler(title, {
			"server.workspace": tiddler.fields["server.recipe"]  ? "recipes/" + tiddler.fields["server.recipe"] :
				tiddler.fields["server.workspace"] || "bags/"+tiddler.fields["server.bag"],
			"server.host": tiddler.fields["server.host"],
			"server.type": tiddler.fields["server.type"]
		}, function() {
			store.setDirty(dirtyStatus);
		});
	}
};

})(jQuery);
//}}}
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xl="http://www.w3.org/1999/xlink" version="1.1" viewBox="72 648 70 70" 
width="30" height="30">
<g stroke="none" stroke-opacity="1" stroke-dasharray="none" fill="none" fill-opacity="1">
	<g>
		<path d="M 77.59005 669.34003 C 71.532745 681.90424 73.714462 697.4441 84.135193 707.86475 
		C 97.315445 721.0451 118.684715 721.0451 131.8649 707.86475 
		C 145.04515 694.68457 145.04515 673.31537 131.8649 660.13513 
		C 121.4441 649.7141 105.90419 647.53253 93.339905 653.5899 L 102.047455 662.2976 
		C 109.58637 660.2373 117.987976 662.16803 123.90997 668.08997 
		C 132.69673 676.8767 132.69673 691.12317 123.90997 699.90985 
		C 115.12313 708.6966 100.87699 708.6966 92.09012 699.90985 
		C 86.168266 693.98804 84.23744 685.58643 86.297653 678.04755 Z M 72 648 L 72 668.25 L 78.75 661.49957 
		L 99.00019 681.7502 L 105.750175 675.00006 L 85.50013 654.75012 L 92.249985 648 Z" fill="black"
		class="glyph"/>
	</g>
</g>
</svg>
A [[SiteIcon|SiteIcon tiddler]]@glossary helps provide some identity to your space.  Ideally it'd be a square and a minimum of 48*48 pixels size.  You can upload your site icon using the uploader below.

<<binaryUploadPublic title:SiteIcon>>
—Methods by which the degree of ICA stenosis is reported vary from laboratory to laboratory, as well as within some laboratories. Some report an estimate of the specific percentage of stenosis, others stratify their estimates into five or six diagnostic categories or gradations of stenosis.
!!Recommendation
—Doppler US cannot be used to predict a single percentage of stenosis. Therefore, the consensus panelists strongly recommend the use of defined diagnostic strata. Laboratories should establish protocols for stratifying the degree of ICA stenosis, and, once established, these criteria should be consistently applied.
*The exact pathophysiology of CIN is not fully understood
*Renal effects are seen with high-osmolality ionic contrast media (HOCM), low-osmolality contrast media (LOCM), and iso-osmolality contrast media (IOCM) 
*Etiologic factors that have been suggested include: 
##renal hemodynamic changes (vasoconstriction), and 
##direct tubular toxicity of the contrast material 
*Both osmotic and chemotoxic mechanisms may be involved, 
**and some investigations suggest agent-specific chemotoxicity

*it does appear that the nephrotoxicity of contrast media is related to the dose administered 
!usage
{{{[img[ContrastMedia.png]]}}}
[img[ContrastMedia.png]]
!notes
//none//
!type
image/png
!file
file:////Users/iki/Desktop/ContrastMedia.png
!url

!data
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
The management of patients taking metformin should be guided by the following:
1.	Evidence suggesting clinically significant con- trast-induced nephrotoxicity (CIN) induced by IV contrast injection is weak to nonexistent in patients with normal renal function [4] .
2 .	Iodinated contrast is not an independent risk factor for patients taking metformin, but it is a concern in the presence of underlying condi- tions delaying renal excretion of metformin
or decreased metabolism of lactic acid or increased anaerobic metabolism 3 .	There have been no reports of lactic acidosis following IV contrast injection in properly selected patients .
4 .	In elderly patients, preliminary estimates of renal function relying on serum creatinine levels may be misleading and overestimate the adequacy of renal function .
The Committee recommends that patients taking metformin be classified into one of three categories, each of which has slightly different suggested management .
Category I
In patients with normal renal function and no known comorbidities (see Table B), there is no need to discontinue metformin prior to intravenously administering iodinated contrast media, nor is there a need to check creatinine following the test or procedure before instructing the patient to resume metformin after 48 hours .
Category II
In patients with multiple comorbidities (see Table B) who apparently have normal renal function, metformin should be discontinued at the time of an examination or procedure using IV iodinated contrast media and withheld for 48 hours . Communication be- tween the radiologist, the health care practitioner, and the patient will be necessary to establish the procedure for reassessing renal function and restarting metformin after the contrast-enhanced examination . The exact method (e .g ., serum creatinine measurement, clinical observation, hydration) will vary depending on the practice setting . A repeat serum creatinine measure- ment is not mandatory .1 If the patient had normal renal function at baseline, was clinically stable, and had no intercurrent risk factors for renal damage (e .g ., treatment with aminoglycosides, major surgery, heart failure, sepsis, repeat administration of large amounts of contrast media), metformin can be restarted without repeating the serum creatinine measurement Category III
In patients taking metformin who are known to have renal dysfunction, metformin should be sus- pended at the time of contrast injection, and cautious follow-up of renal function should be performed until safe reinstitution of metformin can be assured 
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/***
|''Name''|TiddlyFileImporter|
|''Version''|0.3.8|
|''Author''|Ben Gillies|
|''Type''|plugin|
|''Description''|Upload a TiddlyWiki file to TiddlyWeb, and import the tiddlers.|
!Usage
Upload a TiddlyWiki file to TiddlyWeb, and import the tiddlers.
!Requires
tiddlyweb
tiddlywebplugins.reflector
!Code
***/
//{{{
(function($){
if(!version.extensions.TiddlyFileImporter)
{ //# ensure that the plugin is only installed once
	version.extensions.TiddlyFileImporter = { installed: true };
}

config.macros.fileImport = {
	reflectorURI: '/reflector?csrf_token=%0',
	incorrectTypeError: 'Incorrect File Type. You must upload a TiddlyWiki',
	uploadLabel: 'Upload',
	uploadLabelPrompt: 'Import tiddlers from this TiddlyWiki',
	step1FileText: 'File:',
	step1PostText: 'In the next screen you will select the tiddlers to import.',
	step1Title: 'Step 1: Pick a TiddlyWiki to import',
	step1TypeChooser: 'Import From:',
	step3Html: ['<input type="hidden" name="markList" />',
		'<input type="hidden" checked="true" name="chkSync" />',
		'<input type="hidden" name="chkSave" />',
		'<input type="hidden" name="txtSaveTiddler" />'].join(),

	handler: function(place, macroName, params, wikifier, paramString) {
		var wizard = new Wizard();
		wizard.createWizard(place, 'Import a TiddlyWiki');
		this.restart(wizard);
	},

	restart: function(wizard) {
		var me = config.macros.fileImport;
		wizard.addStep(me.step1Title, ['<input type="hidden" ',
			'name="markList" />'].join(""));
		var markList = wizard.getElement('markList');
		var uploadWrapper = document.createElement('div');
		markList.parentNode.insertBefore(uploadWrapper, markList);
		uploadWrapper.setAttribute('refresh', 'macro');
		uploadWrapper.getAttribute('macroName', 'fileImport');
		var iframeName = 'reflectorImporter' + Math.random().toString();
		me.createForm(uploadWrapper, wizard, iframeName);
		$(uploadWrapper).append('<p>' + me.step1PostText + '</p>');
		wizard.setValue('serverType', 'tiddlyweb');
		wizard.setValue('adaptor', new config.adaptors.file());
		wizard.setValue('host', config.defaultCustomFields['server.host']);
		wizard.setValue('context', {});
		var iframe = $(['<iframe name="' + iframeName + '" ',
			'style="display: none" />'].join("")).appendTo(uploadWrapper);
		var onSubmit = function(ev) {
			var uploadType = $('select[name=uploadtype]', wizard.formElem).val();
			if (uploadType == "file") {
				// set an onload ready to hijack the form
				me.setOnLoad(uploadWrapper, wizard, iframe[0]);
				wizard.importType = 'file';
				wizard.formElem.submit();
			} else {
				var csrf_token = config.extensions.tiddlyspace.getCSRFToken();
				$.ajax({
					url: "%0/reflector?csrf_token=%1".format(
						config.defaultCustomFields["server.host"], csrf_token),
					type: "POST",
					dataType: "text",
					data: {
						uri: $("input", ".importFrom", wizard.formElem).val()
					},
					success: function(data, txtStatus, xhr) {
						wizard.POSTResponse = data;
						me.importTiddlers(uploadWrapper, wizard);
					},
					error: function(xhr, txtStatus, error) {
						displayMessage(["There was an error fetching the ",
							'url: ', txtStatus].join(""));
						me.restart(wizard);
					}
				});
				return false;
			}
		};
		wizard.setButtons([{
			caption: me.uploadLabel,
			tooltip: me.uploadLabelPrompt,
			onClick: onSubmit
		}]);
		$(wizard.formElem).submit(function(ev) {
			onSubmit(ev);
			ev.preventDefault();
		});
	},

	createForm: function(place, wizard, iframeName) {
		var form = wizard.formElem;
		var me = config.macros.fileImport;
		form.action = me.reflectorURI.format(
			config.extensions.tiddlyspace.getCSRFToken());
		form.enctype = 'multipart/form-data';
		form.encoding = 'multipart/form-data';
		form.method = 'POST';
		form.target = iframeName;
		onSelectChange = function(e) {
			var changeTo = $(this).val();
			if (changeTo == "file") {
				$(".importFrom").html('%0 <input type="file" name="file" />'.
					format(me.step1FileText));
			} else {
				$(".importFrom").html('URL: <input type="text" name="uri" />'
					+ ' Do you want <a target="_blank" href="http://faq.tiddlyspace.com/How%20do%20I%20include%2Fexclude%20spaces%3F">inclusion</a> instead?');
			}
		};
		$(place).append('<span>%0</span>'.format(me.step1TypeChooser)).
			append($(['<select name="uploadtype"><option value="file" selected="selected">file',
				'<option value="uri">url</select>'].join("")).change(onSelectChange)).
			append('<div class="importFrom">%0<input type="file" name="file" /></div>'.
					format(me.step1FileText));
	},

	setOnLoad: function(place, wizard, iframe) {
		var me = config.macros.fileImport;
		var loadHandler = function() {
			me.importTiddlers.apply(this, [place, wizard, iframe]);
		};
		iframe.onload = loadHandler;
		completeReadyStateChanges = 0;
		iframe.onreadystatechange = function() {
			if (++(completeReadyStateChanges) == 5) {
				loadHandler();
			}
		};
	},

	importTiddlers: function(place, wizard, iframe) {
		var tmpStore = new TiddlyWiki();
		var POSTedWiki = "";
		if (wizard.importType == "file") {
			try {
				POSTedWiki= iframe.contentWindow
					.document.documentElement.innerHTML;
			} catch(e) {
				displayMessage(config.macros.fileImport.incorrectTypeError);
				config.macros.fileImport.restart(wizard);
				return;
			}
			// now we are done, so remove the iframe
			$(iframe).remove();
		} else {
			POSTedWiki = wizard.POSTResponse;
		}

		tmpStore.importTiddlyWiki(POSTedWiki);
		var newTiddlers = tmpStore.getTiddlers();
		var workspace = config.defaultCustomFields['server.workspace'];
		var context = {
			status: true,
			statusText: 'OK',
			httpStatus: 200,
			adaptor: wizard.getValue('adaptor'),
			tiddlers: newTiddlers
		};
		context.adaptor.store = tmpStore;
		wizard.setValue('context', context);
		wizard.setValue('workspace', workspace);
		wizard.setValue('inFileImport', true);
		config.macros.importTiddlers.onGetTiddlerList(context, wizard);
	}
};

var _onGetTiddler = config.macros.importTiddlers.onGetTiddler;
config.macros.importTiddlers.onGetTiddler = function(context, wizard) {
	if (wizard.getValue('inFileImport')) {
		var me = config.macros.importTiddlers;
		if(!context.status)
			displayMessage("Error in importTiddlers.onGetTiddler: " + context.statusText);
		var tiddler = context.tiddler;
		var fields = tiddler.fields;
		merge(fields, config.defaultCustomFields);
		fields["server.workspace"] = wizard.getValue('workspace');
		delete fields['server.permissions'];
		delete fields['server.bag'];
		fields['server.page.revision'] = 'false';
		delete fields['server.recipe'];
		fields.changecount = 1;
		store.suspendNotifications();
		store.saveTiddler(tiddler.title, tiddler.title, tiddler.text,
			tiddler.modifier, tiddler.modified, tiddler.tags, tiddler.fields,
			false, tiddler.created);
		store.resumeNotifications();
		var remainingImports = wizard.getValue("remainingImports")-1;
		wizard.setValue("remainingImports",remainingImports);
		if(remainingImports === 0) {
			if(context.isSynchronous) {
				store.notifyAll();
				refreshDisplay();
			}
			wizard.setButtons([
					{caption: me.doneLabel, tooltip: me.donePrompt, onClick: me.onClose}
				],me.statusDoneImport);
			autoSaveChanges();
		}
	} else {
		_onGetTiddler.apply(this, arguments);
	}
};

var _onCancel = config.macros.importTiddlers.onCancel;
config.macros.importTiddlers.onCancel = function(e)
{
	var wizard = new Wizard(this);
	if (!wizard.getValue('inFileImport')) {
		return _onCancel.apply(this, arguments);
	}
	var place = wizard.clear();
	config.macros.fileImport.restart(wizard);
	return false;
};

var _step3Html = config.macros.importTiddlers.step3Html;
var _onGetTiddlerList = config.macros.importTiddlers.onGetTiddlerList;
config.macros.importTiddlers.onGetTiddlerList = function(context, wizard) {
	var fileImport = config.macros.fileImport;
	var importTiddlers = config.macros.importTiddlers;
	if (wizard.getValue('inFileImport')) {
		importTiddlers.step3Html = fileImport.step3Html;
	} else {
		importTiddlers.step3Html = _step3Html;
	}
	_onGetTiddlerList.apply(this, arguments);
};
})(jQuery);
//}}}
!!Issue
—The structure and content of final reports of carotid US examinations vary greatly from laboratory to laboratory, as well as within given laboratories. 
!!Recommendation
—The final report of the gray-scale and Doppler US interpretation of the ICA examination should include the following:
!!!Body of the report
# Pertinent US findings, including velocity measurements and gray-scale findings (presence, location, and characteristics of ICA plaque), as well as color Doppler findings when appropriate; 
#comments about limitations of the study or deviations from usual interpretive  riteria due to technical factors or hemodynamic considerations; and 
#comparison with results of prior studies.
!!Conclusion or impression
—Estimated degree of ICA stenosis, categorized by the laboratory’s established diagnostic criteria (modified, as appropriate, by technical factors or hemodynamic considerations).
<!DOCTYPE html>
<html lang="en">
<head>
	<meta charset="UTF-8">
	<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1">
	<title>Reply</title>
	<link rel="stylesheet" href="//tiddlyspace.com/bags/benspa_public/tiddlers/bootvelcro.css">
	<style>
		html,
		body {
			overflow: hidden;
			background-color: transparent;
		}

		#container {
			/* prevent a fouc if no images present */
			display: none;
		}

		.modal-header {
			border-bottom: none;
			padding: 5px 0 0;
			position: absolute;
			width: 100%;
			background-color: #e0e0e0;
			-webkit-border-radius: 6px 6px 0 0;
			-moz-border-radius: 6px 6px 0 0;
			border-radius: 6px 6px 0 0;
			cursor: move;
		}

		.form-actions {
			position: absolute;
			bottom: 0;
			box-sizing: border-box;
			-moz-box-sizing: border-box;
			width: 100%;
			margin: 0;
			border-radius: 0 0 6px 6px;
			background-color: #e0e0e0;
			border-top: 1px solid gray;
		}

		.form-actions input.btn {
			width: auto;
			float: right;
			margin: 0 0.2em;
		}

		.closeBtn {
			background-color: #DCE7F1 !important;
		}

		.primary {
			background-color: #09F !important;
		}

		h1 {
			margin-bottom: 9px;
			margin-top: 9px;
		}

		body {
			width: 100%;
			height: 100%;
			position: absolute;
		}

		.modal {
			margin: 10px;
			top: 0;
			left: 0;
			bottom: 0;
			width: 510px;
			position: absolute;
			box-shadow: #444 0px 0px 10px 2px;
			border-radius: 6px;
			background-color: white;
			border: 1px solid gray;
			background-color: #F0F4F8;
		}

		label em {
			cursor: pointer;
		}

		.modal-body {
			overflow: auto;
			position: absolute;
			top: 0;
			bottom: 0;
			left: 0;
			right: 0;
			margin: 65px 20px 67px;
			background-color: transparent;
		}

		.nav-tabs {
			padding-left: 1%;
			margin: 0;
			width: 99%;
			border-color: gray;
		}

		.nav-tabs > li {
			cursor: pointer;
		}

		.nav-tabs > li > a {
			line-height: 2.4em;
			font-weight: bold;
			font-size: 100%;
		}

		.nav-tabs > li.active > a{
			background-color: #F0F4F8;
			border-color: gray;
			border-bottom-color: #F0F4F8;
		}

		.active {
			display: block;
		}

		input,
		textarea,
		select,
		.uneditable-input {
			color: #606060;
		}

		.imagePicker {
			-moz-box-shadow: inset 0 1px 3px rgba(0, 0, 0, 0.1);
			-webkit-box-shadow: inset 0 1px 3px rgba(0, 0, 0, 0.1);
			box-shadow: inset 0 1px 3px rgba(0, 0, 0, 0.1);
			border: 1px solid #CCC;
			height: 110px;
			overflow: auto;
			-webkit-border-radius: 3px;
			-moz-border-radius: 3px;
			border-radius: 3px;
			margin-left: 0;
		}

		.imagePicker img {
			margin: 5px;
			border: 2px solid transparent;
		}

		.imagePicker .current {
			border: 2px dotted #555;
		}

		label {
			font-weight: bold;
		}

		.form-actions label {
			float: left;
			margin-top: 0.75em;
		}

		fieldset input,
		fieldset textarea {
			width: 90%;
			border-color: gray;
		}

		@media all and (max-width: 550px) {
			.modal {
				width: 95%;
			}
		}

		#help {
			position: absolute;
			border: 0;
			right: 4px;
			top: 5px;
			text-indent: -9999px;
			color: transparent;
			height: 16px;
			width: 16px;
			background: none;
			background-image: url(/bags/common/tiddlers/help.png);
			background-repeat: no-repeat;
			background-color: white;
			z-index: 2;
			border-radius: 10px;
		}

		#help-info {
			padding: 0;
			border: 1px solid gray;
			width: 60%;
			height: 50px;
			color: #404040;
			background-color: white;
			position: absolute;
			top: 5px;
			right: 5px;
			z-index: 1;
			cursor: auto;
			border-radius: 5px;

		}

		#help-info p {
			padding: 10px 25px;
			margin-bottom: 0;
		}
	</style>
</head>
<body>
	<div id="container">
		<form action="#" class="modal">
			<div class="modal-header">
				<button id="help">help</button>
				<div id="help-info" style="display:none;"><p>
				Found something interesting? Write about it in your own space. <a href="//docs.tiddlyspace.com/Reply to this Tiddler" target="_blank">Find out more</a>
				</p></div>
				<ul class="nav nav-tabs" data-tabs="tabs">
					<li class="active" data-tab-name="post"><a href="#postForm">Reply</a></li>
				</ul>
			</div>


			<fieldset id="postForm" class="modal-body">
				<label>Title
					<input type="text" name="title">
				</label>
				<input type="hidden" name="url">
				<label>Post
					<textarea name="text" rows="8"></textarea>
				</label>
				<label>Tags
					<input type="text" name="tags" value="">
				</label>
			</fieldset>


			<div class="form-actions">
				<label class="checkbox">
					<input type="checkbox" name="private" val="private">
					keep private
				</label>
				<input type="submit" class="btn primary btn-large" value="Done">
				<input type="button" class="btn btn-large closeBtn" value="Cancel">
			</div>
		</form>
	</div>

	<script type="text/javascript"
            src="/bags/common/tiddlers/jquery.js"></script>
	<script type="text/javascript" src="/bags/tiddlyspace/tiddlers/chrjs"></script>
	<script type="text/javascript" src="/bags/common/tiddlers/_reply.js"></script>
</body>
</html>
<!DOCTYPE html>
<html>
<head>
	<meta http-equiv="Content-Type" content="text/html;charset=utf-8">
	<title>Account</title>
	<link href="/bags/common/tiddlers/profile.css" type='text/css' rel='stylesheet' >
	<link href="/bags/common/tiddlers/admin.css" type='text/css' rel='stylesheet' >
	<link href="/bags/common/tiddlers/jquery-ui.custom.css" type='text/css' rel='stylesheet' >
</head>
<body>

<div id="container">
	<div class="main section">
		<a class="app" href="/">home</a>
		<div class="left">
		<div id="siteiconArea">
		<h2>User Icon</h2>
		<div>
			<img id="siteicon" class="siteicon">
			<form id="upload" method="POST" enctype="multipart/form-data">
				<input type="hidden" name="title" value="SiteIcon" />
				<input type="hidden" name="tags" value="excludeLists">
				<input type="hidden" name="csrf_token" class="csrf" />
				<input type="file" name="file" accept="image/*" />
				<input type="submit" value="upload" />
			</form>
			<div id="dropzone">Drop file here
				<img class="notloading" src="/bags/common/tiddlers/ajax-loader.gif" alt="submitting SiteIcon" />
			</div>
		</div>
		</div>
		<h2>Find Space</h2>
		<form class="spaceSearch">
			<input class="inputBox" type="text" placeholder="find space" />
			<a href="http://docs.tiddlyspace.com/What%20is%20a%20Space%3F" class="help"
				title="What is a space?">What is a space?</a>
			<button>view all</button>
		</form>
		<div class='list-container'>
			You are a member of the following spaces:
			<ul class='ts-space-search'>
			</ul>
		</div>
		<h2>Create New Space</h2>
		<form class="ts-spaces">
			<input class="inputBox" type="text" name="spacename" placeholder="space name"><span class="hostSuffix">.tiddlyspace.com</span>
			<input type="submit" value="Create Space" />
		</form>
		</div>
		<div class="right">
		<h2>Change Password</h2>
		<form class="ts-password">
			<input class="inputBox" placeholder="existing password" type="password" name="password">
			<input class="inputBox" placeholder="new password" type="password" name="new_password">
			<input class="inputBox" placeholder="new password"	type="password" name="new_password_confirm">
			<input type="submit" value="Change password">
		</form>
		<h2>OpenID</h2>
		<h3>Why OpenID?</h3>
		<a href="http://openid.net/"><img src="/bags/common/tiddlers/openid.png" alt="openid" ></a><br />
		Use just one username and password across hundreds of OpenID-enabled sites.<br />
		It's an open standard.<br />
		<a href="http://openid.net/what/">learn more</a>
		<ul class="ts-identities"></ul>
		<form class="ts-openid" target="_top">
			<div>
				Add an openid:
			</div>
			<input class="inputBox" type="text" name="openid" placeholder="your openid" />
			<input type="submit" value="Register" />
			<a href="http://openid.net/get-an-openid/" class="help"
			title="What is an open id?">What is an open id?</a>
		</form>
		</div>
		<div class="clear"></div>
	</div>
</div>
<script src="/bags/common/tiddlers/backstage.js"></script>
<script src='/bags/common/tiddlers/jquery.js'></script>
<script src='/bags/tiddlyspace/tiddlers/chrjs'></script>
<script src='/bags/common/tiddlers/chrjs.space'></script>
<script src='/bags/common/tiddlers/chrjs.users'></script>
<script src='/bags/common/tiddlers/chrjs.identities'></script>
<script src="/bags/common/tiddlers/jquery-ui.custom.js"></script>
<script src='/bags/common/tiddlers/jquery-form.js'></script>
<script src="/bags/common/tiddlers/siteiconupload.js"></script>
<script src='/bags/common/tiddlers/ts.js'></script>
<script src="/status.js"></script>
<script type="text/javascript">
/*
 * jQuery UI Autocomplete HTML Extension
 *
 * Copyright 2010, Scott González (http://scottgonzalez.com)
 * Dual licensed under the MIT or GPL Version 2 licenses.
 *
 * http://github.com/scottgonzalez/jquery-ui-extensions
 */
(function( $ ) {

var proto = $.ui.autocomplete.prototype,
	initSource = proto._initSource;

function filter( array, term ) {
	var matcher = new RegExp( $.ui.autocomplete.escapeRegex(term), "i" );
	return $.grep( array, function(value) {
		return matcher.test( $( "<div>" ).html( value.label || value.value || value ).text() );
	});
}

$.extend( proto, {
	_initSource: function() {
		if ( this.options.html && $.isArray(this.options.source) ) {
			this.source = function( request, response ) {
				response( filter( this.options.source, request.term ) );
			};
		} else {
			initSource.call( this );
		}
	},

	_renderItem: function( ul, item) {
		return $( "<li></li>" )
			.data( "item.autocomplete", item )
			.append( $( "<a></a>" )[ this.options.html ? "html" : "text" ]( item.label ) )
			.appendTo( ul );
	}
});

})( jQuery );

/***
_accounts application specific javascript
***/
var link;
ts.init(function(ts) {
	if(ts.user.anon) { // redirect to homepage when user not logged in
		window.location = ts.getHost();
	} else if(ts.user.name === ts.currentSpace){
		initSiteIconUpload(ts.user.name);
	} else {
		link = $("<a />").attr("href", ts.getHost(ts.user.name) + "/_account").text("Change User Icon");
		$("#siteiconArea div").empty().append(link);
	}
	$(".hostSuffix").text("." + ts.getHost("").split("//")[1]);
	ts.getSpaces(function(spaces) {
		$("<div class='info' />").text("You have " + spaces.length + " spaces.").insertBefore($(".spaceSearch")[0]);
		$("form.spaceSearch input").autocomplete({
			html: true,
			source: function(req, response) {
				ts.getSpaces(function(spaces) {
					var selected = [];
					for(var i = 0; i < spaces.length; i++) {
						var space = spaces[i];
						if(space.name.indexOf(req.term) > -1) {
							var host = ts.getHost(space.name) ;
							var img = host + "/SiteIcon";
							selected.push({
								value: space.name,
								label: '<a href="' + host + '" target="_parent" class="autocompleteLink"><img src="' + img + '" style="height:24px;width:auto;max-height:24px;max-width:24px;"/>' + space.name + '</a>'
							});
						}
					}
					response(selected);
				});
			},
			select: function(event, ui) {
				window.top.location = ts.getHost(ui.item.value);
			}
		});

		var $ul = $('.ts-space-search');
		$.each(spaces, function(i, space) {
			$ul.append($('<li/>').html($('<a/>').attr('href', space.uri)
				.text(space.name)));
		});

		$('form.spaceSearch button').click(function(ev) {
			$('.list-container').slideToggle('fast');
			ev.preventDefault();
			return false;
		});
	});
});

if(window != window.top) {
	$("html").addClass("iframeMode");
	$("a").live("click",function(ev) {
		$(ev.target).attr("target", "_parent");
	});
}
</script>
<!--[if lt IE 8]>
<script type="text/javascript" src="/bags/common/tiddlers/json2.js"></script>
<![endif]-->
</body>
</html>
!Upload an icon
<<tiddler spaceIcon>>
!Describe your space
If you haven't already done so, you should provide a brief decscription of yourself and what you're using this space for. To do this, just edit the [[SiteInfo]] tiddler (keeping the title the same of course).

!Change the title
<<tiddler spaceTitle>>
!Change the theme
<<tiddler colorScheme>>
!Change the menu
If you'd like to change the menu items along the top, you can edit the [[MainMenu]] tiddler.

!Change the default tiddlers
<<tiddler setDefaultTiddlers>>
!More Advanced customisations
If you know HTML and CSS, you can edit some or all of the following tiddlers to customise your space further:
* PageTemplate
* EditTemplate
* ViewTemplate
* StyleSheet
*An understanding of the basic principles of vascular Doppler US is required to successfully perform liver Doppler US
*The conventional nomenclature used to describe the waveforms encountered at liver Doppler US remains inconsistent
**however, systematic characterization can be achieved in a reproducible manner.

*Pathologic conditions such as portal hypertension, right-sided heart failure, and tricuspid regurgitation have characteristic effects on Doppler waveforms.

*Doppler US remains the “workhorse” modality for the evaluation of TIPS patency. 
**Competency in interpreting these examinations requires an 
***understanding of TIPS anatomy and expected flow patterns, 
***the availability of prior examination records, and a 
***knowledge of established criteria for shunt failure.
*The efficacy of N-acetylcysteine to reduce the incidence of CIN is controversial
**There is evidence that it reduces serum creatinine in normal volunteers without changing cystatin C (said to be a better marker of GFR than serum creatinine)
***This raises the possibility that N-acetylcysteine might be simply lowering serum creatinine, so patients do not meet the laboratory criteria for CIN, but not preventing the renal damage
***As considerably more investigation is needed, the, use of N-acetylcysteine should not be considered as a substitute for close attention to renal function and adequate hydration

*regimen of oral acetylcysteine, 
**600 mg twice daily on the day before and on the day of administration of iodinated contrast media
***is simple, inexpensive, and has few contraindications (although allergic reactions have been rarely reported)
**higher doses may be more effective if the agent is effective at all
*IV regimen 
**beginning 30 minutes prior to contrast media administration may be considered (150 mg/kg in 200 ml of D5W over 30 minutes, followed by 50 mg/kg in 500 ml of D5W over 4 hours) 
**IV administration may have a higher rate of adverse effects than oral administration

*The evidence for other potentially renal-protective medications is even less convincing, such as 
**theophylline
**enodthelin-1, and 
**IV infusion of fenoldopam, 
/***
|''Name''|TiddlySpaceConfig|
|''Version''|0.7.7|
|''Description''|TiddlySpace configuration|
|''Status''|stable|
|''Source''|http://github.com/TiddlySpace/tiddlyspace/raw/master/src/plugins/TiddlySpaceConfig.js|
|''CoreVersion''|2.6.1|
|''Requires''|TiddlyWebConfig ServerSideSavingPlugin TiddlyFileImporter|
!Code
***/
//{{{
(function($) {

var tweb = config.extensions.tiddlyweb;

var recipe = config.defaultCustomFields["server.workspace"].split("recipes/")[1];
var currentSpace; // assigned later

var disabledTabs = [];

var coreBags = ["system", "tiddlyspace"];
var systemSpaces = ["plugins", "info", "images", "theme"];
systemSpaces = $.map(systemSpaces, function(item, i) {
	return "system-%0_public".format(item);
});

// hijack search macro to add custom attributes for mobile devices
var _search = config.macros.search.handler;
config.macros.search.handler = function(place, macroName, params) {
	_search.apply(this, arguments);
	$(".searchField:input", place).
		attr({ autocapitalize: "off", autocorrect: "off" });
};

// arg is either a container name or a tiddler object
// if fuzzy is truthy, space may be inferred from workspace (for new tiddlers)
// returns space object or false
var determineSpace = function(arg, fuzzy) {
	if(typeof arg == "string") { // container name
		var space = split(arg, "_", "r");
		return ["public", "private"].contains(space.type) ? space : false;
	} else if(arg) { // tiddler
		var container = determineContainer(arg, fuzzy);
		return container ? determineSpace(container.name, fuzzy) : false;
	} else {
		return false;
	}
};

// if fuzzy is truthy, container may be inferred from workspace for new tiddlers
// returns container object or false
var determineContainer = function(tiddler, fuzzy) { // TODO: expose?
	var bag = tiddler.fields["server.bag"];
	var recipe = tiddler.fields["server.recipe"]; // XXX: unused/irrelevant/redundant!?
	if(bag) {
		return { type: "bag", name: bag };
	} else if(recipe) {
		return { type: "recipe", name: recipe };
	} else if(fuzzy) { // new tiddler
		var workspace = tiddler.fields["server.workspace"];
		if(workspace) {
			var container = split(workspace, "/", "l");
			return ["bags", "recipes"].contains(container.type) ? container : false;
		} else {
			return false;
		}
	} else {
		return false;
	}
};

// hijack removeTiddlerCallback to restore tiddler from recipe cascade -- TODO: move into TiddlyWebWiki?
var sssp = config.extensions.ServerSideSavingPlugin;
var _removeTiddlerCallback = sssp.removeTiddlerCallback;
sssp.removeTiddlerCallback = function(context, userParams) {
	var title = context.tiddler.title;
	var recipe = context.tiddler.fields["server.recipe"];
	_removeTiddlerCallback.apply(this, arguments);
	if(recipe) {
		context.workspace = "recipes/" + recipe;
		var callback = function(context, userParams) {
			if(context.status) {
				var dirty = store.isDirty();
				store.saveTiddler(context.tiddler).clearChangeCount();
				store.setDirty(dirty);
			} else {
				store.notify(title, true);
			}
		};
		context.adaptor.getTiddler(title, context, null, callback);
	}
};

// splits a string once using delimiter
// mode "l" splits at the first, "r" at the last occurrence
// returns an object with members type and name
var split = function(str, sep, mode) {
	mode = mode == "r" ? "pop" : "shift"; // TODO: use +/-1 instead of "l"/"r"?
	var arr = str.split(sep);
	var type = arr.length > 1 ? arr[mode]() : null;
	return { type: type, name: arr.join(sep) };
};

var plugin = config.extensions.tiddlyspace = {
	currentSpace: determineSpace(recipe),
	coreBags: coreBags.concat(systemSpaces),

	determineSpace: determineSpace,
	isValidSpaceName: function(name) {
		return name.match(/^[a-z][0-9a-z\-]*[0-9a-z]$/) ? true : false;
	},
	getCurrentBag: function(type) {
		return "%0_%1".format(currentSpace, type);
	},
	getCurrentWorkspace: function(type) {
		return "bags/" + this.getCurrentBag(type);
	},
	// returns the URL for a space's avatar (SiteIcon) based on a server_host
	// object and an optional space name
	// optional nocors argument prevents cross-domain URLs from being generated
	getAvatar: function(host, space, nocors) {
		if(space && typeof space != "string") { // backwards compatibility -- XXX: deprecated
			space = space.name;
		}
		var subdomain = nocors ? currentSpace : space;
		host = host ? this.getHost(host, subdomain) : "";
		var bag = space ? "%0_public".format(space) : "tiddlyspace";
		return "%0/bags/%1/tiddlers/SiteIcon".format(host, bag);
	},
	// returns the URL based on a server_host object (scheme, host, port) and an
	// optional subdomain
	getHost: function(host, subdomain) {
		if(host === undefined) { // offline
			tweb.status.server_host = {}; // prevents exceptions further down the stack -- XXX: hacky workaround, breaks encapsulation
			return null;
		}
		subdomain = subdomain ? subdomain + "." : "";
		var url = "%0://%1%2".format(host.scheme, subdomain, host.host);
		var port = host.port;
		if(port && !["80", "443"].contains(port)) {
			url += ":" + port;
		}
		return url;
	},
	disableTab: function(tabTiddler) {
		if(typeof(tabTiddler) == "string") {
			disabledTabs.push(tabTiddler);
		} else {
			for(var i = 0; i < tabTiddler.length; i++) {
				plugin.disableTab(tabTiddler[i]);
			}
		}
	},
    checkSyncStatus: function(tiddler) {
		if(tiddler) {
			var title = typeof(tiddler) === "string" ? tiddler : tiddler.title;
			var el = story.getTiddler(title) || false;
			if(el) {
				refreshElements(el);
			}
		}
	},
	isDisabledTab: function(tabTitle) {
		var match = new RegExp("(?:\\[\\[([^\\]]+)\\]\\])", "mg").exec(tabTitle);
		var tabIdentifier = match ? match[1] : tabTitle;
		return disabledTabs.contains(tabIdentifier);
	},
	getCSRFToken: window.getCSRFToken || null // this may not have been processed yet
};

currentSpace = plugin.currentSpace.name;

tweb.serverPrefix = tweb.host.split("/")[3] || ""; // XXX: assumes root handler
tweb.getStatus(function(status) {
	var url = plugin.getHost(status.server_host);
	tweb.status.server_host.url = url;
	config.messages.tsVersion = status.version;
});

if(window.location.protocol == "file:") {
	// enable AutoSave by default
	config.options.chkAutoSave = config.options.chkAutoSave === undefined ?
		true : config.options.chkAutoSave;
} else {
	// set global read-only mode based on membership heuristics
	var indicator = store.getTiddler("SiteTitle") || tiddler;
	readOnly = !(recipe.split("_").pop() == "private" ||
		tweb.hasPermission("write", indicator));
	// replace TiddlyWiki's ImportTiddlers due to cross-domain restrictions
	if(config.macros.fileImport) {
		$.extend(config.macros.importTiddlers, config.macros.fileImport);
	}
}

// hijack saveChanges to ensure SystemSettings is private by default
var _saveChanges = saveChanges;
saveChanges = function(onlyIfDirty, tiddlers) {
	if(tiddlers && tiddlers.length == 1 &&
			tiddlers[0] && tiddlers[0].title == "SystemSettings") {
		var fields = tiddlers[0].fields;
		delete fields["server.recipe"];
		fields["server.bag"] = plugin.getCurrentBag("private");
		fields["server.workspace"] = plugin.getCurrentWorkspace("private");
	}
	return _saveChanges.apply(this, arguments);
};

// ensure backstage is always initialized
// required to circumvent TiddlyWiki's read-only based handling
config.macros.backstageInit = {
	init: function() {
		showBackstage = true;
	}
};

// disable evaluated macro parameters for security reasons
config.evaluateMacroParameters = "none";
var _parseParams = String.prototype.parseParams;
String.prototype.parseParams = function(defaultName, defaultValue, allowEval,
		noNames, cascadeDefaults) {
	if(config.evaluateMacroParameters == "none") {
		arguments[2] = false;
	}
	return _parseParams.apply(this, arguments);
};

var _tabsMacro = config.macros.tabs.handler;
config.macros.tabs.handler = function(place, macroName, params) {
	var newParams = [params[0]]; // keep cookie name
	for(var i = 1; i < params.length; i += 3) {
		var tabTitle = params[i + 2];
		if(!plugin.isDisabledTab(tabTitle)){
			newParams = newParams.concat(params[i], params[i + 1], tabTitle);
		}
	}
	_tabsMacro.apply(this, [place, macroName, newParams]);
};

// disable ControlView for XHRs by default
$.ajaxSetup({
	beforeSend: function(xhr) {
		xhr.setRequestHeader("X-ControlView", "false");
	}
});
// TiddlyWeb adaptor currently still uses httpReq, which needs extra magic -- XXX: obsolete this!
var _httpReq = httpReq;
httpReq = function(type, url, callback, params, headers, data, contentType,
		username, password, allowCache) {
	headers = headers || {};
	headers["X-ControlView"] = "false";
	_httpReq.apply(this, arguments);
};

// register style sheet for backstage separately (important)
store.addNotification("StyleSheetBackstage", refreshStyles);

// option for default privacy setting
config.optionsDesc.chkPrivateMode = "Set your default privacy mode to private";
config.optionsSource.chkPrivateMode = "setting";
config.options.chkPrivateMode = config.options.chkPrivateMode || false;
saveSystemSetting("chkPrivateMode", true);
config.defaultCustomFields["server.workspace"] = plugin.
	getCurrentWorkspace(config.options.chkPrivateMode ? "private" : "public");

config.paramifiers.follow = {
	onstart: function(v) {
		if(!readOnly) {
			var bag = "%0_public".format(currentSpace);
			story.displayTiddler(null, v, DEFAULT_EDIT_TEMPLATE, null, null,
				"server.bag:%0 server.workspace:bags/%0".format(bag));
			story.setTiddlerTag(v, "follow", 1);
			story.focusTiddler(v, "text");
		}
	}
};

var fImport = config.macros.fileImport;
if(fImport) {
	fImport.uploadTo = "Upload to: ";
	var _createForm = config.macros.fileImport.createForm;
	config.macros.fileImport.createForm = function(place, wizard, iframeName) {
		var container = $("<div />").text(fImport.uploadTo).appendTo(place);
		var select = $('<select name="mode" />').appendTo(container)[0];
		$('<option value="private" selected>private</a>').appendTo(select);
		$('<option value="public">public</a>').appendTo(select);
		wizard.setValue("importmode", select);
		_createForm.apply(this, [place, wizard, iframeName]);
	};

	var _onGet = config.macros.importTiddlers.onGetTiddler;
	config.macros.importTiddlers.onGetTiddler = function(context, wizard) {
		var type = $(wizard.getValue("importmode")).val();
		var ws =  plugin.getCurrentWorkspace(type);
		wizard.setValue("workspace", ws);
		_onGet.apply(this, [context, wizard]);
	};
}

config.extensions.ServerSideSavingPlugin.reportSuccess = function(msg, tiddler) {
	plugin.checkSyncStatus(tiddler);
	msg = config.extensions.ServerSideSavingPlugin.locale[msg];
	var link = "/" + encodeURIComponent(tiddler.title);
	displayMessage(msg.format([tiddler.title]), link);
};


})(jQuery);
//}}}
!usage
{{{[img[p.png]]}}}
[img[p.png]]
!notes
Dynamic T1-weighted MR images using a 3D volume interpolated technique after IV bolus of hepatocyte selective gadolinium chelate (Gd-EOB-DTPA) in a normal liver. Imaging was performed in the (A) arterial, (B) portovenous and (C) interstitial phases of contrast enhancement, similar to the use of non-specific extracellular gadolinium chelates. However, a (D) delayed hepatic phase (15–30 min) was observed with intense hepatic parenchymal enhancement accompanied by clearance of contrast medium from hepatic vasculature due to hepatocyte contrast excretion. Lesions of non-hepatocellular origin (e.g. metastases) would increase in conspicuity during this phase
!type
image/png
!file
file:////Users/iki/Desktop/p.png
!url

!data
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
/***
|''Name''|TiddlyWebAdaptor|
|''Description''|adaptor for interacting with TiddlyWeb|
|''Author:''|FND|
|''Contributors''|Chris Dent, Martin Budden|
|''Version''|1.4.10|
|''Status''|stable|
|''Source''|http://svn.tiddlywiki.org/Trunk/association/adaptors/TiddlyWebAdaptor.js|
|''CodeRepository''|http://svn.tiddlywiki.org/Trunk/association/|
|''License''|[[BSD|http://www.opensource.org/licenses/bsd-license.php]]|
|''CoreVersion''|2.5|
|''Keywords''|serverSide TiddlyWeb|
!Notes
This plugin includes [[jQuery JSON|http://code.google.com/p/jquery-json/]].
!To Do
* createWorkspace
* document custom/optional context attributes (e.g. filters, query, revision) and tiddler fields (e.g. server.title, origin)
!Code
***/
//{{{
(function($) {

var adaptor = config.adaptors.tiddlyweb = function() {};

adaptor.prototype = new AdaptorBase();
adaptor.serverType = "tiddlyweb";
adaptor.serverLabel = "TiddlyWeb";
adaptor.mimeType = "application/json";

adaptor.parsingErrorMessage = "Error parsing result from server";
adaptor.noBagErrorMessage = "no bag specified for tiddler";
adaptor.locationIDErrorMessage = "no bag or recipe specified for tiddler"; // TODO: rename

// retrieve current status (requires TiddlyWeb status plugin)
adaptor.prototype.getStatus = function(context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	var uriTemplate = "%0/status";
	var uri = uriTemplate.format([context.host]);
	var req = httpReq("GET", uri, adaptor.getStatusCallback, context,
		null, null, null, null, null, true);
	return typeof req == "string" ? req : true;
};

adaptor.getStatusCallback = function(status, context, responseText, uri, xhr) {
	context.status = responseText ? status : false;
	try {
		context.statusText = xhr.statusText;
	} catch(exc) { // offline (Firefox)
		context.status = false;
		context.statusText = null;
	}
	context.httpStatus = xhr.status;
	if(context.status) {
		context.serverStatus = $.evalJSON(responseText); // XXX: error handling!?
	}
	if(context.callback) {
		context.callback(context, context.userParams);
	}
};

// retrieve a list of workspaces
adaptor.prototype.getWorkspaceList = function(context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	context.workspaces = [];
	var uriTemplate = "%0/recipes"; // XXX: bags?
	var uri = uriTemplate.format([context.host]);
	var req = httpReq("GET", uri, adaptor.getWorkspaceListCallback,
		context, { accept: adaptor.mimeType }, null, null, null, null, true);
	return typeof req == "string" ? req : true;
};

adaptor.getWorkspaceListCallback = function(status, context, responseText, uri, xhr) {
	context.status = status;
	context.statusText = xhr.statusText;
	context.httpStatus = xhr.status;
	if(status) {
		try {
			var workspaces = $.evalJSON(responseText);
		} catch(ex) {
			context.status = false; // XXX: correct?
			context.statusText = exceptionText(ex, adaptor.parsingErrorMessage);
			if(context.callback) {
				context.callback(context, context.userParams);
			}
			return;
		}
		context.workspaces = workspaces.map(function(itm) { return { title: itm }; });
	}
	if(context.callback) {
		context.callback(context, context.userParams);
	}
};

// retrieve a list of tiddlers
adaptor.prototype.getTiddlerList = function(context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	var uriTemplate = "%0/%1/%2/tiddlers%3";
	var params = context.filters ? "?" + context.filters : "";
	if(context.format) {
		params = context.format + params;
	}
	var workspace = adaptor.resolveWorkspace(context.workspace);
	var uri = uriTemplate.format([context.host, workspace.type + "s",
		adaptor.normalizeTitle(workspace.name), params]);
	var req = httpReq("GET", uri, adaptor.getTiddlerListCallback,
		context, merge({ accept: adaptor.mimeType }, context.headers), null, null, null, null, true);
	return typeof req == "string" ? req : true;
};

adaptor.getTiddlerListCallback = function(status, context, responseText, uri, xhr) {
	context.status = status;
	context.statusText = xhr.statusText;
	context.httpStatus = xhr.status;
	if(status) {
		context.tiddlers = [];
		try {
			var tiddlers = $.evalJSON(responseText); //# NB: not actual tiddler instances
		} catch(ex) {
			context.status = false; // XXX: correct?
			context.statusText = exceptionText(ex, adaptor.parsingErrorMessage);
			if(context.callback) {
				context.callback(context, context.userParams);
			}
			return;
		}
		for(var i = 0; i < tiddlers.length; i++) {
			var tiddler = adaptor.toTiddler(tiddlers[i], context.host);
			context.tiddlers.push(tiddler);
		}
	}
	if(context.callback) {
		context.callback(context, context.userParams);
	}
};

// perform global search
adaptor.prototype.getSearchResults = function(context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	var uriTemplate = "%0/search?q=%1%2";
	var filterString = context.filters ? ";" + context.filters : "";
	var uri = uriTemplate.format([context.host, context.query, filterString]); // XXX: parameters need escaping?
	var req = httpReq("GET", uri, adaptor.getSearchResultsCallback,
		context, { accept: adaptor.mimeType }, null, null, null, null, true);
	return typeof req == "string" ? req : true;
};

adaptor.getSearchResultsCallback = function(status, context, responseText, uri, xhr) {
	adaptor.getTiddlerListCallback(status, context, responseText, uri, xhr); // XXX: use apply?
};

// retrieve a particular tiddler's revisions
adaptor.prototype.getTiddlerRevisionList = function(title, limit, context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	var uriTemplate = "%0/%1/%2/tiddlers/%3/revisions";
	var workspace = adaptor.resolveWorkspace(context.workspace);
	var uri = uriTemplate.format([context.host, workspace.type + "s",
		adaptor.normalizeTitle(workspace.name), adaptor.normalizeTitle(title)]);
	var req = httpReq("GET", uri, adaptor.getTiddlerRevisionListCallback,
		context, merge({ accept: adaptor.mimeType }, context.headers), null, null, null, null, true);
	return typeof req == "string" ? req : true;
};

adaptor.getTiddlerRevisionListCallback = function(status, context, responseText, uri, xhr) {
	context.status = status;
	context.statusText = xhr.statusText;
	context.httpStatus = xhr.status;
	if(status) {
		context.revisions = [];
		try {
			var tiddlers = $.evalJSON(responseText); //# NB: not actual tiddler instances
		} catch(ex) {
			context.status = false; // XXX: correct?
			context.statusText = exceptionText(ex, adaptor.parsingErrorMessage);
			if(context.callback) {
				context.callback(context, context.userParams);
			}
			return;
		}
		for(var i = 0; i < tiddlers.length; i++) {
			var tiddler = adaptor.toTiddler(tiddlers[i], context.host);
			context.revisions.push(tiddler);
		}
		var sortField = "server.page.revision";
		context.revisions.sort(function(a, b) {
			return a.fields[sortField] < b.fields[sortField] ? 1 :
				(a.fields[sortField] == b.fields[sortField] ? 0 : -1);
		});
	}
	if(context.callback) {
		context.callback(context, context.userParams);
	}
};

// retrieve an individual tiddler revision -- XXX: breaks with standard arguments list -- XXX: convenience function; simply use getTiddler?
adaptor.prototype.getTiddlerRevision = function(title, revision, context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	context.revision = revision;
	return this.getTiddler(title, context, userParams, callback);
};

// retrieve an individual tiddler
//# context is an object with members host and workspace
//# callback is passed the new context and userParams
adaptor.prototype.getTiddler = function(title, context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	context.title = title;
	if(context.revision) {
		var uriTemplate = "%0/%1/%2/tiddlers/%3/revisions/%4";
	} else {
		uriTemplate = "%0/%1/%2/tiddlers/%3";
	}
	if(!context.tiddler) {
		context.tiddler = new Tiddler(title);
	}
	context.tiddler.fields["server.type"] = adaptor.serverType;
	context.tiddler.fields["server.host"] = AdaptorBase.minHostName(context.host);
	context.tiddler.fields["server.workspace"] = context.workspace;
	var workspace = adaptor.resolveWorkspace(context.workspace);
	var uri = uriTemplate.format([context.host, workspace.type + "s",
		adaptor.normalizeTitle(workspace.name), adaptor.normalizeTitle(title),
		context.revision]);
	var req = httpReq("GET", uri, adaptor.getTiddlerCallback, context,
		merge({ accept: adaptor.mimeType }, context.headers), null, null, null, null, true);
	return typeof req == "string" ? req : true;
};

adaptor.getTiddlerCallback = function(status, context, responseText, uri, xhr) {
	context.status = status;
	context.statusText = xhr.statusText;
	context.httpStatus = xhr.status;
	if(status) {
		try {
			var tid = $.evalJSON(responseText);
		} catch(ex) {
			context.status = false;
			context.statusText = exceptionText(ex, adaptor.parsingErrorMessage);
			if(context.callback) {
				context.callback(context, context.userParams);
			}
			return;
		}
		var tiddler = adaptor.toTiddler(tid, context.host);
		tiddler.title = context.tiddler.title;
		tiddler.fields["server.etag"] = xhr.getResponseHeader("Etag");
		// normally we'd assign context.tiddler = tiddler here - but we can't do
		// that because of IE, which triggers getTiddler in putTiddlerCallback,
		// and since ServerSideSavingPlugin foolishly relies on persistent
		// object references, we need to merge the data into the existing object
		$.extend(context.tiddler, tiddler);
	}
	if(context.callback) {
		context.callback(context, context.userParams);
	}
};

// retrieve tiddler chronicle (all revisions)
adaptor.prototype.getTiddlerChronicle = function(title, context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	context.title = title;
	var uriTemplate = "%0/%1/%2/tiddlers/%3/revisions?fat=1";
	var workspace = adaptor.resolveWorkspace(context.workspace);
	var uri = uriTemplate.format([context.host, workspace.type + "s",
		adaptor.normalizeTitle(workspace.name), adaptor.normalizeTitle(title)]);
	var req = httpReq("GET", uri, adaptor.getTiddlerChronicleCallback,
		context, { accept: adaptor.mimeType }, null, null, null, null, true);
	return typeof req == "string" ? req : true;
};

adaptor.getTiddlerChronicleCallback = function(status, context, responseText, uri, xhr) {
	context.status = status;
	context.statusText = xhr.statusText;
	context.httpStatus = xhr.status;
	if(status) {
		context.responseText = responseText;
	}
	if(context.callback) {
		context.callback(context, context.userParams);
	}
};

// store an individual tiddler
adaptor.prototype.putTiddler = function(tiddler, context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	context.title = tiddler.title;
	context.tiddler = tiddler;
	context.host = context.host || this.fullHostName(tiddler.fields["server.host"]);
	var uriTemplate = "%0/%1/%2/tiddlers/%3";
	try {
		context.workspace = context.workspace || tiddler.fields["server.workspace"];
		var workspace = adaptor.resolveWorkspace(context.workspace);
	} catch(ex) {
		return adaptor.locationIDErrorMessage;
	}
	var uri = uriTemplate.format([context.host, workspace.type + "s",
		adaptor.normalizeTitle(workspace.name),
		adaptor.normalizeTitle(tiddler.title)]);
	var etag = adaptor.generateETag(workspace, tiddler);
	var headers = etag ? { "If-Match": etag } : null;
	var payload = {
		type: tiddler.fields["server.content-type"] || null,
		text: tiddler.text,
		tags: tiddler.tags,
		fields: $.extend({}, tiddler.fields)
	};
	delete payload.fields.changecount;
	$.each(payload.fields, function(key, value) {
		if(key.indexOf("server.") == 0) {
			delete payload.fields[key];
		}
	});
	payload = $.toJSON(payload);
	var req = httpReq("PUT", uri, adaptor.putTiddlerCallback,
		context, headers, payload, adaptor.mimeType, null, null, true);
	return typeof req == "string" ? req : true;
};

adaptor.putTiddlerCallback = function(status, context, responseText, uri, xhr) {
	context.status = [204, 1223].contains(xhr.status);
	context.statusText = xhr.statusText;
	context.httpStatus = xhr.status;
	if(context.status) {
		var loc = xhr.getResponseHeader("Location");
		var etag = xhr.getResponseHeader("Etag");
		if(loc && etag) {
			var bag = loc.split("/bags/").pop().split("/")[0];
			context.tiddler.fields["server.bag"] = bag;
			context.tiddler.fields["server.workspace"] = "bags/" + bag;
			var rev = etag.split("/").pop().split(/;|:/)[0];
			context.tiddler.fields["server.page.revision"] = rev;
			context.tiddler.fields["server.etag"] = etag;
			if(context.callback) {
				context.callback(context, context.userParams);
			}
		} else { // IE
			context.adaptor.getTiddler(context.tiddler.title, context,
				context.userParams, context.callback);
		}
	} else if(context.callback) {
		context.callback(context, context.userParams);
	}
};

// store a tiddler chronicle
adaptor.prototype.putTiddlerChronicle = function(revisions, context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	context.title = revisions[0].title;
	var headers = null;
	var uriTemplate = "%0/%1/%2/tiddlers/%3/revisions";
	var host = context.host || this.fullHostName(tiddler.fields["server.host"]);
	var workspace = adaptor.resolveWorkspace(context.workspace);
	var uri = uriTemplate.format([host, workspace.type + "s",
		adaptor.normalizeTitle(workspace.name),
		adaptor.normalizeTitle(context.title)]);
	if(workspace.type == "bag") { // generate ETag
		var etag = [adaptor.normalizeTitle(workspace.name),
			adaptor.normalizeTitle(context.title), 0].join("/"); //# zero-revision prevents overwriting existing contents
		headers = { "If-Match": '"' + etag + '"' };
	}
	var payload = $.toJSON(revisions);
	var req = httpReq("POST", uri, adaptor.putTiddlerChronicleCallback,
		context, headers, payload, adaptor.mimeType, null, null, true);
	return typeof req == "string" ? req : true;
};

adaptor.putTiddlerChronicleCallback = function(status, context, responseText, uri, xhr) {
	context.status = [204, 1223].contains(xhr.status);
	context.statusText = xhr.statusText;
	context.httpStatus = xhr.status;
	if(context.callback) {
		context.callback(context, context.userParams);
	}
};

// store a collection of tiddlers (import TiddlyWiki HTML store)
adaptor.prototype.putTiddlerStore = function(store, context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	var uriTemplate = "%0/%1/%2/tiddlers";
	var host = context.host;
	var workspace = adaptor.resolveWorkspace(context.workspace);
	var uri = uriTemplate.format([host, workspace.type + "s",
		adaptor.normalizeTitle(workspace.name)]);
	var req = httpReq("POST", uri, adaptor.putTiddlerStoreCallback,
		context, null, store, "text/x-tiddlywiki", null, null, true);
	return typeof req == "string" ? req : true;
};

adaptor.putTiddlerStoreCallback = function(status, context, responseText, uri, xhr) {
	context.status = [204, 1223].contains(xhr.status);
	context.statusText = xhr.statusText;
	context.httpStatus = xhr.status;
	if(context.callback) {
		context.callback(context, context.userParams);
	}
};

// rename an individual tiddler or move it to a different workspace -- TODO: make {from|to}.title optional
//# from and to are objects with members title and workspace (bag; optional),
//# representing source and target tiddler, respectively
adaptor.prototype.moveTiddler = function(from, to, context, userParams, callback) { // XXX: rename parameters (old/new)?
	var self = this;
	var newTiddler = store.getTiddler(from.title) || store.getTiddler(to.title); //# local rename might already have occurred
	var oldTiddler = $.extend(true, {}, newTiddler); //# required for eventual deletion
	oldTiddler.title = from.title; //# required for original tiddler's ETag
	var _getTiddlerChronicle = function(title, context, userParams, callback) {
		return self.getTiddlerChronicle(title, context, userParams, callback);
	};
	var _putTiddlerChronicle = function(context, userParams) {
		if(!context.status) {
			return callback(context, userParams);
		}
		var revisions = $.evalJSON(context.responseText); // XXX: error handling?
		// change current title while retaining previous location
		for(var i = 0; i < revisions.length; i++) {
			delete revisions[i].revision;
			if(!revisions[i].fields.origin) { // NB: origin = "<workspace>/<title>"
				revisions[i].fields.origin = ["bags", revisions[i].bag, revisions[i].title].join("/");
			}
			revisions[i].title = to.title;
		}
		// add new revision
		var rev = $.extend({}, revisions[0]);
		$.each(newTiddler, function(i, item) {
			if(!$.isFunction(item)) {
				rev[i] = item;
			}
		});
		rev.title = to.title;
		rev.created = rev.created.convertToYYYYMMDDHHMM();
		rev.modified = new Date().convertToYYYYMMDDHHMM();
		delete rev.fields.changecount;
		revisions.unshift(rev);
		if(to.workspace) {
			context.workspace = to.workspace;
		} else if(context.workspace.substring(0, 4) != "bags") { // NB: target workspace must be a bag
			context.workspace = "bags/" + rev.bag;
		}
		var subCallback = function(context, userParams) {
			if(!context.status) {
				return callback(context, userParams);
			}
			context.adaptor.getTiddler(newTiddler.title, context, userParams, _deleteTiddler);
		};
		return self.putTiddlerChronicle(revisions, context, context.userParams, subCallback);
	};
	var _deleteTiddler = function(context, userParams) {
		if(!context.status) {
			return callback(context, userParams);
		}
		$.extend(true, newTiddler, context.tiddler);
		context.callback = null;
		return self.deleteTiddler(oldTiddler, context, context.userParams, callback);
	};
	callback = callback || function() {};
	context = this.setContext(context, userParams);
	context.host = context.host || oldTiddler.fields["server.host"];
	context.workspace = from.workspace || oldTiddler.fields["server.workspace"];
	return _getTiddlerChronicle(from.title, context, userParams, _putTiddlerChronicle);
};

// delete an individual tiddler
adaptor.prototype.deleteTiddler = function(tiddler, context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	context.title = tiddler.title; // XXX: not required!?
	var uriTemplate = "%0/bags/%1/tiddlers/%2";
	var host = context.host || this.fullHostName(tiddler.fields["server.host"]);
	var bag = tiddler.fields["server.bag"];
	if(!bag) {
		return adaptor.noBagErrorMessage;
	}
	var uri = uriTemplate.format([host, adaptor.normalizeTitle(bag),
		adaptor.normalizeTitle(tiddler.title)]);
	var etag = adaptor.generateETag({ type: "bag", name: bag }, tiddler);
	var headers = etag ? { "If-Match": etag } : null;
	var req = httpReq("DELETE", uri, adaptor.deleteTiddlerCallback, context, headers,
		null, null, null, null, true);
	return typeof req == "string" ? req : true;
};

adaptor.deleteTiddlerCallback = function(status, context, responseText, uri, xhr) {
	context.status = [204, 1223].contains(xhr.status);
	context.statusText = xhr.statusText;
	context.httpStatus = xhr.status;
	if(context.callback) {
		context.callback(context, context.userParams);
	}
};

// compare two revisions of a tiddler (requires TiddlyWeb differ plugin)
//# if context.rev1 is not specified, the latest revision will be used for comparison
//# if context.rev2 is not specified, the local revision will be sent for comparison
//# context.format is a string as determined by the TiddlyWeb differ plugin
adaptor.prototype.getTiddlerDiff = function(title, context, userParams, callback) {
	context = this.setContext(context, userParams, callback);
	context.title = title;

	var tiddler = store.getTiddler(title);
	try {
		var workspace = adaptor.resolveWorkspace(tiddler.fields["server.workspace"]);
	} catch(ex) {
		return adaptor.locationIDErrorMessage;
	}
	var tiddlerRef = [workspace.type + "s", workspace.name, tiddler.title].join("/");

	var rev1 = context.rev1 ? [tiddlerRef, context.rev1].join("/") : tiddlerRef;
	var rev2 = context.rev2 ? [tiddlerRef, context.rev2].join("/") : null;

	var uriTemplate = "%0/diff?rev1=%1";
	if(rev2) {
		uriTemplate += "&rev2=%2";
	}
	if(context.format) {
		uriTemplate += "&format=%3";
	}
	var host = context.host || this.fullHostName(tiddler.fields["server.host"]);
	var uri = uriTemplate.format([host, adaptor.normalizeTitle(rev1),
		adaptor.normalizeTitle(rev2), context.format]);

	if(rev2) {
		var req = httpReq("GET", uri, adaptor.getTiddlerDiffCallback, context, null,
			null, null, null, null, true);
	} else {
		var payload = {
			title: tiddler.title,
			text: tiddler.text,
			modifier: tiddler.modifier,
			tags: tiddler.tags,
			fields: $.extend({}, tiddler.fields)
		}; // XXX: missing attributes!?
		payload = $.toJSON(payload);
		req = httpReq("POST", uri, adaptor.getTiddlerDiffCallback, context,
			null, payload, adaptor.mimeType, null, null, true);
	}
	return typeof req == "string" ? req : true;
};

adaptor.getTiddlerDiffCallback = function(status, context, responseText, uri, xhr) {
	context.status = status;
	context.statusText = xhr.statusText;
	context.httpStatus = xhr.status;
	context.uri = uri;
	if(status) {
		context.diff = responseText;
	}
	if(context.callback) {
		context.callback(context, context.userParams);
	}
};

// generate tiddler information
adaptor.prototype.generateTiddlerInfo = function(tiddler) {
	var info = {};
	var uriTemplate = "%0/%1/%2/tiddlers/%3";
	var host = this.host || tiddler.fields["server.host"]; // XXX: this.host obsolete?
	host = this.fullHostName(host);
	var workspace = adaptor.resolveWorkspace(tiddler.fields["server.workspace"]);
	info.uri = uriTemplate.format([host, workspace.type + "s",
		adaptor.normalizeTitle(workspace.name),
		adaptor.normalizeTitle(tiddler.title)]);
	return info;
};

// create Tiddler instance from TiddlyWeb tiddler JSON
adaptor.toTiddler = function(json, host) {
	var created = Date.convertFromYYYYMMDDHHMM(json.created);
	var modified = Date.convertFromYYYYMMDDHHMM(json.modified);
	var fields = json.fields;
	fields["server.type"] = adaptor.serverType;
	fields["server.host"] = AdaptorBase.minHostName(host);
	fields["server.bag"] = json.bag;
	fields["server.title"] = json.title;
	if(json.recipe) {
		fields["server.recipe"] = json.recipe;
	}
	if(json.type && json.type != "None") {
		fields["server.content-type"] = json.type;
	}
	fields["server.permissions"] = json.permissions.join(", ");
	fields["server.page.revision"] = json.revision;
	fields["server.workspace"] = "bags/" + json.bag;
	var tiddler = new Tiddler(json.title);
	tiddler.assign(tiddler.title, json.text, json.modifier, modified, json.tags,
		created, json.fields, json.creator);
	return tiddler;
};

adaptor.resolveWorkspace = function(workspace) {
	var components = workspace.split("/");
	return {
		type: components[0] == "bags" ? "bag" : "recipe",
		name: components[1] || components[0]
	};
};

adaptor.generateETag = function(workspace, tiddler) {
	var revision = tiddler.fields["server.page.revision"];
	var etag = revision == "false" ? null : tiddler.fields["server.etag"];
	if(!etag && workspace.type == "bag") {
		if(typeof revision == "undefined") {
			revision = "0";
		} else if(revision == "false") {
			return null;
		}
		etag = [adaptor.normalizeTitle(workspace.name),
			adaptor.normalizeTitle(tiddler.title), revision].join("/");
		etag = '"' + etag + '"';
	}
	return etag;
};

adaptor.normalizeTitle = function(title) {
	return encodeURIComponent(title);
};

})(jQuery);


/*
 * jQuery JSON Plugin
 * version: 1.3
 * source: http://code.google.com/p/jquery-json/
 * license: MIT (http://www.opensource.org/licenses/mit-license.php)
 */
(function($){function toIntegersAtLease(n)
{return n<10?'0'+n:n;}
Date.prototype.toJSON=function(date)
{return this.getUTCFullYear()+'-'+
toIntegersAtLease(this.getUTCMonth())+'-'+
toIntegersAtLease(this.getUTCDate());};var escapeable=/["\\\x00-\x1f\x7f-\x9f]/g;var meta={'\b':'\\b','\t':'\\t','\n':'\\n','\f':'\\f','\r':'\\r','"':'\\"','\\':'\\\\'};$.quoteString=function(string)
{if(escapeable.test(string))
{return'"'+string.replace(escapeable,function(a)
{var c=meta[a];if(typeof c==='string'){return c;}
c=a.charCodeAt();return'\\u00'+Math.floor(c/16).toString(16)+(c%16).toString(16);})+'"';}
return'"'+string+'"';};$.toJSON=function(o,compact)
{var type=typeof(o);if(type=="undefined")
return"undefined";else if(type=="number"||type=="boolean")
return o+"";else if(o===null)
return"null";if(type=="string")
{return $.quoteString(o);}
if(type=="object"&&typeof o.toJSON=="function")
return o.toJSON(compact);if(type!="function"&&typeof(o.length)=="number")
{var ret=[];for(var i=0;i<o.length;i++){ret.push($.toJSON(o[i],compact));}
if(compact)
return"["+ret.join(",")+"]";else
return"["+ret.join(", ")+"]";}
if(type=="function"){throw new TypeError("Unable to convert object of type 'function' to json.");}
var ret=[];for(var k in o){var name;type=typeof(k);if(type=="number")
name='"'+k+'"';else if(type=="string")
name=$.quoteString(k);else
continue;var val=$.toJSON(o[k],compact);if(typeof(val)!="string"){continue;}
if(compact)
ret.push(name+":"+val);else
ret.push(name+": "+val);}
return"{"+ret.join(", ")+"}";};$.compactJSON=function(o)
{return $.toJSON(o,true);};$.evalJSON=function(src)
{return eval("("+src+")");};$.secureEvalJSON=function(src)
{var filtered=src;filtered=filtered.replace(/\\["\\\/bfnrtu]/g,'@');filtered=filtered.replace(/"[^"\\\n\r]*"|true|false|null|-?\d+(?:\.\d*)?(?:[eE][+\-]?\d+)?/g,']');filtered=filtered.replace(/(?:^|:|,)(?:\s*\[)+/g,'');if(/^[\],:{}\s]*$/.test(filtered))
return eval("("+src+")");else
throw new SyntaxError("Error parsing JSON, source is not valid.");};})(jQuery);
//}}}
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![[General Considerations]]

!![[Risk Factors for Adverse Intravenous Contrast Material Reactions]] 

!![[Contrast Material Reactions]]

!![[Premedication]]

!![[Breakthrough Reactions]]

!![[Other Considerations]]
!!Avoidance of Iodinated Contrast Media

*The risk of developing CIN is not an absolute but a relative (and often weak relative) contraindication to the administration of IV iodinated contrast media
*With the use of the maneuvers described below to reduce risk, and the usual short clinical course of CIN, the risk of clinically relevant renal dysfunction is very low in many situations
*In other cases, the risk may be sufficiently great, and the information that may be obtained by using no contrast media (e .g . noncontrast CT) or by other modalities may be sufficiently useful, that IV iodinated contrast may be avoided 
*In some clinical situations, the use of iodinated contrast media may be necessary regardless of CIN risk
*The use of the minimum dose of radiographic iodinated contrast media that provides sufficient diagnostic information may reduce risk.

!!Choice of Iodinated Contrast Media

*LOCM are, generally, less nephrotoxic than HOCM in patients with underlying renal insufficiency
**LOCM were not shown to confer a significant benefit in patients with normal renal function where the risk is low

*Some studies have suggested that iodixanol was associated with a lower risk of CIN than the LOCM,
**Subsequent reports have failed to establish a clear advantage of iodixanol over the other low-osmolality contrast media with regard to CIN, whether administration is IV or intra- arterial

!!Hydration

*Not all clinical studies have shown dehydration to be a major risk factor for CIN
*However, in the dehydrated state, 
**renal blood flow and glomerular filtration rate are decreased, 
**the magnitude of the effects of contrast media on these parameters is accentuated, and 
**there is the theoretical concern of prolonged tubular exposure to contrast media because of low tubular flow rates. 

*The incidence of CIN was decreased by hydration with 0 .45% saline or 0 .9% saline administered at a rate of 100 ml/hr beginning 12 hours before and continuing 12 hours after angiography
**In another study, IV 0 .9% saline hydration was shown to reduce CIN risk more than 0 .45% saline hydration
**Hydration with sodium bicarbonate [21] was shown to be more effective than using 0 .9% saline in one study, but these results have been challenged and cannot be considered definitive at this time.

!!Diuretics: Mannitol and Furosemide

*no beneficial effects from the osmotic diuretic mannitol when it was added to saline hydration in patients with or without diabetes
*exacerbation of contrast media-induced renal dysfunction when the loop diuretic furosemide was used in addition to saline hydration 
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	margin-right: 32px;
	width: 16px;
}

.tagAnnotation {
	margin-top: 8px;
	padding-bottom: 8px;
}
.annotationsBox {
	margin-top: 8px;
}

.editorFooter {
	position: relative;
	padding: 0;
	margin-top: 16px;
	margin-left: 64px;
}

.tiddler .editorFooter .editor {
	padding-left: 0px;
}

.heading .editor input {
	width: 100%;
	font-size: 1.5em;
}

.spaceSiteIcon .externalImage .image a:hover,
.modifierIcon .externalImage .image a:hover {
	background: none;
}

div.toolbar {
	visibility:hidden;
	right:-16px;
}

.selected div.toolbar {
	visibility: visible;
}

.followButton a:hover {
	background: [[ColorPalette::PrimaryMid]];
	text-decoration: underline;
}

a.image:hover {
	background: transparent;
}

@media all and (max-device-width: 480px) {
	div.toolbar {
		visibility:visible;
	}
}
@media only screen and (device-width: 768px) {
	div.toolbar {
		visibility:visible;
	}
}
@media all and (max-width: 960px) {
	.tiddler .titleBar {
		margin-left: 36px;
		margin-right: 80px;
	}

	.tiddler .heading {
		margin-bottom: 48px;
	}

	.tiddler .heading .title {
		font-size: 32px;
		line-height: 32px;
	}

	.tiddler .modifierIcon img,
	.tiddler .modifierIcon svg,
	.tiddler .spaceSiteIcon .originButton img,
	.originButton svg {
		width: 32px;
		height: 32px;
		margin-left: 0px;
		margin-right: 0px;
	}

	.tiddler .followPlaceHolder {
		right: 48px;
	}

	.tiddler .followButton {
		width: 24px;
	}

	.tiddler .viewer {
		margin: 0px 0px 0px 36px;
		padding-top: 0;
	}

	br {
		line-height: 0.5em;
	}
}
/*}}}*/
ColorPalette
StyleSheet
SiteSubtitle
GettingStarted
SiteTitle
MainMenu
SiteIcon
DefaultTiddlers
ViewTemplate
PageTemplate
SideBarOptions
EditTemplate
SiteInfo
SideBarTabs
ToolbarCommands
!usage
{{{[img[F1CarotidDoppler]]}}}
[img[F1CarotidDoppler]]
!notes
Graph demonstrates the relationship between mean PSV and percentage of stenosis as measured arteriographically. PSV increases with increasing severity of stenosis. Note marked overlap in adjacent categories of stenosis. Error bars = 1 SD about the mean. (Reprinted, with permission, from reference 18.) 
!type
image/gif
!file

!url
http://radiology.rsna.org/content/229/2/340/F1.small.gif
!data
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
Classification of ~Budd-Chiari syndrome
*Types 1 and 2 are the most common and involve obstruction at the level of the hepatic vein or vena cava
*Type 3, also called hepatic veno-occlusive disease, is rare and involves diffuse narrowing at the venule level

*The obstruction is usually secondary to bland thrombus related to a hypercoagulable state
**however, the list of causes of hepatic vein occlusion is long and is traditionally divided into 
***primary (eg, congenital webs) and 
***secondary (eg, benign or malignant thrombosis) causes.

*hepatic vein thrombosis is much less common than portal vein thrombosis. 

*Malignant hepatic vein thrombosis (ie, tumor thrombus) 
**is usually the result of direct invasion from an adjacent parenchymal hepatocellular carcinoma
**however, any other malignant vena cava thrombosis, such as renal cell carcinoma, adrenal cortical carcinoma, or primary inferior vena cava (IVC) leiomyosarcoma, may also cause ~Budd-Chiari syndrome

*vein enlargement is not a reliable discriminating feature (tumor thrombus and acute bland thrombus)
The title and subtitle of your space are visible to visitors and are also displayed in your browser's tabs. Click on the SiteTitle and SiteSubtitle tiddler links below to make changes.
* [[SiteTitle]]
* [[SiteSubtitle]]
*Reactions that are not acute have long been a source of concern with both iodinated and gadolinium-based contrast media 
**Currently, delayed reacions to gadolinium media in the form of nephrogenic systemic fibrosis (NSF) are a major concern
**Many different symptoms and signs have been reported as delayed reactions associated with iodinated contrast media
***relatively common ones are nausea, vomiting, drowsiness, headache, and pruritus without urticaria
****self-limited and usually do not require therapy 
**Delayed cardiopulmonary arrest has also been reported, 
***but this and other severe systemic reactions are probably related to etiologies other than the contrast media .

*Delayed cutaneous reactions
**other than contrast-induced nephropathy, are of most frequent concern are the cutaneous ones
**These are important for several reasons: 
***they occur more often than is generally recognized;
****0 .5% to 9% 
***they may recur (high rate of recorrency: 25%?); 
***they may have serious sequellae; and, perhaps most importantly, 
***they are often ascribed to causes other than contrast media .
**Some are moderate to severe in distribution and associated symptoms . 
**Delayed cutaneous reactions are more common in patients treated with interleukin-2 (IL-2) therapy 
**onset: from 3 hours to 7 days following the administration of a contrast agent 
**Presentation
***with an exanthem that varies widely in size and distribution
****often macular but may be maculopapular or pustular or may resemble angioneurotic edema, 
****usually associated with pruritus
**generally self limited and require only minimal symptomatic therapy
***They may, however, progress to severe symptomatology with wide distribution
***Cases have been reported that resemble Stevens-Johnson syndrome, toxic epidermal necrolysis, or cutaneous vasculitis, and one fatality has even been described
**Tretment
***When the rash is limited, symptomatic therapy such as corticosteroid creams can be used; 
***if it is progressive or widespread, or if there are significant associated symptoms, consultation with allergy or dermatology services is an appropriate early step
**Delayed cutaneous reactions are not, however, associated with other acute adverse events such as bronchospasm or laryngeal edema
**The etiology, as with most significant contrast-related complications, is not clear
***thought to be T-cell mediated
[[Radiologia]]
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!usage
{{{[img[AttachFileSample2]]}}}
[img[AttachFileSample2]]
!notes
example of external attachment (no embedded data)
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!!“Anaphylactoid” or “non-allergic anaphylactic”
**appear identical to an anaphylatic reaction to a drug or other allergen, but 
**an antigen-antibody response has not been identified in most reacting patients
**Treatment, however, is identical to that for an allergic anaphylactic reaction

The precise pathogenesis of most adverse events occurring after the administration of contrast media is unclear
*There are multiple potential mechanisms
**Some reactions may involve activation, deactivation, or inhibition of a variety of vasoactive substances or mediators
**Histamine release must have occurred when patients develop urticaria, but the precise cause and pathway of histamine release are not known
*In general, accurate prediction of a contrast reaction is not yet possible, although it is clear that certain patients are at increased risk of a reaction
*In some cases, the cause of an adverse event can be identified. 
**The etiology of cardiovascular effects, for example, is complex but to some extent definable. 
***cardiovascular effects are more frequent and more significant in patients with underlying cardiac disease
***Some effects, such as hypotension and tachycardia, have been thought by some to be related to hypertonicity .
***Others, such as the negative inotropy and chronotropy that occur with direct coronary injection, are related to both increased osmolality and ionic concentration
***Pulseless electrical activity, with associated cardiac arrest, has been shown to result from a sudden drop in serum-ionized calcium, which in turn may be caused by the specific contrast formulation or an additive
**The incidence and severity of such events seem to decrease with the use of low- osmolality and isotonic contrast media .

*patients with left heart failure 
**are less able to compensate for the osmotic load and the minor negative chronotropic effects of contrast media, because of the high osmolality of some contrast media and because of the volume load . 
***there is an increased risk of developing acute pulmonary edema
*Patients with an acute increase in pulmonary vascular resistance, and thus an acute increase in right heart pressure (e .g ., patients with massive pulmonary embolism)
**have an increased risk of developing right heart failure that may be irreversible
*Vasovagal reactions are relatively common and characterized by hypotension with bradycardia
**Pathogenesis is unknown, but is thought to be the result of increased vagal tone arising from the central nervous system . 
**The effects of increased vagal tone include 
***depressed sinoatrial and atrioventricular nodal activity, 
***inhibition of atrioventricular conduction, and 
***peripheral vasodilatation
**Most vagal reactions are mild and self-limited, but should be treated and observed closely until they resolve fully
***they may progress to cardiovascular collapse or be associated with angina or seizure secondary to clinically significant hypotension

!!!Obtaining a focused patient medical history prior to the administration of contrast media is critically important 
*Prior reaction to contrast injection is the best predictor of a recurrent adverse event 
**It is not an absolute indicator, however, since the incidence of recurrent reactions may range from 8% to perhaps as high as 30% 
**Pre-existing medical conditions can also foreshadow adverse events
***Urticarial reactions are more frequent in patients with a strong history of active allergies
***Bronchospasm is a common reaction among patients with active asthma
***Hemodynamic changes are more common among patients with significant cardio-vascular disease, such as aortic stenosis or severe congestive heart failure .

!!!Special Circumstances
*precautions are necessary to avoid adverse events in patients with known or suspected pheochromocytoma, thyrotoxicosis, dysproteinemias, myasthenia gravis, or sickle cell disease .
**There are scant data, however, to support the need for specific precautions in these patients when low-osmolality contrast media is used
/%

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To edit these options: 

* click [[here|ServerSettings]] to open the [[ServerSettings]] tiddler
* click on the edit button (the pencil icon)
* add the options you wish to set 
* click on the save button (the tick icon).

An example [[ServerSettings]] tiddler:
{{{
index: HelloThere
editor: /edit#{tiddler}
}}}

The additional text after /edit allows a tiddler to be opened in edit mode e.g:
{{{http://hello.tiddlyspace.com/edit#MyTiddler}}}

!!See Also

* [[ServerSettings shadow tiddler|http://docs.tiddlyspace.com/ServerSettings%20shadow%20tiddler]]
* [[Choosing a non-TiddlyWiki Default Application for your Space|http://docs.tiddlyspace.com/Choosing%20a%20non-TiddlyWiki%20Default%20Application%20for%20your%20Space]]

!Finished customising?
You can [[Start writing]] some [[tiddlers|http://docs.tiddlyspace.com/Tiddler]].
If you're not done tweaking yet though, you can always [[Customise this space|SpaceSettings]] a bit more.

You can also [[access and read other tiddlers in various ways|http://docs.tiddlyspace.com/Viewing%20Tiddlers]].

!Administration
If you'd like to change your password or create another space, visit "Your Account" from the [[Universal Backstage|http://docs.tiddlyspace.com/UniversalBackstage]] (the blue dot in the upper right of the page). If you'd like to add a member or [[include a space|http://docs.tiddlyspace.com/How%20do%20I%20include%2Fexclude%20spaces%3F]] visit "This Space" from the [[Universal Backstage|http://docs.tiddlyspace.com/UniversalBackstage]].

You can have as many spaces as you like and each space can have as many members as you or your group need.

!Stuck?
If you're stuck, and would like some help, please visit the [[help|http://help.tiddlyspace.com]] space, which can point you in the right direction.
/***
|''Name''|TiddlySpacePublishingCommands|
|''Version''|0.8.5|
|''Status''|@@beta@@|
|''Description''|toolbar commands for drafting and publishing|
|''Author''|Jon Robson|
|''Source''|http://github.com/TiddlySpace/tiddlyspace/raw/master/src/plugins/TiddlySpacePublishingCommands.js|
|''CoreVersion''|2.6.1|
|''Requires''|TiddlySpaceConfig TiddlySpaceFilters|
!Usage
Provides changeToPrivate, changeToPublic and saveDraft commands
Provides TiddlySpacePublisher macro.
{{{<<TiddlySpacePublisher type:private>>}}} make lots of private tiddlers public.
{{{<<TiddlySpacePublisher type:public>>}}} make lots of public tiddlers public.
!TODO
* add public argument?
!Code
***/
//{{{
(function($) {

var tiddlyspace = config.extensions.tiddlyspace;
var originMacro = config.macros.tiddlerOrigin;

tiddlyspace.getTiddlerStatusType = function(tiddler) {
	var isShadow = store.isShadowTiddler(tiddler.title);
	var exists = store.tiddlerExists(tiddler.title);
	if(isShadow && !exists) {
		return "shadow";
	} else if(!exists) {
		return "missing";
	} else {
		var types = ["private", "public"];
		var type = "external";
		for(var i = 0; i < types.length; i++) {
			var t = types[i];
			type = config.filterHelpers.is[t](tiddler) ? t : type;
		}
		if(config.filterHelpers.is.unsynced(tiddler)) {
			type = type == "private" ? "unsyncedPrivate" : "unsyncedPublic";
		}
		return type;
	}
};

var cmd = config.commands.publishTiddler = {
	text: "make public",
	tooltip: "Change this private tiddler into a public tiddler",
	errorMsg: "Error publishing %0: %1",

	isEnabled: function(tiddler) {
		return !readOnly && config.filterHelpers.is["private"](tiddler);
	},
	handler: function(ev, src, title) {
		var tiddler = store.getTiddler(title);
		if(tiddler) {
			var newBag = cmd.toggleBag(tiddler.fields["server.bag"]);
			this.moveTiddler(tiddler, {
				title: tiddler.fields["publish.name"] || tiddler.title,
				fields: { "server.bag": newBag }
			});
		}
	},
	toggleBag: function(bag, to) {
		var newBag;
		if(typeof bag != typeof "") {
			var tiddler = bag;
			bag = tiddler.fields["server.bag"];
		}
		if(bag.indexOf("_private") > -1) { // should make use of endsWith
			to = to ? to : "public";
			newBag = bag.replace("_private", "_" + to);
		} else {
			to = to ? to : "private";
			newBag = bag.replace("_public", "_" + to);
		}
		return newBag;
	},
	copyTiddler: function(title, newTitle, newBag, callback) {
		var original = store.getTiddler(title);
		newTitle = newTitle ? newTitle : title;
		var adaptor = original.getAdaptor();
		var publish = function(original, callback) {
			var tiddler = $.extend(new Tiddler(newTitle), original);
			tiddler.fields = $.extend({}, original.fields, {
				"server.bag": newBag,
				"server.workspace": "bags/%0".format(newBag),
				"server.page.revision": "false"
			});
			delete tiddler.fields["server.title"];
			tiddler.title = newTitle;
			adaptor.putTiddler(tiddler, null, null, callback);
		};
		publish(original, callback);
	},
	moveTiddler: function(tiddler, newTiddler, callback) {
			var info = {
			copyContext: {},
			deleteContext: {}
		};
		var _dirty = store.isDirty();
		var adaptor = tiddler.getAdaptor();
		var newTitle = newTiddler.title;
		var oldTitle = tiddler.title;
		delete tiddler.fields["server.workspace"];
		var oldBag = tiddler.fields["server.bag"];
		var newBag = newTiddler.fields["server.bag"];
		var newWorkspace = "bags/%0".format(newBag);
		cmd.copyTiddler(oldTitle, newTitle, newBag, function(ctx) {
				info.copyContext = ctx;
				var context = {
					tiddler: tiddler,
					workspace: newWorkspace
				};
				store.addTiddler(ctx.tiddler);
				tiddler.title = oldTitle; // for cases where a rename occurs
				if(ctx.status) { // only do if a success
					if(oldBag != newBag) {
						adaptor.deleteTiddler(tiddler, context, {}, function(ctx) {
							info.deleteContext = ctx;
							var el;
							if(tiddler) {
								tiddler.fields["server.workspace"] = newWorkspace;
								tiddler.fields["server.bag"] = newBag;
							}
							el = el ? el : story.refreshTiddler(oldTitle, null, true);
							if(oldTitle != newTitle) {
								store.deleteTiddler(oldTitle);
								store.notify(oldTitle, true);
							}
							if(el) {
								story.displayTiddler(el, newTitle);
							}
							if(oldTitle != newTitle) {
								story.closeTiddler(oldTitle);
							}
							if(callback) {
								callback(info);
							}
							store.setDirty(_dirty);
						});
					} else {
						if(callback) {
							callback(info);
						}
					}
					refreshDisplay();
				}
		});
	}
};

var changeToPrivate = config.commands.changeToPrivate = {
	text: "make private",
	tooltip: "turn this public tiddler into a private tiddler",
	isEnabled: function(tiddler) {
		return !readOnly && config.filterHelpers.is["public"](tiddler);
	},
	handler: function(event, src, title) {
		var tiddler = store.getTiddler(title);
		var newBag = cmd.toggleBag(tiddler, "private");
		var newTiddler = { title: title, fields: { "server.bag": newBag }};
		cmd.moveTiddler(tiddler, newTiddler);
	}
};
config.commands.changeToPublic = cmd;

/* Save as draft command */
var saveDraftCmd = config.commands.saveDraft = {
	text: "save draft",
	tooltip: "Save as a private draft",
	isEnabled: function(tiddler) {
		return changeToPrivate.isEnabled(tiddler);
	},
	getDraftTitle: function(title) {
		var draftTitle;
		var draftNum = "";
		while(!draftTitle) {
			var suggestedTitle = "%0 [draft%1]".format(title, draftNum);
			if(store.getTiddler(suggestedTitle)) {
				draftNum = !draftNum ? 2 : draftNum + 1;
			} else {
				draftTitle = suggestedTitle;
			}
		}
		return draftTitle;
	},
	createDraftTiddler: function(title, gatheredFields) {
		var tiddler = store.getTiddler(title);
		var draftTitle = saveDraftCmd.getDraftTitle(title);
		var draftTiddler = new Tiddler(draftTitle);
		if(tiddler) {
			$.extend(true, draftTiddler, tiddler);
		} else {
			$.extend(draftTiddler.fields, config.defaultCustomFields);
		}
		for(var fieldName in gatheredFields) {
			if(TiddlyWiki.isStandardField(fieldName)) {
				draftTiddler[fieldName] = gatheredFields[fieldName];
			} else {
				draftTiddler.fields[fieldName] = gatheredFields[fieldName];
			}
		}
		var privateBag = tiddlyspace.getCurrentBag("private");
		var privateWorkspace = tiddlyspace.getCurrentWorkspace("private");
		draftTiddler.title = draftTitle;
		draftTiddler.fields["publish.name"] = title;
		draftTiddler.fields["server.workspace"] = privateWorkspace;
		draftTiddler.fields["server.bag"] = privateBag;
		draftTiddler.fields["server.title"] = draftTitle;
		draftTiddler.fields["server.page.revision"] = "false";
		delete draftTiddler.fields["server.etag"];
		return draftTiddler;
	},
	handler: function(ev, src, title) {
		var tiddler = store.getTiddler(title); // original tiddler
		var tidEl = story.getTiddler(title);
		var uiFields = {};
		story.gatherSaveFields(tidEl, uiFields);
		var tid = saveDraftCmd.createDraftTiddler(title, uiFields);
		tid = store.saveTiddler(tid.title, tid.title, tid.text, tid.modifier,
			new Date(), tid.tags, tid.fields);
		autoSaveChanges(null, [tid]);
		story.closeTiddler(title);
		story.displayTiddler(src, title);
		story.displayTiddler(src, tid.title);
	}
};

var macro = config.macros.TiddlySpacePublisher = {
	locale: {
		title: "Batch Publisher",
		changeStatusLabel: "Make %0",
		noTiddlersText: "No tiddlers to publish",
		changeStatusPrompt: "Make all the selected tiddlers %0.",
		description: "Change tiddlers from %0 to %1 in this space"
	},

	listViewTemplate: {
		columns: [
			{ name: "Selected", field: "Selected", rowName: "title", type: "Selector" },
			{ name: "Tiddler", field: "tiddler", title: "Tiddler", type: "Tiddler" },
			{ name: "Status", field: "status", title: "Status", type: "WikiText" }
		],
		rowClasses: []
	},

	changeStatus: function(tiddlers, status, callback) { // this is what is called when you click the publish button
		var publicBag;
		for(var i = 0; i < tiddlers.length; i++) {
			var tiddler = tiddlers[i];
			var newTiddler = {
				title: tiddler.title,
				fields: { "server.bag": cmd.toggleBag(tiddler, status) }
			};
			cmd.moveTiddler(tiddler, newTiddler, callback);
		}
	},
	getMode: function(paramString) {
		var params = paramString.parseParams("anon")[0];
		var status = params.type ?
			(["public", "private"].contains(params.type[0]) ? params.type[0] : "private") :
			"private";
		var newStatus = status == "public" ? "private" : "public";
		return [status, newStatus];
	},
	handler: function(place, macroName, params, wikifier, paramString, tiddler) {
		var wizard = new Wizard();
		var locale = macro.locale;
		var status = macro.getMode(paramString);
		wizard.createWizard(place, locale.title);
		wizard.addStep(macro.locale.description.format(status[0], status[1]),
			'<input type="hidden" name="markList" />');
		var markList = wizard.getElement("markList");
		var listWrapper = $("<div />").addClass("batchPublisher").
			attr("refresh", "macro").attr("macroName", macroName).
			attr("params", paramString)[0];
		markList.parentNode.insertBefore(listWrapper, markList);
		$.data(listWrapper, "wizard", wizard);
		macro.refresh(listWrapper);
	},
	getCheckedTiddlers: function(listWrapper, titlesOnly) {
		var tiddlers = [];
		$(".chkOptionInput[rowName]:checked", listWrapper).each(function(i, el) {
			var title = $(el).attr("rowName");
			if(titlesOnly) {
				tiddlers.push(title);
			} else {
				tiddlers.push(store.getTiddler(title));
			}
		});
		return tiddlers;
	},
	refresh: function(listWrapper) {
		var checked = macro.getCheckedTiddlers(listWrapper, true);
		var paramString = $(listWrapper).empty().attr("params");
		var wizard = $.data(listWrapper, "wizard");
		var locale = macro.locale;
		var params = paramString.parseParams("anon")[0];
		var publishCandidates = [];
		var status = macro.getMode(paramString);
		var pubType = status[0];
		var newPubType = status[1];
		var tiddlers = params.filter ? store.filterTiddlers(params.filter[0]) :
			store.filterTiddlers("[is[%0]]".format(pubType));
		var enabled = [];
		for(var i = 0; i < tiddlers.length; i++) {
			var tiddler = tiddlers[i];
			var title = tiddler.title;
			if(!tiddler.tags.contains("excludePublisher") && title !== "SystemSettings") {
				publishCandidates.push({ title: title, tiddler: tiddler, status: pubType});
			}
			if(checked.contains(title)) {
				enabled.push("[rowname=%0]".format(title));
			}
		}

		if(publishCandidates.length === 0) {
			createTiddlyElement(listWrapper, "em", null, null, locale.noTiddlersText);
		} else {
			var listView = ListView.create(listWrapper, publishCandidates, macro.listViewTemplate);
			wizard.setValue("listView", listView);
			var btnHandler = function(ev) {
				var tiddlers = macro.getCheckedTiddlers(listWrapper);
				var callback = function(status) {
					$(".batchPublisher").each(function(i, el) {
						macro.refresh(el);
					});
				};
				macro.changeStatus(tiddlers, newPubType, callback);
			};
			wizard.setButtons([{
				caption: locale.changeStatusLabel.format(newPubType),
				tooltip: locale.changeStatusPrompt.format(newPubType),
				onClick: btnHandler
			}]);
			$(enabled.join(",")).attr("checked", true); // retain what was checked before
		}
	}
};

})(jQuery);
//}}}
—Errors in positioning the Doppler gate and in accounting for the Doppler
angle are common in current clinical practices. Since interpretative criteria for carotid stenosis are heavily based on Doppler velocities, errors in Doppler position and angle correction will lead to serious errors in diagnosis. 
!!Recommendation.
—The Doppler waveform should be obtained with an angle of insonation less than or equal to 60°, as measurements obtained with an angle of insonation greater than 60° are likely to be inaccurate, even with appropriate angle adjustment, because of the physical properties of Doppler.
!!Conflicting opinions.
—Some believed that maintaining a constant angle of insonation of exactly 60° would provide greater consistency. Other panelists did not agree that a fixed angle of insonation for all carotid US examinations is required and instead expressed that it is necessary only to maintain an angle of less than or equal to 60°. It was thought that further investigation on this matter is warranted.
#Allergy: 
**With regard to specific risk factors, a history of a prior allergy-like reaction to contrast media is associated with an up to five fold increased likelihood of the patient experiencing a subsequent reaction
**Additionally, any allergic diathesis predisposes individuals to reactions. 
***This relationship is a difficult one to define, since many individuals have at least a minor allergy, such as seasonal rhinitis, and do not experience reactions. 
***True concern should be focused on patients with significant allergies, such as a prior major anaphylactic response to one or more allergens. 
**The predictive value of specific allergies, such as those to shellfish or dairy products, previously thought to be helpful, is now recognized to be unreliable
***A significant number of health care providers continue to inquire specifically into a patient’s history of “allergy” to seafood, especially shellfish
****There is no evidence to support the continuation of this practice
***Any patient who describes an “allergy” to a food or contrast media should be questioned further to clarify the type and severity of the “allergy” or reaction, as these patients could be atopic and at increased risk for reactions
**Most forms of atopy result in a 2 to 3 times likelihood of contrast reaction compared with non-atopic patients
***However, considering the rarity of severe life-threatening anaphylaxis, this level of incremental risk remains low and should be considered in the context of risk versus benefit.
#Asthma: 
**A history of asthma may indicate an increased likelihood of a contrast reaction
#Renal Insufficiency: 
**each patient should be questioned whether he or she has a history of renal dysfunction. 
**[[contrastinduced nephrotoxicity (CIN)|Contrast Nephrotoxicity]] and [[nephrogenic systemic fibrosis (NSF)]] 
#Cardiac Status: 
**Patients with significant cardiac disease may be at increased risk for contrast reactions. 
***These include symptomatic patients (e.g., patients with angina or congestive heart failure symptoms with minimal exertion) and also patients with severe aortic stenosis, primary pulmonary hypertension, or severe but well-compensated cardiomyopathy.
**Limite the volume and osmolality of the contrast media. 
#Anxiety: 
**A general category that deserves attention is emotional state. 
**There is anecdotal evidence that severe adverse effects to contrast media or to procedures can be mitigated at least in part by reducing anxiety. 
#Miscellaneous Risk Factors: 
##Paraproteinemias, particularly multiple myeloma, are known to predispose patients to irreversible renal failure after high-osmolality contrast media (HOCM) administration due to tubular protein precipitation and aggregation; 
***however, there is no data predicting risk with the use of low-osmolality or iso-osmolality agents. 
##Age, apart from the general health of the patient, is not a major consideration in patient preparation
***In infants and neonates, contrast volume is an important consideration because of the low blood volume of the patient and the hypertonicity (and potentially detrimental cardiac effects) of even nonionic monomeric contrast media. 
##Gender is not considered a risk factor for IV contrast injection. 
##Some retrospective case control studies suggest a statistically significant risk that the use of betaadrenergic blocking agents lowers the threshold for and increases the severity of contrast reactions, and reduces the responsiveness of treatment of anaphylactoid reactions with epinephrine
##Others have suggested that sickle cell trait or disease increases the risk to patients; however, in neither case is there evidence of any clinically significant risk, particularly after the injection of low-osmolality contrast media (LOCM)
##Concomitant use of certain intra-arterial injections, such as papaverine, is believed to lead to precipitation of contrast media during arteriography. 
##There have been reports of thrombus formation during angiography using nonionic as opposed to ionic agents. 
##Some patients with pheochromocytoma develop an increase in serum catecholamine levels after the IV injection of HOCM. 
***A subsequent study showed no elevation of catecholamine levels after the IV injection of nonionic contrast media [11]. 
***Direct injection of either type of contrast medium into the adrenal or renal artery is to be avoided, however, as this may cause a hypertensive crisis.
##Some patients with hyperthyroidism or other thyroid disease (especially when present in those who live in iodine-deficient areas) may develop iodineprovoked delayed hyperthyroidism. 
***This effect may ppear 4 to 6 weeks after the IV contrast administration in some of these patients. 
***This can occur after the administration of any iodinated contrast media. It is usually self-limited.
##Patients with carcinoma of the thyroid deserve special consideration before the IV or oral administration of iodinated contrast media (ionic or nonionic). 
***Uptake of I-131 in the thyroid becomes moderately decreased to about 50% at one week after iodinated contrast injection but seems to become normal within a few weeks. 
****Therefore, if systemic radioactive iodine therapy is part of planned treatment, a pretherapy diagnostic study of the patient using an iodinated radiographic contrast medium (intravascular or oral) may be contraindicated; 
##Intravenous injections may cause heat and discomfort but rarely cause pain unless there is extravasation. 
##Intra-arterial contrast injections into peripheral vessels in the arms, legs, or head can be quite painful, particularly with HOCM. 
***For such injections, isoosmolality contrast media (IOCM) are associated with the least amount of discomfort. 
!Spaces
<<groupBy server.bag>>

!Private
<<list filter [is[private]]>>

!Public
<<list filter [is[public]]>>

!Drafts
<<list filter [is[draft]]>>
!!Issue
—Published literature is replete with velocity thresholds for categorizing ICA stenosis (Table 1). Tremendous variation exists among these studies in the methods used to assess individual Doppler parameters and in the thresholds recommended for diagnosing ICA stenosis (7).
!!Recommendation
—The consensus panel developed recommendations for diagnosis and stratification of ICA stenosis (Table 3). 
These recommendations were derived from analysis of numerous studies and do not represent the results of any one laboratory or study. For a particular laboratory setting, internal validation is encouraged when possible. This may yield alternative diagnostic criteria that can be used successfully at that facility. However, each laboratory should have a single set of diagnostic criteria that is applied uniformly. The following points are included in Table 3 and should be considered in the diagnosis of ICA stenosis: 
#The ICA is considered normal when ICA PSV is less than 125 cm/sec and no plaque or  ntimal thickening is visible sonographically. Additional criteria include ICA/CCA PSV ratio < 2.0 and ICA EDV < 40 cm/sec.
#A <50% ICA stenosis is diagnosed when ICA PSV is less than 125 cm/sec and plaque or intimal thickening is visible sonographically. Additional criteria include ICA/CCA PSV ratio < 2.0 and ICA EDV < 40 cm/sec. 
#A 50%–69% ICA stenosis is diagnosed when ICA PSV is 125–230 cm/sec and plaque is visible sonographically. Additional criteria include ICA/CCA PSV ratio of 2.0–4.0 and ICA EDV of 40–100 cm/sec.
#A >70% ICA stenosis but less than near occlusion of the ICA is diagnosed when the ICA PSV is greater than 230 cm/sec and visible plaque and luminal narrowing are seen at gray-scale and color Doppler US. Additional criteria include ICA/CCA PSV ratio > 4 and ICA EDV > 100 cm/sec. The higher the Doppler parameter lies above the threshold of 230 cm/sec, the greater the likelihood of severe disease.
#In cases of near occlusion of the ICA, the velocity parameters may not apply, since velocities may be high, low, or undetectable. This diagnosis is established primarily by demonstrating a markedly narrowed lumen at color or power Doppler US (35).
#Total occlusion of the ICA should be suspected when there is no detectable patent lumen at gray-scale US and no flow with spectral, power, and color Doppler US. Magnetic resonance (MR) angiography, computed tomographic (CT) angiography, or conventional angiography may be used for confirmation in this setting (35).

[img[T3CarotidDoppler]]
/***
|''Name''|TiddlySpaceBackstage|
|''Version''|0.8.0|
|''Description''|Provides a TiddlySpace version of the backstage and a homeLink macro|
|''Status''|@@beta@@|
|''Contributors''|Jon Lister, Jon Robson, Colm Britton|
|''Source''|http://github.com/TiddlySpace/tiddlyspace/raw/master/src/plugins/TiddlySpaceBackstage.js|
|''Requires''|TiddlySpaceConfig ImageMacroPlugin TiddlySpaceViewTypes|
!StyleSheet
.tiddler .error.annotation .button{
	display: inline-block;
}

#backstageArea {
	z-index: 49;
	color: white;
	background-color: black;
	background: -webkit-gradient(linear,left bottom,left top,color-stop(0, #222),color-stop(0.5, #333),color-stop(1, #555));
	background: -moz-linear-gradient(center bottom,#222 0%, #333 50%, #555 100%);
	filter: progid:DXImageTransform.Microsoft.gradient(startColorstr=#ff555555, endColorstr=#ff222222);
	-ms-filter: "progid:DXImageTransform.Microsoft.gradient(startColorstr=#ff555555, endColorstr=#ff222222)";
	height: 25px;
	padding: 0;
}

#backstageButton {
	overflow: hidden;
}

#backstageButton #backstageShow,
#backstageButton #backstageHide {
	margin: 0px;
	padding: 0px;
}

#backstageButton #backstageShow:hover,
#backstageButton #backstageHide:hover {
	background: none;
	color: none;
}

#backstageButton img,
#backstageButton svg {
	width: 24px;
	height: 24px;
}

#messageArea {
	top: 50px;
}

#backstageToolbar {
	position: relative;
}

#backstageArea a {
	padding: 0px;
	margin-left: 0px;
	color: white;
	background: none;
}

#backstageArea a:hover {
	background-color: white;
}

#backstage ol,
#backstage ul {
	padding: auto;
}

#backstageButton a {
	margin: 0;
}

.backstagePanelBody ul {
	padding: 5px;
	margin: 5px;
}

#backstage #backstagePanel {
	margin-left: 5%;
	padding: 0em;
	margin-right: 5%;
}

#backstageToolbar a {
	position: relative;
}

#backstageArea a.backstageSelTab,
#backstageToolbar .backstageTask {
	line-height: 25px;
	color: #767676;
}

.backstageTask .externalImage,
.backstageTask .image {
	display: inline;
}

#backstageToolbar a span {
	z-index: 2;
}

a.backstageTask {
	display: inline;
        margin-left: 1em !important;
}

.backstagePanelBody .button {
	display: inline-block;
	margin-right: 10px;
}

.backstagePanelBody {
	margin: 0 0 0 0.6em;
	padding: 0.4em 0.5em 1px 0.5em;
}

#backstage table {
	margin: auto;
}

#backstage .wizard table {
	border: 0px;
	margin: 0;
}

#backstage div  li.listLink {
	border: 0px;
	width: 78%;
	font-size: 0.7em;
}

#backstage div li.listTitle {
	font-weight: bold;
	text-decoration: underline;
	font-size: 1em;
	background: #ccc;
	width: 100%;
}

#backstage fieldset {
	border: solid 1px [[ColorPalette::Background]];
}

#backstage .viewer table,#backstage table.twtable {
	border: 0px;
}

#backstageToolbar img {
	padding: 0;
}

#backstage .wizard,
#backstage .wizardFooter {
	background: none;
}

.viewer td, .viewer tr, .twtable td, .twtable tr {
	border: 1px solid #eee;
}

#backstage .inlineList ul li {
	background-color: [[ColorPalette::Background]];
	border: solid 1px [[ColorPalette::TertiaryMid]];
	display: block;
	float: left;
	list-style: none;
	margin-right: 1em;
	padding: 0.5em;
}

.backstageClear, .inlineList form {
	clear: both;
	display: block;
	margin-top: 3em;
}

.tiddlyspaceMenu {
	text-align: center;
}

span.chunkyButton {
	display: inline-block;
	padding: 0;
	margin: 0;
	border: solid 2px #000;
	background-color: #04b;
}

span.chunkyButton a.button, span.chunkyButton a:active.button {
	white-space: nowrap;
	font-weight: bold;
	font-size: 1.8em;
	color: #fff;
	text-align: center;
	padding: 0.5em 0.5em;
	margin: 0;
	border-style: none;
	display: block;
}

span.chunkyButton:hover {
	background-color: #014;
}

span.chunkyButton a.button:hover {
	border-style: none;
	background: none;
	color: #fff;
}

#backstage .unpluggedSpaceTab .wizard,
.unpluggedSpaceTab .wizard {
	background: white;
	border: 2px solid #CCC;
	padding: 5px;
}

.syncKey .keyItem {
	border: 1px solid black;
	display: inline-block;
	margin: 0.2em;
	padding: 0.1em 0.1em 0.1em 0.1em;
}

.keyHeading {
	font-size: 2em;
	font-weight: bold;
	margin: 0.4em 0em -0.2em;
}

.unpluggedSpaceTab .putToServer,
.unpluggedSpaceTab .notChanged {
	display: none;
}

.tiddlyspaceMenu ul {
	margin: 0;
	padding: 0;
}

.tiddlyspaceMenu ul li {
	list-style: none;
}

.unsyncedChanges .unsyncedList {
	display: block;
}

.unsyncedList {
	display: none;
}
!Code
***/
//{{{
(function ($) {
    var name = "StyleSheet" + tiddler.title;
    config.shadowTiddlers[name] = "/*{{{*/\n%0\n/*}}}*/".
        format(store.getTiddlerText(tiddler.title + "##StyleSheet")); // this accesses the StyleSheet section of the current tiddler (the plugin that contains it)
    store.addNotification(name, refreshStyles);

    if (!config.extensions.tiddlyweb.status.tiddlyspace_version) { // unplugged
        config.extensions.tiddlyweb.status.tiddlyspace_version = "<unknown>";
        config.extensions.tiddlyweb.status.server_host = {
            url:config.extensions.tiddlyweb.host }; // TiddlySpaceLinkPlugin expects this
    }
    var disabled_tasks_for_nonmembers = ["tiddlers", "plugins", "batch", "sync"];

    var tweb = config.extensions.tiddlyweb;
    var tiddlyspace = config.extensions.tiddlyspace;
    var currentSpace = tiddlyspace.currentSpace.name;
    var imageMacro = config.macros.image;

    if (config.options.chkBackstage === undefined) {
        config.options.chkBackstage = false;
    }

// Set up Backstage
    config.tasks = {};
    config.tasks.status = {
        text:"status",
        tooltip:"TiddlySpace Info",
        content:"<<tiddler Backstage##Menu>>"
    };
    config.tasks.tiddlers = {
        text:"tiddlers",
        tooltip:"tiddlers control panel",
        content:"<<tiddler Backstage##BackstageTiddlers>>"
    };
    config.tasks.plugins = {
        text:"plugins",
        tooltip:"Manage installed plugins",
        content:"<<tiddler Backstage##Plugins>>"
    };
    config.tasks.batch = {
        text:"batch",
        tooltip:"Batch manage public/private tiddlers",
        content:"<<tiddler Backstage##BatchOps>>"
    };
    config.tasks.tweaks = {
        text:"tweaks",
        tooltip:"Tweak TiddlyWiki behaviors",
        content:"<<tiddler Backstage##Tweaks>>"
    };
    config.tasks.exportTiddlers = {
        text:"import/export",
        tooltip:"Import/export tiddlers from/to a TiddlyWiki",
        content:"<<tiddler Backstage##ImportExport>>"
    };
    config.tasks.sync = {
        text:"sync",
        tooltip:"Check Sync status",
        content:"<<tiddler Backstage##SpaceUnplugged>>"
    };

    if (window.location.protocol === "file:") {
        config.unplugged = true;
    }

    config.backstageTasks = ["status", "tiddlers", "plugins",
        "batch", "tweaks", "exportTiddlers", "sync"];

    config.messages.backstage.prompt = "";
// initialize state
    var _show = backstage.show;
    backstage.show = function () {
        // selectively hide backstage tasks and tabs based on user status
        var tasks = $("#backstageToolbar .backstageTask").show();
        var bs = backstage.tiddlyspace;
        if (!config.unplugged) {
            tweb.getUserInfo(function (user) {
                if (user.anon) {
                    jQuery.each(disabled_tasks_for_nonmembers, function (i, task) {
                        var taskIndex = config.backstageTasks.indexOf(task);
                        if (taskIndex !== -1) {
                            config.backstageTasks.splice(taskIndex, 1);
                        }
                    });
                    config.messages.memberStatus = bs.locale.loggedout;
                } else {
                    config.messages.memberStatus = readOnly ?
                        bs.locale.nonmember : bs.locale.member;
                }
            });
        } else {
            config.messages.memberStatus = bs.locale.unplugged;
        }

        // display backstage
        return _show.apply(this, arguments);
    };
    if (readOnly) {
        jQuery.each(disabled_tasks_for_nonmembers, function (i, task) {
            var taskIndex = config.backstageTasks.indexOf(task);
            if (taskIndex !== -1) {
                config.backstageTasks.splice(taskIndex, 1);
            }
        });
    }

    var tasks = config.tasks;
    var commonUrl = "/bags/common/tiddlers/%0";

    backstage.tiddlyspace = {
        locale:{
            member:"You are a member of this space.",
            nonmember:"You are not a member of this space.",
            loggedout:"You are currently logged out of TiddlySpace.",
            unplugged:"You are unplugged."
        },
        showButton:function () {
            var showBtn = $("#backstageShow")[0];
            var altText = $(showBtn).text();
            $(showBtn).empty();
            imageMacro.renderImage(showBtn, "backstage.svg",
                { altImage:commonUrl.format("backstage.png"), alt:altText});
        },
        hideButton:function () {
            var hideBtn = $("#backstageHide")[0];
            var altText = $(hideBtn).text();
            $(hideBtn).empty();
            imageMacro.renderImage(hideBtn, "close.svg",
                { altImage:commonUrl.format("close.png"), alt:altText, width:24, height:24 });
        }
    };

    var _init = backstage.init;
    backstage.init = function () {
        _init.apply(this, arguments);
        var init = function (user) {
            var bs = backstage.tiddlyspace;
            bs.showButton();
            bs.hideButton();
        };
        tweb.getUserInfo(init);
    };

    var home = config.macros.homeLink = {
        locale:{
            linkText:"your home space"
        },
        handler:function (place) {
            var container = $("<span />").appendTo(place)[0];
            tweb.getUserInfo(function (user) {
                if (!user.anon && user.name !== currentSpace) {
                    createSpaceLink(container, user.name, null, home.locale.linkText);
                }
            });
        }
    };

    config.macros.exportSpace = {
        handler:function (place, macroName, params) {
            var filename = params[0] ||
                "/tiddlers.wiki?download=%0.html".format(currentSpace);
            $('<a class="button">download</a>').// XXX: i18n
                attr("href", filename).appendTo(place);
        }
    };

}(jQuery));
//}}}
/***
|''Name''|RevisionsCommandPlugin|
|''Description''|provides access to tiddler revisions|
|''Author''|FND|
|''Contributors''|Martin Budden|
|''Version''|0.3.3|
|''Status''|@@beta@@|
|''Source''|http://svn.tiddlywiki.org/Trunk/association/plugins/RevisionsCommandPlugin.js|
|''CodeRepository''|http://svn.tiddlywiki.org/Trunk/association/plugins/|
|''License''|[[BSD|http://www.opensource.org/licenses/bsd-license.php]]|
|''CoreVersion''|2.6.0|
|''Keywords''|serverSide|
!Usage
Extend [[ToolbarCommands]] with {{{revisions}}}.
!Revision History
!!v0.1 (2009-07-23)
* initial release (renamed from experimental ServerCommandsPlugin)
!!v0.2 (2010-03-04)
* suppressed wikification in diff view
!!v0.3 (2010-04-07)
* restored wikification in diff view
* added link to side-by-side diff view
!To Do
* strip server.* fields from revision tiddlers
* resolve naming conflicts
* i18n, l10n
* code sanitizing
* documentation
!Code
***/
//{{{
(function($) {

jQuery.twStylesheet(".diff { white-space: pre, font-family: monospace }",
	{ id: "diff" });

var cmd = config.commands.revisions = {
	type: "popup",
	hideShadow: true,
	text: "revisions",
	tooltip: "display tiddler revisions",
	revTooltip: "", // TODO: populate dynamically?
	loadLabel: "loading...",
	loadTooltip: "loading revision list",
	selectLabel: "select",
	selectTooltip: "select revision for comparison",
	selectedLabel: "selected",
	compareLabel: "compare",
	linkLabel: "side-by-side view",
	revSuffix: " [rev. #%0]",
	diffSuffix: " [diff: #%0 #%1]",
	dateFormat: "YYYY-0MM-0DD 0hh:0mm",
	listError: "revisions could not be retrieved",

	handlePopup: function(popup, title) {
		title = this.stripSuffix("rev", title);
		title = this.stripSuffix("diff", title);
		var tiddler = store.getTiddler(title);
		var type = _getField("server.type", tiddler);
		var adaptor = new config.adaptors[type]();
		var limit = null; // TODO: customizable
		var context = {
			host: _getField("server.host", tiddler),
			workspace: _getField("server.workspace", tiddler)
		};
		var loading = createTiddlyButton(popup, cmd.loadLabel, cmd.loadTooltip);
		var params = { popup: popup, loading: loading, origin: title };
		adaptor.getTiddlerRevisionList(title, limit, context, params, this.displayRevisions);
	},

	displayRevisions: function(context, userParams) {
		removeNode(userParams.loading);
		if(context.status) {
			var callback = function(ev) {
				var e = ev || window.event;
				var revision = resolveTarget(e).getAttribute("revision");
				context.adaptor.getTiddlerRevision(tiddler.title, revision, context,
					userParams, cmd.displayTiddlerRevision);
			};
			var table = createTiddlyElement(userParams.popup, "table");
			for(var i = 0; i < context.revisions.length; i++) {
				var tiddler = context.revisions[i];
				var row = createTiddlyElement(table, "tr");
				var timestamp = tiddler.modified.formatString(cmd.dateFormat);
				var revision = tiddler.fields["server.page.revision"];
				var cell = createTiddlyElement(row, "td");
				createTiddlyButton(cell, timestamp, cmd.revTooltip, callback, null,
					null, null, { revision: revision });
				cell = createTiddlyElement(row, "td", null, null, tiddler.modifier);
				cell = createTiddlyElement(row, "td");
				createTiddlyButton(cell, cmd.selectLabel, cmd.selectTooltip,
					cmd.revisionSelected, null, null, null,
					{ index:i, revision: revision, col: 2 });
				cmd.context = context; // XXX: unsafe (singleton)!?
			}
		} else {
			$("<li />").text(cmd.listError).appendTo(userParams.popup);
		}
	},

	revisionSelected: function(ev) {
		var e = ev || window.event;
		e.cancelBubble = true;
		if(e.stopPropagation) {
			e.stopPropagation();
		}
		var n = resolveTarget(e);
		var index = n.getAttribute("index");
		var col = n.getAttribute("col");
		while(!index || !col) {
			n = n.parentNode;
			index = n.getAttribute("index");
			col = n.getAttribute("col");
		}
		cmd.revision = n.getAttribute("revision");
		var table = n.parentNode.parentNode.parentNode;
		var rows = table.childNodes;
		for(var i = 0; i < rows.length; i++) {
			var c = rows[i].childNodes[col].firstChild;
			if(i == index) {
				if(c.textContent) {
					c.textContent = cmd.selectedLabel;
				} else {
					c.text = cmd.selectedLabel;
				}
			} else {
				if(c.textContent) {
					c.textContent = cmd.compareLabel;
				} else {
					c.text = cmd.compareLabel;
				}
				c.onclick = cmd.compareSelected;
			}
		}
	},

	compareSelected: function(ev) {
		var e = ev || window.event;
		var n = resolveTarget(e);
		var context = cmd.context;
		context.rev1 = n.getAttribute("revision");
		context.rev2 = cmd.revision;
		context.tiddler = context.revisions[n.getAttribute("index")];
		context.format = "unified";
		context.adaptor.getTiddlerDiff(context.tiddler.title, context,
			context.userParams, cmd.displayTiddlerDiffs);
	},

	displayTiddlerDiffs: function(context, userParams) {
		var tiddler = context.tiddler;
		tiddler.title += cmd.diffSuffix.format([context.rev1, context.rev2]);
		tiddler.text = "{{diff{\n" + context.diff + "\n}}}";
		tiddler.tags = ["diff"];
		tiddler.fields.doNotSave = "true"; // XXX: correct?
		if(!store.getTiddler(tiddler.title)) {
			store.addTiddler(tiddler);
		}
		var src = story.getTiddler(userParams.origin);
		var tiddlerEl = story.displayTiddler(src, tiddler);
		var uri = context.uri.replace("format=unified", "format=horizontal");
		var link = $('<a target="_blank" />').attr("href", uri).text(cmd.linkLabel);
		$(".viewer", tiddlerEl).prepend(link);
	},

	displayTiddlerRevision: function(context, userParams) {
		var tiddler = context.tiddler;
		tiddler.title += cmd.revSuffix.format([tiddler.fields["server.page.revision"]]);
		tiddler.fields.doNotSave = "true"; // XXX: correct?
		if(!store.getTiddler(tiddler.title)) {
			store.addTiddler(tiddler);
		}
		var src = story.getTiddler(userParams.origin);
		story.displayTiddler(src, tiddler);
	},

	stripSuffix: function(type, title) {
		var str = cmd[type + "Suffix"];
		var i = str.indexOf("%0");
		i = title.indexOf(str.substr(0, i));
		if(i != -1) {
			title = title.substr(0, i);
		}
		return title;
	}
};

var _getField = function(name, tiddler) {
	return tiddler.fields[name] || config.defaultCustomFields[name];
};

})(jQuery);
//}}}
/***
|''Description''|Sanitisation for dynamically pulling tiddlers into your space and displaying them|
!Notes
Works both inside and outside TiddlyWiki. Uses the HTML Sanitizer provided by the Google Caja project
(see http://code.google.com/p/google-caja/wiki/JsHtmlSanitizer for more on this), which is licensed under
an Apache License (see http://www.apache.org/licenses/LICENSE-2.0).
!Code
***/
//{{{
(function($) {

var cleanURL = function(url) {
	var regexp = /^(?:http|https|mailto|ftp|irc|news):\/\//;
	return (regexp.test(url)) ? url : null;
};

$.sanitize = function(html) {
	return html_sanitize(html, cleanURL);
};

/*
 * HTML Sanitizer, provided by Google Caja
 */

/* Copyright Google Inc.
 * Licensed under the Apache Licence Version 2.0
 * Autogenerated at Tue May 17 17:39:24 BST 2011
 * @provides html4
 */var html4={};html4.atype={NONE:0,URI:1,URI_FRAGMENT:11,SCRIPT:2,STYLE:3,ID:4,IDREF:5,IDREFS:6,GLOBAL_NAME:7,LOCAL_NAME:8,CLASSES:9,FRAME_TARGET:10},html4.ATTRIBS={"*::class":9,"*::dir":0,"*::id":4,"*::lang":0,"*::onclick":2,"*::ondblclick":2,"*::onkeydown":2,"*::onkeypress":2,"*::onkeyup":2,"*::onload":2,"*::onmousedown":2,"*::onmousemove":2,"*::onmouseout":2,"*::onmouseover":2,"*::onmouseup":2,"*::style":3,"*::title":0,"a::accesskey":0,"a::coords":0,"a::href":1,"a::hreflang":0,"a::name":7,"a::onblur":2,"a::onfocus":2,"a::rel":0,"a::rev":0,"a::shape":0,"a::tabindex":0,"a::target":10,"a::type":0,"area::accesskey":0,"area::alt":0,"area::coords":0,"area::href":1,"area::nohref":0,"area::onblur":2,"area::onfocus":2,"area::shape":0,"area::tabindex":0,"area::target":10,"bdo::dir":0,"blockquote::cite":1,"br::clear":0,"button::accesskey":0,"button::disabled":0,"button::name":8,"button::onblur":2,"button::onfocus":2,"button::tabindex":0,"button::type":0,"button::value":0,"canvas::height":0,"canvas::width":0,"caption::align":0,"col::align":0,"col::char":0,"col::charoff":0,"col::span":0,"col::valign":0,"col::width":0,"colgroup::align":0,"colgroup::char":0,"colgroup::charoff":0,"colgroup::span":0,"colgroup::valign":0,"colgroup::width":0,"del::cite":1,"del::datetime":0,"dir::compact":0,"div::align":0,"dl::compact":0,"font::color":0,"font::face":0,"font::size":0,"form::accept":0,"form::action":1,"form::autocomplete":0,"form::enctype":0,"form::method":0,"form::name":7,"form::onreset":2,"form::onsubmit":2,"form::target":10,"h1::align":0,"h2::align":0,"h3::align":0,"h4::align":0,"h5::align":0,"h6::align":0,"hr::align":0,"hr::noshade":0,"hr::size":0,"hr::width":0,"iframe::align":0,"iframe::frameborder":0,"iframe::height":0,"iframe::marginheight":0,"iframe::marginwidth":0,"iframe::width":0,"img::align":0,"img::alt":0,"img::border":0,"img::height":0,"img::hspace":0,"img::ismap":0,"img::name":7,"img::src":1,"img::usemap":11,"img::vspace":0,"img::width":0,"input::accept":0,"input::accesskey":0,"input::align":0,"input::alt":0,"input::autocomplete":0,"input::checked":0,"input::disabled":0,"input::ismap":0,"input::maxlength":0,"input::name":8,"input::onblur":2,"input::onchange":2,"input::onfocus":2,"input::onselect":2,"input::readonly":0,"input::size":0,"input::src":1,"input::tabindex":0,"input::type":0,"input::usemap":11,"input::value":0,"ins::cite":1,"ins::datetime":0,"label::accesskey":0,"label::for":5,"label::onblur":2,"label::onfocus":2,"legend::accesskey":0,"legend::align":0,"li::type":0,"li::value":0,"map::name":7,"menu::compact":0,"ol::compact":0,"ol::start":0,"ol::type":0,"optgroup::disabled":0,"optgroup::label":0,"option::disabled":0,"option::label":0,"option::selected":0,"option::value":0,"p::align":0,"pre::width":0,"q::cite":1,"select::disabled":0,"select::multiple":0,"select::name":8,"select::onblur":2,"select::onchange":2,"select::onfocus":2,"select::size":0,"select::tabindex":0,"table::align":0,"table::bgcolor":0,"table::border":0,"table::cellpadding":0,"table::cellspacing":0,"table::frame":0,"table::rules":0,"table::summary":0,"table::width":0,"tbody::align":0,"tbody::char":0,"tbody::charoff":0,"tbody::valign":0,"td::abbr":0,"td::align":0,"td::axis":0,"td::bgcolor":0,"td::char":0,"td::charoff":0,"td::colspan":0,"td::headers":6,"td::height":0,"td::nowrap":0,"td::rowspan":0,"td::scope":0,"td::valign":0,"td::width":0,"textarea::accesskey":0,"textarea::cols":0,"textarea::disabled":0,"textarea::name":8,"textarea::onblur":2,"textarea::onchange":2,"textarea::onfocus":2,"textarea::onselect":2,"textarea::readonly":0,"textarea::rows":0,"textarea::tabindex":0,"tfoot::align":0,"tfoot::char":0,"tfoot::charoff":0,"tfoot::valign":0,"th::abbr":0,"th::align":0,"th::axis":0,"th::bgcolor":0,"th::char":0,"th::charoff":0,"th::colspan":0,"th::headers":6,"th::height":0,"th::nowrap":0,"th::rowspan":0,"th::scope":0,"th::valign":0,"th::width":0,"thead::align":0,"thead::char":0,"thead::charoff":0,"thead::valign":0,"tr::align":0,"tr::bgcolor":0,"tr::char":0,"tr::charoff":0,"tr::valign":0,"ul::compact":0,"ul::type":0},html4.eflags={OPTIONAL_ENDTAG:1,EMPTY:2,CDATA:4,RCDATA:8,UNSAFE:16,FOLDABLE:32,SCRIPT:64,STYLE:128},html4.ELEMENTS={a:0,abbr:0,acronym:0,address:0,applet:16,area:2,b:0,base:18,basefont:18,bdo:0,big:0,blockquote:0,body:49,br:2,button:0,canvas:0,caption:0,center:0,cite:0,code:0,col:2,colgroup:1,dd:1,del:0,dfn:0,dir:0,div:0,dl:0,dt:1,em:0,fieldset:0,font:0,form:0,frame:18,frameset:16,h1:0,h2:0,h3:0,h4:0,h5:0,h6:0,head:49,hr:2,html:49,i:0,iframe:4,img:2,input:2,ins:0,isindex:18,kbd:0,label:0,legend:0,li:1,link:18,map:0,menu:0,meta:18,nobr:0,noframes:20,noscript:20,object:16,ol:0,optgroup:0,option:1,p:1,param:18,pre:0,q:0,s:0,samp:0,script:84,select:0,small:0,span:0,strike:0,strong:0,style:148,sub:0,sup:0,table:0,tbody:1,td:1,textarea:8,tfoot:1,th:1,thead:1,title:24,tr:1,tt:0,u:0,ul:0,"var":0},html4.ueffects={NOT_LOADED:0,SAME_DOCUMENT:1,NEW_DOCUMENT:2},html4.URIEFFECTS={"a::href":2,"area::href":2,"blockquote::cite":0,"body::background":1,"del::cite":0,"form::action":2,"img::src":1,"input::src":1,"ins::cite":0,"q::cite":0},html4.ltypes={UNSANDBOXED:2,SANDBOXED:1,DATA:0},html4.LOADERTYPES={"a::href":2,"area::href":2,"blockquote::cite":2,"body::background":1,"del::cite":2,"form::action":2,"img::src":1,"input::src":1,"ins::cite":2,"q::cite":2};var html=function(a){function x(b,c,d){var e=[];w(function(b,e){for(var f=0;f<e.length;f+=2){var g=e[f],h=e[f+1],i=null,j;if((j=b+"::"+g,a.ATTRIBS.hasOwnProperty(j))||(j="*::"+g,a.ATTRIBS.hasOwnProperty(j)))i=a.ATTRIBS[j];if(i!==null)switch(i){case a.atype.NONE:break;case a.atype.SCRIPT:case a.atype.STYLE:h=null;break;case a.atype.ID:case a.atype.IDREF:case a.atype.IDREFS:case a.atype.GLOBAL_NAME:case a.atype.LOCAL_NAME:case a.atype.CLASSES:h=d?d(h):h;break;case a.atype.URI:h=c&&c(h);break;case a.atype.URI_FRAGMENT:h&&"#"===h.charAt(0)?(h=d?d(h):h,h&&(h="#"+h)):h=null;break;default:h=null}else h=null;e[f+1]=h}return e})(b,e);return e.join("")}function w(b){var c,d;return v({startDoc:function(a){c=[],d=!1},startTag:function(e,f,g){if(!d){if(!a.ELEMENTS.hasOwnProperty(e))return;var h=a.ELEMENTS[e];if(h&a.eflags.FOLDABLE)return;if(h&a.eflags.UNSAFE){d=!(h&a.eflags.EMPTY);return}f=b(e,f);if(f){h&a.eflags.EMPTY||c.push(e),g.push("<",e);for(var i=0,j=f.length;i<j;i+=2){var k=f[i],l=f[i+1];l!==null&&l!==void 0&&g.push(" ",k,'="',r(l),'"')}g.push(">")}}},endTag:function(b,e){if(d)d=!1;else{if(!a.ELEMENTS.hasOwnProperty(b))return;var f=a.ELEMENTS[b];if(!(f&(a.eflags.UNSAFE|a.eflags.EMPTY|a.eflags.FOLDABLE))){var g;if(f&a.eflags.OPTIONAL_ENDTAG)for(g=c.length;--g>=0;){var h=c[g];if(h===b)break;if(!(a.ELEMENTS[h]&a.eflags.OPTIONAL_ENDTAG))return}else for(g=c.length;--g>=0;)if(c[g]===b)break;if(g<0)return;for(var i=c.length;--i>g;){var h=c[i];a.ELEMENTS[h]&a.eflags.OPTIONAL_ENDTAG||e.push("</",h,">")}c.length=g,e.push("</",b,">")}}},pcdata:function(a,b){d||b.push(a)},rcdata:function(a,b){d||b.push(a)},cdata:function(a,b){d||b.push(a)},endDoc:function(a){for(var b=c.length;--b>=0;)a.push("</",c[b],">");c.length=0}})}function v(c){return function(d,e){d=String(d);var f=null,g=!1,h=[],j=void 0,l=void 0,m=void 0;c.startDoc&&c.startDoc(e);while(d){var n=d.match(g?t:u);d=d.substring(n[0].length);if(g){if(n[1]){var o=b(n[1]),p;if(n[2]){var q=n[3];switch(q.charCodeAt(0)){case 34:case 39:q=q.substring(1,q.length-1)}p=k(i(q))}else p=o;h.push(o,p)}else if(n[4]){l!==void 0&&(m?c.startTag&&c.startTag(j,h,e):c.endTag&&c.endTag(j,e));if(m&&l&(a.eflags.CDATA|a.eflags.RCDATA)){f===null?f=b(d):f=f.substring(f.length-d.length);var r=f.indexOf("</"+j);r<0&&(r=d.length),l&a.eflags.CDATA?c.cdata&&c.cdata(d.substring(0,r),e):c.rcdata&&c.rcdata(s(d.substring(0,r)),e),d=d.substring(r)}j=l=m=void 0,h.length=0,g=!1}}else if(n[1])c.pcdata&&c.pcdata(n[0],e);else if(n[3])m=!n[2],g=!0,j=b(n[3]),l=a.ELEMENTS.hasOwnProperty(j)?a.ELEMENTS[j]:void 0;else if(n[4])c.pcdata&&c.pcdata(n[4],e);else if(n[5]&&c.pcdata)switch(n[5]){case"<":c.pcdata("&lt;",e);break;case">":c.pcdata("&gt;",e);break;default:c.pcdata("&amp;",e)}}c.endDoc&&c.endDoc(e)}}function s(a){return a.replace(m,"&amp;$1").replace(n,"&lt;").replace(o,"&gt;")}function r(a){return a.replace(l,"&amp;").replace(n,"&lt;").replace(o,"&gt;").replace(p,"&#34;").replace(q,"&#61;")}function k(a){return a.replace(j,g)}function i(a){return a.replace(h,"")}function g(a,b){return f(b)}function f(a){a=b(a);if(c.hasOwnProperty(a))return c[a];var f=a.match(d);if(f)return String.fromCharCode(parseInt(f[1],10));if(!!(f=a.match(e)))return String.fromCharCode(parseInt(f[1],16));return""}var b;"script"==="SCRIPT".toLowerCase()?b=function(a){return a.toLowerCase()}:b=function(a){return a.replace(/[A-Z]/g,function(a){return String.fromCharCode(a.charCodeAt(0)|32)})};var c={lt:"<",gt:">",amp:"&",nbsp:"240",quot:'"',apos:"'"},d=/^#(\d+)$/,e=/^#x([0-9A-Fa-f]+)$/,h=/\0/g,j=/&(#\d+|#x[0-9A-Fa-f]+|\w+);/g,l=/&/g,m=/&([^a-z#]|#(?:[^0-9x]|x(?:[^0-9a-f]|$)|$)|$)/gi,n=/</g,o=/>/g,p=/\"/g,q=/\=/g,t=new RegExp("^\\s*(?:(?:([a-z][a-z-]*)(\\s*=\\s*(\"[^\"]*\"|'[^']*'|(?=[a-z][a-z-]*\\s*=)|[^>\"'\\s]*))?)|(/?>)|[\\s\\S][^a-z\\s>]*)","i"),u=new RegExp("^(?:&(\\#[0-9]+|\\#[x][0-9a-f]+|\\w+);|<!--[\\s\\S]*?-->|<!\\w[^>]*>|<\\?[^>*]*>|<(/)?([a-z][a-z0-9]*)|([^<&>]+)|([<&>]))","i");return{escapeAttrib:r,makeHtmlSanitizer:w,makeSaxParser:v,normalizeRCData:s,sanitize:x,unescapeEntities:k}}(html4),html_sanitize=html.sanitize

// stop here if we're not in TiddlyWiki
// XXX: is this the correct way of checking for TiddlyWiki?
if (!window.TiddlyWiki || !window.store || !store instanceof TiddlyWiki) {
	return;
}

var tiddlyspace = config.extensions.tiddlyspace;

var _subWikify = Wikifier.prototype.subWikify;

var cleanedTitle = 'This section has been cleaned of any potentially harmful code';

var replaceFunctions = {
	html: function(w) {
		var sanitizedHTML, spanEl;
		this.lookaheadRegExp.lastIndex = w.matchStart;
		var lookaheadMatch = this.lookaheadRegExp.exec(w.source);
		if(lookaheadMatch && lookaheadMatch.index == w.matchStart) {
			sanitizedHTML = $.sanitize(lookaheadMatch[1]);
			spanEl = createTiddlyElement(w.output, 'span', null, 'sanitized');
			spanEl.innerHTML = sanitizedHTML;
			spanEl.setAttribute('title', cleanedTitle);
			w.nextMatch = this.lookaheadRegExp.lastIndex;
		}
	},
	customFormat: function(w) {
		switch(w.matchText) {
			case '@@':
				var e = createTiddlyElement(w.output, 'span');
				var styles = config.formatterHelpers.inlineCssHelper(w);
				if (styles.length === 0) {
					e.className = 'marked';
				}
				w.subWikifyTerm(e, /(@@)/mg);
				break;
			case '{{':
				var lookaheadRegExp = /\{\{[\s]*([\w]+[\s\w]*)[\s]*\{(\n?)/mg;
				lookaheadRegExp.lastIndex = w.matchStart;
				var lookaheadMatch = lookaheadRegExp.exec(w.source);
				if(lookaheadMatch) {
					w.nextMatch = lookaheadRegExp.lastIndex;
					e = createTiddlyElement(w.output,lookaheadMatch[2] == "\n" ? "div" : "span",null,lookaheadMatch[1]);
					w.subWikifyTerm(e,/(\}\}\})/mg);
				}
				break;
		}
	}
};

Wikifier.prototype.subWikify = function(output, terminator) {
	var tid = this.tiddler,
		spaceName = tiddlyspace.currentSpace.name,
		tidSpace, recipeName, stripped;
	try {
		recipeName = tid.fields['server.recipe'] ||
			tid.fields['server.workspace'];
		tidSpace = tiddlyspace.resolveSpaceName(recipeName);
		if (tidSpace !== spaceName) {
			// external tiddler, so replace dangerous formatters
			stripped = stripHTML(tid, this.formatter);
		}
	} catch(e) {
		// do nothing. There's no tiddler, so assume it's safe (?!?!?)
	}

	_subWikify.apply(this, arguments);

	if (stripped) {
		// change back to the original function
		unstripHTML(stripped, this.formatter);
	}
};

// replace potentially unsafe formatters with versions that strip bad HTML/CSS
var stripHTML = function(tid, formatter) {
	var popped = {}, _handler;
	for (var i = 0; i < formatter.formatters.length; i++) {
		var f = formatter.formatters[i];
		if (replaceFunctions[f.name]) {
			_handler = f.handler;
			popped[f.name] = _handler;
			f.handler = replaceFunctions[f.name];
		}
	};

	return popped;
};

// put the original formatters back where they belong
var unstripHTML = function(stripped, formatter) {
	for (var i = 0; i < formatter.formatters.length; i++) {
		var f = formatter.formatters[i];
		if (stripped[f.name]) {
			f.handler = stripped[f.name];
		}
	};
};

})(jQuery);
//}}}
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
<!--{{{-->
<link rel="shortcut icon" href="/recipes/egp_public/tiddlers/favicon.ico" />
<link href="/bags/egp_public/tiddlers.atom" rel="alternate"
	type="application/atom+xml" title="egp's public feed" />
<link rel="canonical" href="http://egp.tiddlyspace.com/" />
<!--}}}-->
Although investigators have confirmed that the average Doppler velocity rises in direct proportion to the degree of stenosis as determined with angiography (18,26), there are very wide ranges of Doppler values around those means, which makes it impossible to classify lesions into gradations as narrow as 10% (Figure) (18,34). Even in evaluations of the ability of Doppler US to help estimate the degree of stenosis by using more expanded strata (eg, <50%, 50%–69%, and >70% stenosis), the findings have been disappointing. US is most accurate when lesions are classified as being above or below a single level, such as 60% stenosis or 70% stenosis (18).

[img[F1CarotidDoppler]]
!!Issue
—How should reporting of ICA stenosis be stratified?
!!Recommendation
—The consensus panel recommends stratification of the degree of stenosis on the basis of gray-scale and Doppler US results into the following strata: normal (no stenosis), 50% stenosis, 50%–69% stenosis, 70% stenosis but less than near occlusion, near occlusion, and total occlusion. 
!!Discussion
—The threshold of 70% stenosis was chosen because it was believed to be the threshold currently used by most major vascular centers for surgical intervention. The panel agreed, however, that in some laboratories, there may be a compelling reason to choose a different stratification scheme. The diagnoses of near occlusion and total occlusion are usually not based primarily on the Doppler measurement of velocity but rather on gray-scale and color and/or power Doppler imaging.
Metformin is a biguanide oral anti-hyperglycemic agent used to treat patients with non-insulin-depen- dent diabetes mellitus . It is available as a generic drug as well as in proprietary formulations, alone
and in combination with other drugs (see Table A for some of the brand name formulations) . The drug was approved in the United States in December of 1994 for use as monotherapy or combination therapy in patients with non-insulin-dependent diabetes mel- litus whose hyperglycemia is not controlled by diet or sulfonylurea therapy alone .
Metformin is thought to act by decreasing hepatic glucose production and enhancing peripheral glu- cose uptake as a result of increased sensitivity of peripheral tissues to insulin . Only rarely does it cause hypo-glycemia .
The most significant adverse effect of metformin therapy is the potential for the development of metformin-associated lactic acidosis in the suscep- tible patient . This condition is estimated to occur
at a rate of 0 to 0 .084 cases per 1,000 patient years . Patient mortality in reported cases is about 50% . However, in almost all reported cases, lactic acido- sis occurred because one or more patient-associated contraindications for the drug were overlooked . In one extensive 13-year retrospective study of patients in Sweden, 16 cases were found and all patients had several comorbid factors, most often cardiovascular or renal disease . There are no documented cases
of metformin-associated lactic acidosis in properly selected patients .
Metformin is excreted unchanged by the kidneys, probably by both glomerular filtration and tubular excretion . The renal route eliminates approximately 90% of the absorbed drug within the first 24 hours. Metformin seems to cause increased lactic acid production by the intestines . Any factors that de- crease metformin excretion or increase blood lactate levels are important risk factors for lactic acidosis . Renal insufficiency, then, is a major consideration.
Also, factors that depress the ability to metabo- lize lactate, such as liver dysfunction or alcohol abuse, or increase lactate production by increasing anaerobic metabolism (e .g ., cardiac failure, cardiac or peripheral muscle ischemia, or severe infection) are contraindications to the use of metformin (see Table B) . Iodinated X-ray contrast media are not an inde-
pendent risk factor for patients taking metformin but are a concern only in the presence of underlying renal dysfunction . Although contrast media-induced renal failure is very rare in patients with normal renal func- tion, elderly patients with reduced muscle mass (and thus reduced ability to make creatinine) can have a “normal” serum creatinine level in the presence of a markedly depressed glomerular filtration rate.
Intravascular (IV) administration of iodinated contrast media to a patient taking metformin is a po- tential clinical concern . Of metformin associated lac- tic acidosis cases reported worldwide between 1968 and 1991, 7 of the 110 patients received iodinated contrast media before developing lactic acidosis . The metformin package inserts approved by the U .S . Food and Drug Administration states that metformin should be withheld temporarily for patients undergo- ing radiological studies using IV iodinated contrast media . If acute renal failure or a reduction in renal function were to be caused by the iodinated contrast media, an accumulation of metformin could occur, with resultant lactate accumulation . The major clini- cal concern, then, is confined to patients with known, borderline, or incipient renal dysfunction .
Limiting the amount of contrast medium adminis- tered and hydrating the patient lessen the risk of con- trast media-induced dysfunction; both of these mea- sures should be considered in patients with known or incipient renal dysfunction. The efficacy of other measures thought to limit contrast nephrotoxicity (e .g ., administration of N-acetylcysteine) in prevent- ing lactic acidosis related to metformin is not known (also see Chapter on Contrast Nephrotoxicity) 

!![[Management]]

!![[Metformin and Gadolinium]]

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
#[[Patient Selection and Preparation Strategies]]
#[[Incidence of Adverse Effects]]
#[[Adverse effects of Iodinated Contrast Media]]
#[[Contrast Nephrotoxicity]]
#[[Metformina]]
#[[Contrast Media in Children]]
/***
|''Name''|BinaryTiddlersPlugin|
|''Description''|renders base64-encoded binary tiddlers as images or links|
|''Author''|FND|
|''Version''|0.3.2|
|''Status''|@@beta@@|
|''Source''|http://svn.tiddlywiki.org/Trunk/association/plugins/BinaryTiddlersPlugin.js|
|''License''|[[BSD|http://www.opensource.org/licenses/bsd-license.php]]|
|''CoreVersion''|2.5|
!Code
***/
//{{{
(function($) {

"use strict";

var ctfield = "server.content-type";

var plugin = config.extensions.BinaryTiddlersPlugin = {
	isWikiText: function(tiddler) {
		var ctype = tiddler.fields[ctfield];
		if(ctype) {
			if (ctype === 'text/x-tiddlywiki') {
				return true;
			}
			return !this.isBinary(tiddler) && !this.isTextual(ctype);
		} else {
			return true;
		}
	},
	// NB: pseudo-binaries are considered non-binary here
	isBinary: function(tiddler) {
		var ctype = tiddler.fields[ctfield];
		return ctype ? !this.isTextual(ctype) : false;
	},
	isTextual: function(ctype) {
		return ctype.indexOf("text/") === 0
			|| this.endsWith(ctype, "+xml")
			|| ctype === 'application/json'
			|| ctype === 'application/javascript';
	},
	endsWith: function(str, suffix) {
		return str.length >= suffix.length &&
			str.substr(str.length - suffix.length) === suffix;
	},
	isLink: function(tiddler) {
		return this.isBinary(tiddler) && tiddler.text.indexOf("<html>") !== -1;
	}
};

// Disable edit for linked tiddlers (for now)
// This will be changed to a GET then PUT
config.commands.editTiddler.isEnabled = function(tiddler) {
    var existingTest = config.commands.editTiddler.isEnabled;
    if (existingTest) {
        return existingTest && !plugin.isLink(tiddler);
    } else {
        return !plugin.isLink(tiddler);
    }
};

// hijack text viewer to add special handling for binary tiddlers
var _view = config.macros.view.views.wikified;
config.macros.view.views.wikified = function(value, place, params, wikifier,
		paramString, tiddler) {
	var ctype = tiddler.fields["server.content-type"];
	if(params[0] === "text" && ctype && ctype !== 'text/x-tiddlywiki' &&
			!tiddler.tags.contains("systemConfig") && !plugin.isLink(tiddler)) {
		var el;
		if(plugin.isBinary(tiddler)) {
			var uri = "data:%0;base64,%1".format([ctype, tiddler.text]); // TODO: fallback for legacy browsers
			if(ctype.indexOf("image/") === 0) {
				el = $("<img />").attr("alt", tiddler.title).attr("src", uri);
			} else {
				el = $("<a />").attr("href", uri).text(tiddler.title);
			}
		} else {
			el = $("<pre />").text(tiddler.text);
		}
		el.appendTo(place);
	} else {
		_view.apply(this, arguments);
	}
};

// hijack edit macro to disable editing of binary tiddlers' body
var _editHandler = config.macros.edit.handler;
config.macros.edit.handler = function(place, macroName, params, wikifier,
		paramString, tiddler) {
	if(params[0] === "text" && plugin.isBinary(tiddler)) {
		return false;
	} else {
		_editHandler.apply(this, arguments);
	}
};

// hijack autoLinkWikiWords to ignore binary tiddlers
var _autoLink = Tiddler.prototype.autoLinkWikiWords;
Tiddler.prototype.autoLinkWikiWords = function() {
	return plugin.isWikiText(this) ? _autoLink.apply(this, arguments) : false;
};

}(jQuery));
//}}}
/***
|''Name''|ImageMacroPlugin|
|''Version''|0.9.4|
|''Description''|Allows the rendering of svg images in a TiddlyWiki|
|''Author''|Osmosoft|
|''License''|[[BSD|http://www.opensource.org/licenses/bsd-license.php]]|
|''Notes''|Currently only works in modern browsers (not IE)|
|''Requires''|BinaryTiddlersPlugin|
!Usage
{{{<<image SVG>>}}} will render the text of the tiddler with title SVG as an SVG image (but not in ie where it will fail silently)
!!Parameters
width/height: specify width/height parameters
link: make the image link to a given location
tiddlyLink: link to a tiddler

!Notes
Binary tiddlers in TiddlyWeb when passed through the wikifier will be shown as images.
eg. {{{<<view text wikified>>}}} on a binary tiddler will show the image.
{{{<<view fieldname image>>}}}
will render the value of the tiddler field 'fieldname' as an image. This field can contain a tid
{{{<<image SiteIcon>>}}}
will create an image tag where the tiddler has content type beginning image and not ending +xml
will attempt to create svg object in other scenarios
{{{<<image /photos/x.jpg>>}}}
will create an image tag with src /photos/x.jpg as long as there is not a tiddler called /photos/x.jpg in 
which case it will render that tiddler as an image. Note for the case of svg files it will attempt to render as an svg if possible via the image
tag. It doesn't embed the svg in the dom for security reasons as svg code can contain javascript.
!Code
***/
//{{{
(function($) {

var macro = config.macros.image = {
	shim: "/bags/common/tiddlers/shim",
	ieVersion: config.browser.isIE ? parseInt(config.browser.ieVersion[1], 10) : false,
	svgns: "http://www.w3.org/2000/svg",
	xlinkns: "http://www.w3.org/1999/xlink", 
	svgAvailable: document.implementation.hasFeature("http://www.w3.org/TR/SVG11/feature#BasicStructure", "1.1"),
	_fixPrefix: 1,
	_external_cache: {},
	_image_tag_cache: {},
	_image_dimensions: {},
	locale: {
		badImage: "This image cannot be displayed."
	},
	handler: function(place, macroName, params, wikifier, paramString, tiddler){
		var imageSource = params[0];
		// collect named arguments
		var args = macro.getArguments(paramString, params);
		this.renderImage(place, imageSource, args);
	},
	init: function() {
		var startupImages = store.getTaggedTiddlers("systemImage");
		var place = $("<div />").attr("id", "systemImageArea").appendTo("body").hide()[0];
		for(var i = 0; i < startupImages.length; i++) {
			var image = startupImages[i];
			macro.renderImage(place, image.title, { idPrefix: "" });
		}
		var data = new Image();
		data.onload = function() {
			// note ie 8 only supports data uris up to 32k so cannot be relied on
			macro.supportsDataUris = this.width != 1 || this.height != 1 ? false : true;
			macro.supportsDataUris = macro.ieVersion && macro.ieVersion < 9 ? false : macro.supportsDataUris;
		};
		data.onerror = data.onload;
		data.src = "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///ywAAAAAAQABAAACAUwAOw==";
	},
	refreshImage: function(src) {
		var elements = macro._image_tag_cache[src] ? macro._image_tag_cache[src] : [];
		if(macro._image_dimensions[src]) {
			macro._image_dimensions[src] = false;
		}
		for(var i = 0; i < elements.length; i++) {
			var el = $(elements[i]);
			var newSrc = "%0?nocache=%1".format(src, Math.random());
			el.attr("src", newSrc); // force reload
		}
	},
	isBinaryImageType: function(contentType) {
		return (contentType && contentType.indexOf("image") === 0 &&
			contentType.indexOf("+xml") != contentType.length - 4) ? true : false;
	},
	isImageTiddler: function(tiddler) {
		return macro.isSVGTiddler(tiddler) || macro.isBinaryImageTiddler(tiddler);
	},
	isSVGTiddler: function(tiddler) {
		var type = tiddler ? tiddler.fields['server.content-type'] : false;
		return type == "image/svg+xml";
	},
	isBinaryImageTiddler: function(tiddler) {
		return macro.isBinaryImageType(tiddler.fields['server.content-type']);
	},
	renderImage: function(place, imageSource, options) {
		var imageTiddler = store.getTiddler(imageSource);
		var container;
		var classes = ["image"];
		if(options.link) {
			classes = classes.concat(["imageLink", "externalLink"]);
			container = $("<a />").attr("href", options.link).appendTo(place)[0];
		} else if(options.tiddlyLink) {
			classes.push("imageLink");
			container = createTiddlyLink(place, options.tiddlyLink, false);
		} else {
			container = $("<span />").appendTo(place)[0];
		}
		$(container).addClass(classes.join(" "));

		options = options ? options : {};
		if(imageTiddler && macro.isBinaryImageTiddler(imageTiddler)) { // handle the case where we have an image url
			return macro._renderBinaryImageTiddler(container, imageTiddler, options);
		} else if(imageTiddler){ // handle the case where we have a tiddler
			return macro._renderSVGTiddler(container, imageTiddler, options);
		} else { // we have a string representing a url
			return macro._renderBinaryImageUrl(container, imageSource, options);
		}
	},
	_renderAlternateText: function(container, options) {
		var img;
		var src = options.src || "";
		if(options.width && options.height) {
			img = $("<img />").attr("src", src).addClass("svgImageText").attr("width", options.width).
				attr("height", options.height).appendTo(container);
		}
		var alt = options.alt;
		if(img && alt) {
			img.attr("alt", alt).attr("title", alt);
		} else if(alt) {
			$(container).addClass("svgImageText").text(alt);
		}
		macro._image_tag_cache[src] = img;
	},
	_renderSVGTiddler: function(place, tiddler, options) {
		if(!options) {
			options = {};
		}
		merge(options, { tiddler: tiddler, fix: true});

		if(macro.svgAvailable) {
			this._importSVG(place, options); // display the svg
		} else if(options.altImage) {
			var image = options.altImage;
			delete options.altImage;
			this._renderBinaryImageUrl(place, image, options);
		} else {
			this._renderAlternateText(place, options); // instead of showing the image show the alternate text.
		}
	},
	_renderBinaryImageTiddler: function(place, tiddler, options) {
		var resourceURI;
		var fields = tiddler.fields;
		if(fields["server.type"] == "tiddlyweb") { // construct an accurate url for the resource
			resourceURI = "%0/%1/tiddlers/%2".format(config.defaultCustomFields["server.host"],
				fields["server.workspace"], encodeURI(fields["server.title"]));
		} else { // guess the url for the resource
			resourceURI = tiddler.title;
		}
		var ctype = fields["server.content-type"] || tiddler.type;
		var text = tiddler.text;
		if(macro.supportsDataUris && ctype && text.indexOf("<html") == -1) {
			var uri = "data:%0;base64,%1".format(ctype, text);
			options.src = resourceURI;
			return macro._renderBinaryImageUrl(place, uri, options);
		} else if(options.src) {
			return macro._renderBinaryImageUrl(place, options.src, options);
		} else {
			return macro._renderBinaryImageUrl(place, resourceURI, options);
		}
	},
	_renderImageTag: function(container, src, width, height, options) {
		var img;
		img = $("<img />").appendTo(container);
		if(height) {
			img.attr("height", height);
		}
		if(width) {
			img.attr("width", width);
		}
		if(macro.ieVersion && macro.ieVersion < 7 && macro.shim && options.ie6png) {
			$(img).css({width: userW, height: userH,
					filter: "progid:DXImageTransform.Microsoft.AlphaImageLoader(src='%0', sizingMethod='scale')".format(src)
				}).attr("src", macro.shim);
		} else {
			img.attr("src", src);
		}
		if(!macro._image_tag_cache[options.srcUrl]) {
			macro._image_tag_cache[options.srcUrl] = [];
		}
		img = $(img).addClass(options.imageClass)[0];
		macro._image_tag_cache[options.srcUrl].push(img);
		return img;
	},
	_getDimensions: function(realDimensions, reqDimensions, preserve) {
		var w = realDimensions.width;
		var h = realDimensions.height;
		var reqh = reqDimensions.height;
		var reqw = reqDimensions.width;
		var finalw = w, finalh = h;
		var ratiow = reqw / w, ratioh = reqh / h;
		var scaledw = ratioh * w;
		var scaledh = ratiow * h;
		if(!reqw && reqh) {
			finalw = scaledw;
			finalh = reqh;
		} else if(reqw && !reqh) {
			finalw = reqw;
			finalh = scaledh;
		} else if(reqh && reqw) {
			var preserveWidth = w > h ? true : false;
			if(preserve) {
				if(preserveWidth && scaledh < reqh) {
					finalh = scaledh;
					finalw = reqw;
				} else {
					finalh = reqh;
					finalw = scaledw;
				}
			} else {
				finalw = reqw;
				finalh = reqh;
			}
		}
		return { width: parseInt(finalw, 10), height: parseInt(finalh, 10) };
	},
	_renderBinaryImageUrl: function(container, src, options) {
		var srcUrl = options.src ? options.src : src;
		srcUrl = srcUrl.indexOf("/") === -1 ? "/%0".format(srcUrl) : srcUrl; // for IE. 
		var image_dimensions = macro._image_dimensions[srcUrl];
		var image = new Image(); // due to weird scaling issues where you use just a width or just a height
		var createImageTag = function(dimensions, error) {
			if(error) {
				var altImage = options.altImage;
				if(altImage) {
					delete options.altImage;
					macro._renderBinaryImageUrl(container, altImage, options);
				} else {
					options.src = src;
					macro._renderAlternateText(container, options);
				}
			} else {
				var dim = macro._getDimensions(dimensions, { 
					width: options.width, height: options.height }, options.preserveAspectRatio);
				options.srcUrl = srcUrl;
				macro._renderImageTag(container, src, dim.width, dim.height, options);
			}
		};

		if(!image_dimensions) {
			image.onload = function() {
				var dimensions = { width: image.width, height: image.height};
				macro._image_dimensions[srcUrl] = dimensions;
				createImageTag(dimensions);
			};
			image.onerror = function() {
				createImageTag(null, true);
			};
			image.src = src;
		} else {
			createImageTag(image_dimensions);
		}
	},
	_generateIdPrefix: function(){
		return "twsvgfix_" + (this._fixPrefix++).toString() + "_";
	},
	_fixSVG: function(childNodes, idPrefix) {
		var urlPattern = /url\(\#([^\)]*)\)*/ig;
		var fixes = [
		{ attr: "id", pattern: /^(.*)$/ig },
		{ attr: "href", namespace: macro.xlinkns, pattern: /^#(.*)$/ig }
		];
		var url_fixes = ["filter", "fill", "mask", "stroke", "style"];
		for(var i = 0; i < url_fixes.length; i++) {
			fixes.push({ attr: url_fixes[i], pattern: urlPattern });
		}
		for(var t = 0; t < childNodes.length; t++) {
			var node = childNodes[t];
			for(var a = 0; a < fixes.length; a++) {
				var fix = fixes[a];
				var attr = fix.attr;
				var ns = fix.namespace || "";
				if(node.hasAttributeNS && node.hasAttributeNS(ns, attr)) {
					var v = node.getAttributeNS(ns, attr);
					fix.pattern.lastIndex = 0;
					var match = fix.pattern.exec(v);
					if(match) {
						// Make sure replacement string doesn't contain any single dollar signs
						var toReplace = match[1];
						if(toReplace.indexOf(idPrefix) !== 0 && toReplace.indexOf("twglobal_") !== 0) {
							var replacement = (idPrefix + toReplace).replace("$", "$$$$"); 
							v = v.replace(match[1], replacement);
						}
						node.setAttributeNS(ns, attr,v);
					}
				}
			}
			var children = node.childNodes;
			if(children.length > 0) {
				this._fixSVG(children, idPrefix);
			}
		}
	},
	_importSVG: function(place, options){
		options = options ? options : {};
		var svgDoc, tiddlerText = options.tiddler.text;
		if (window.DOMParser) {
			svgDoc = new DOMParser().parseFromString(tiddlerText, "application/xml").documentElement;
			var idPrefix = options.idPrefix || this._generateIdPrefix();
			this._fixSVG([svgDoc], idPrefix);
			var el = document.importNode(svgDoc, true);
			var svgHolder = document.createElementNS(macro.svgns,"svg");
			var width = options.width;
			var height = options.height;
			if(width || height) {
				if(width && height) { // set view box of containing svg element based on the svg viewbox and width and height.
					var viewBox = el.getAttribute("viewBox");
					var topLeft = "0 0";
					if(viewBox) {
						topLeft = viewBox.replace(/([0-9]*) +([0-9]*) +([0-9]*) +([0-9]*) */gi,"$1 $2");
					}
					svgHolder.setAttributeNS(macro.svgns, "viewBox", "0 0 %0 %1".format(width, height));
				} else {
					if(!width) {
						width = el.getAttribute("width");
					}
					if(!height) {
						height = el.getAttribute("height");
					}
				}
				svgHolder.setAttribute("width", width);
				svgHolder.setAttribute("height", height);

				el.setAttribute("width", "100%");
				el.setAttribute("height", "100%");
				svgHolder.setAttribute("class", "svgImage svgIcon %0".format(options.imageClass || ""));
				svgHolder.appendChild(el);
				place.appendChild(svgHolder);
			}
			else {
				var existing = el.className ? el.className.baseVal : "";
				el.setAttribute("class","svgImage %0".format(existing));
				place.appendChild(el);
			}
			// if a tiddler attribute is set this is read as a link
			$("[tiddler], [tiddlyLink]", place).attr("refresh", "link").click(function(ev) {
				var tiddler = $(ev.target).attr("tiddlyLink");
				if(tiddler) {
					story.displayTiddler(ev.target, tiddler);
				}
			});
		}
	},
	getArguments: function(paramString, params) {
		var args = paramString.parseParams("name", null, true, false, true)[0];
		var options = {};
		for(var id in args) {
			if(true) {
				var p = args[id];
				if(id == "def") {
					options[id] = p;
				} else {
					options[id] = p[0];
				}
			}
		}
		var width = isNaN(params[1]) ? false : parseInt(params[1], 10);
		var height = isNaN(params[2]) ? false : parseInt(params[2], 10);

		options.width = macro.lookupArgument(options, "width", width);
		options.height = macro.lookupArgument(options, "height", height);
		options.preserveAspectRatio = args.preserveAspectRatio && 
			args.preserveAspectRatio[0] == "yes" ? true : false;
		options.tiddlyLink = macro.lookupArgument(options, "tiddlyLink", false);
		options.link = macro.lookupArgument(options, "link", false);
		return options;
	},
	lookupArgument: function(args, id, ifEmpty) {
		return args[id] ? args[id] : ifEmpty;
	}
};

// update views
var _oldwikifiedview = config.macros.view.views.wikified;
// update wikifier to check tiddler type before rendering
merge(config.macros.view.views, {
	wikified: function(value, place, params, wikifier, paramString, tiddler) {
		if(macro.isImageTiddler(tiddler) && params[0] == "text") {
			var newplace = $("<div />").addClass("wikifiedImage").appendTo(place)[0];
			macro.renderImage(newplace, tiddler.title, { alt: macro.locale.badImage });
		} else {
			_oldwikifiedview.apply(this, arguments);
		}
	},
	image: function(value, place, params, wikifier, paramString, tiddler) {
		// a field can point to another tiddler whereas text is the current tiddler.
		var title = params[0] == "text" ? tiddler.title : value;
		var args = macro.getArguments(paramString, params);
		macro.renderImage(place, title, args);
	}
});
config.shadowTiddlers.StyleSheetImageMacro = [".wikifiedImage svg, .wikifiedImage .image { width: 80%; }",
	".svgImageText { background-color:[[ColorPalette::Error]]; color:#ddd; display: inline-block; }",
	"span.svgImageText { display: inline-block; overflow: hidden; }"
].join("");
store.addNotification("StyleSheetImageMacro", refreshStyles);

})(jQuery);
//}}}
text/plain
.txt .text .js .vbs .asp .cgi .pl
----
text/html
.htm .html .hta .htx .mht
----
text/comma-separated-values
.csv
----
text/javascript
.js
----
text/css
.css
----
text/xml
.xml .xsl .xslt
----
image/gif
.gif
----
image/jpeg
.jpg .jpe .jpeg
----
image/png
.png
----
image/bmp
.bmp
----
image/tiff
.tif .tiff
----
audio/basic
.au .snd
----
audio/wav
.wav
----
audio/x-pn-realaudio
.ra .rm .ram
----
audio/x-midi
.mid .midi
----
audio/mp3
.mp3
----
audio/m3u
.m3u
----
video/x-ms-asf
.asf
----
video/avi
.avi
----
video/mpeg
.mpg .mpeg
----
video/quicktime
.qt .mov .qtvr
----
application/pdf
.pdf
----
application/rtf
.rtf
----
application/postscript
.ai .eps .ps
----
application/wordperfect
.wpd
----
application/mswrite
.wri
----
application/msexcel
.xls .xls3 .xls4 .xls5 .xlw
----
application/msword
.doc
----
application/mspowerpoint
.ppt .pps
----
application/x-director
.swa
----
application/x-shockwave-flash
.swf
----
application/x-zip-compressed
.zip
----
application/x-gzip
.gz
----
application/x-rar-compressed
.rar
----
application/octet-stream
.com .exe .dll .ocx
----
application/java-archive
.jar
/*{{{*/
Background: #e8f5e0
Foreground: #121e09
PrimaryPale: #fbfdfa
PrimaryLight: #a9d987
PrimaryMid: #5c9930
PrimaryDark: #17260c
SecondaryPale: #fcfafd
SecondaryLight: #c687d9
SecondaryMid: #803099
SecondaryDark: #200c26
TertiaryPale: #fbfafd
TertiaryLight: #a887d9
TertiaryMid: #5a3099
TertiaryDark: #160c26
Error: #f88
ColorPaletteParameters: HSL([95|11], [0.5195645017647156],[0.1|0.3959967969881699|0.6919935939763397|0.9879903909645096])
/*}}}*/
Unless you're delighted with the default theme you can make some quick changes by generating a new random color palette, hit this button to cycle through some alternatives.

<<RandomColorPaletteButton saturation_pale:0.67 saturation_light:0.53
saturation_mid:0.43 saturation_dark:0.06 pale:0.99 light:0.85 mid:0.5 dark:0.31>>

You can also change the look and feel completely by installing a new theme. To do this, find one you like in the @themes space, note down the name, and include it in this space by going to the space menu. You can reach the space menu by clicking on the blue and pink circle at the top-right of the page and chooshing "THIS SPACE". Here are a few to check out:
* @pip
* @caspian-ii
* @basalt
* @simplicity
* @cheesecake
* @jelly-doughnut

(//Note that if you are using a custom TiddlySpace install, these themes may not be present.//)
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<!-- Created with Inkscape (http://www.inkscape.org/) -->

<svg
   xmlns:dc="http://purl.org/dc/elements/1.1/"
   xmlns:cc="http://creativecommons.org/ns#"
   xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
   xmlns:svg="http://www.w3.org/2000/svg"
   xmlns="http://www.w3.org/2000/svg"
   xmlns:xlink="http://www.w3.org/1999/xlink"
   version="1.1"
   width="14pt"
   height="14pt"
   viewBox="918 510 14 14"
   id="svg3070">
  <metadata
     id="metadata3089">
    <rdf:RDF>
      <cc:Work
         rdf:about="">
        <dc:format>image/svg+xml</dc:format>
        <dc:type
           rdf:resource="http://purl.org/dc/dcmitype/StillImage" />
        <dc:title></dc:title>
      </cc:Work>
    </rdf:RDF>
  </metadata>
  <defs
     id="defs3072">
    <radialGradient
       cx="0"
       cy="0"
       r="1"
       id="Gradient"
       gradientUnits="userSpaceOnUse">
      <stop
         id="stop3075"
         style="stop-color:#ffffff;stop-opacity:1"
         offset="0" />
      <stop
         id="stop3077"
         style="stop-color:#2b2b2b;stop-opacity:1"
         offset="1" />
    </radialGradient>
    <radialGradient
       id="Obj_Gradient"
       xlink:href="#Gradient"
       gradientTransform="matrix(11.473944,0,0,11.473944,922.3752,513.7837)" />
  </defs>
  <g
     id="g3080"
     style="fill:none;stroke:none">
    <g
       id="g3082">
      <path
         d="m 929.6952,512.9018 c -2.5384,-2.53843 -6.654,-2.53843 -9.1924,0 -2.5384,2.5384 -2.5384,6.654 0,9.19238 2.5384,2.53839 6.654,2.53839 9.1924,0 2.5384,-2.53838 2.5384,-6.65398 0,-9.19238 m -4.5962,2.8407 2.07733,-2.07734 1.75547,1.75549 -2.0773,2.07735 2.0773,2.07732 -1.75547,1.75548 -2.07733,-2.07732 -2.07733,2.07732 -1.75547,-1.75548 2.0773,-2.07732 -2.0773,-2.07735 1.75547,-1.75549 z"
         id="path3084"
         style="fill:url(#Obj_Gradient)" />
      <path
         d="m 927.61447,515.38354 a 4.51205,4.2590378 0 1 1 -9.0241,0 4.51205,4.2590378 0 1 1 9.0241,0 z"
         transform="matrix(1.0218069,0,0,1.0462046,-18.063694,-21.648443)"
         id="path2394"
         style="fill:#000000;fill-opacity:0;fill-rule:evenodd;stroke:none;stroke-width:5;marker:none;visibility:visible;display:inline;overflow:visible;enable-background:accumulate" />
    </g>
  </g>
</svg>
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After reading this article and taking the test, the reader will be able to:
*Discuss the basic concepts and terminology for vascular Doppler US.
*Recognize the characteristic appearances of normal and abnormal liver Doppler waveforms.
*Describe the US manifestations of both normally functioning and malfunctioning TIPS.
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INTRAVASCULAR RADIOLOGICAL IODINATED CONTRAST MEDIA
Ronald G. Grainger

Iodine (atomic weight 127) is the only element that has proved satisfactory for general use as an intravascular radiological contrast medium (RCM). The iodine provides the radio-opacity: the other elements of the RCM molecule provide no radio-opacity but act as carriers of the iodine, greatly increasing the solubility and markedly reducing the toxicity of the total molecule.

The problem has always been how to package the iodine so that it may be delivered safely into very sensitive arterial systems (e.g. brain, heart, kidney) in the very large amounts required to produce adequate film-screen radio-opacity[1] (see later).

Organic carriers of iodine will probably remain the basis of all intravascular RCM for the foreseeable future. Since the 1950s, there are four chemical varieties of iodinated RCM in clinical use ( Fig. 2.1 , Tables 2.1, 2.2 [1] [2]). All four are tri-iodo benzene ring derivatives with three atoms of iodine at 2,4,6 positions (in monomers) and six atoms of iodine per molecule of the ring anion (in dimers); they are very hydrophilic, have low lipid solubility, low toxicity, low binding affinities for protein, receptors or membranes, and have molecular weights less than 2000[2] ( Table 2.1 ).

[img[f4-u1.0-B978-0-443-10163-2..50005-1..gr1.png]]

On intravascular injection, all of these four products are distributed rapidly because of high capillary permeability into the extravascular, extracellular space (except in the central nervous system [CNS]). They do not enter the interior of blood cells or tissue cells and they are rapidly excreted, with over 90 per cent being eliminated by glomerular filtration by the kidneys within 12h. None of these four chemical types of RCM have marked pharmacological actions. This is highly desirable as they are used purely as imaging and not therapeutic agents.

IONIC MONOMERS (HIGH OSMOLAR CONTRAST MEDIA [HOCM])
All ionic monomers are salts with sodium or meglumine (N-methyl glucamine) as the non-radio-opaque cation and a radio-opaque tri-iodinated fully substituted benzoic acid ring as the anion. These anions include diatrizoate (Urografin, Hypaque), iothalamate (Conray), ioxithalamate, metrizoate – the first two being by far the most frequently used. Each molecule completely dissociates in water solution into two ions – one non-radio-opaque cation and one tri-iodinated radio-opaque anion, giving an iodine:particle ratio of 3:2 (1.5) ( Table 2.1 and Figure 2.1 ). They are very hypertonic – 1600 mosmols kg-1 water at 300 mg iodine kg-1 compared to physiological osmolality of 300 mosmol kg-1 water.

NON-IONIC MONOMERS (LOW OSMOLAR CONTRAST MEDIA [LOCM])
Almén introduced the concept of non-ionic (and therefore low osmolar) contrast media in 1969 with metrizamide. The 2nd generation non-ionic monomers in 2006 include iohexol, iopamidol, iopromide, ioversol, ioxilan, etc. (Tables 2.1 and 2.2 [1] [2]) and are much more stable, much more soluble, much less toxic and much less expensive than metrizamide. None of these molecules dissociate in solution. They are tri-iodinated non-ionizing compounds and therefore in solution they provide three atoms of iodine to one osmotically active particle (the entire molecule), producing an iodine:particle ratio of 3:1 (Tables 2.1, 2.2 [1] [2], Fig. 2.1 ). They have less than half of the osmolality of HOCM. They have an osmolality of about 600 mosmol kg-1 water at a concentration of 300 mg I/ml-1 compared with the physiological osmolality of 300 mosmols.

IONIC DIMERS
Ioxaglate is the only compound in this group. It is a mixture of the sodium and meglumine salts of a monoacidic double benzene ring with each benzene ring having three atoms of iodine at C2, 4, 6 positions. The total molecule therefore contains six atoms of iodine and in solution each molecule dissociates into one radio-opaque hexa-iodinated anion and one non-radio-opaque cation (sodium and/or meglumine). Ioxaglate therefore has an iodine:particle ratio of 6:2 or 3:1 (Tables 2.1, 2.2 [1] [2], Fig. 2.1 ).

NON-IONIC DIMERS
Iotrolan (Schering) and iodixanol (Nycomed) are both examples of non-ionizing chemicals. They do not ionize or dissociate in solution. Each molecule contains two non-ionizing tri-iodinated benzene rings linked by a bridge (Tables 2.1, 2.2 [1] [2], Fig. 2.1 ). Each molecule therefore provides in solution six atoms of iodine for one molecule, i.e. an iodine:particle ratio of 6:1. Non-ionic dimers are physiologically isotonic (300 mosmol kg-1 water) in solution at 300 mg I/ml-1.

Iotrolan has been recently voluntarily withdrawn for intravascular use because of unexpected delayed reactions – usually with allergic and skin manifestations that are rarely serious but seem to be more severe and frequent in the Japanese. These delayed adverse reactions may also apply to other dimers. There are recent but unconfirmed reports that non-ionic dimers may be less nephrotoxic than non-ionic monomers [3] [4] (see renal toxicity later).

QUANTITY OF IODINE REQUIRED
Very large amounts of iodine are necessary because of the low sensitivity inherent in conventional photographic film-screen radiography. This low sensitivity to iodine is not an inherent property of the X-ray beam but is due to the low sensitivity of the photographic process in distinguishing minor differences in radio-opacity. Alternative nonphotographic X-ray detection recording systems, such as photodetectors with electronic amplification, like those used in CT scanning and in digital subtraction angiography (DSA), are very much more sensitive to minor differences in iodine concentration as demonstrated by 95 per cent tumour blush in all cerebral tumours on CT after IV injection of RCM compared to about 20 per cent blush after intra-arterial injection using photographic film-screen radiography.

The average daily physiological turnover of iodine is 0.0001 g. The total iodine content in the body (mainly in the thyroid) is 0.01 g. The requirement for a 2-, 3- or 4-vessel angiogram (with conventional film-screen photographic recording) may be 70 g iodine, delivered in, say, 30 min into the arterial supply trees of very sensitive organs, for example, the brain, kidney, or heart. This is 700 000 times the daily body turnover of iodine and it is testimony to the low toxicity of RCM (either HOCM or LOCM) that this huge quantity of iodine can be accepted into the arterial tree of the most sensitive organs of the body with very rare evidence of severe toxicity.

In complicated cases, these massive quantities may have to be increased by 100 per cent or even more, involving more than 200 g of iodine (400++ g of RCM) being injected intravascularly for film-screen radiographic angiography, probably the largest quantity of any drug used in the whole of clinical medicine.

INFORMED CONSENT
Informed consent is essential for any invasive procedure (angiography, angioplasty, vascular embolization, biopsy, etc.), but probably is not essential in many countries for uncomplicated procedures (e.g. intravenous urography [IVU]) in a reasonably fit patient, as it may alarm the pvatient to learn that there is a risk (however small) of a severe or fatal ADR. In some countries, e.g. the USA, informed consent may well be necessary, even in these patients.

Like every other drug, contrast agents should be administered only when there are clear and defensible clinical indications and when the prospects of benefit to the patient outweigh the risks and discomfort that may occur.

With modern contrast agents (either HOCM or LOCM), it is more likely that a complication occurring during a radiological arterial procedure will be due to the consequences of the instrumentation (e.g. vessel damage, thromboembolism) rather than to the contrast agent, if the latter is used in an appropriate dose and manner.

ADVERSE REACTIONS TO RADIOLOGICAL CONTRAST MEDIA [6] [7] [8] [9] [10] [11] [12]
An excellent (1999) review of adverse reactions, their mechanism, prophylaxis and treatment is presented by Sidhu and Dawson[6].

In clinical medicine, every technical procedure and every drug given to a patient by whatever route (oral, rectal, IV, IA, intrathecal) may cause adverse drug reactions (ADRs), which are sometimes fatal. Radiographic procedures and drugs are no exceptions. It is inevitable that even when administered appropriately, RCM will very occasionally result in a severe or even fatal ADR, sometimes leading to litigation. It has become increasingly difficult to defend inappropriate indications, inadequate resuscitation facilities and inappropriate experience, especially in small imaging departments, in either private or public hospitals.

TYPES OF ADVERSE REACTION
Adverse reactions to RCM may be divided into:
#Idiosyncratic anaphylactoid reactions
#Non-idiosyncratic reactions
#Combined 1 and 2 reactions.

Idiosyncratic anaphylactoid reactions
These ADRs are the most dreaded and most serious and fatal complications of RCM injection as they occur without warning, cannot be reliably predicted and are not preventable in the present state of our knowledge. These reactions usually (85 per cent) begin either during or immediately after the injection of contrast medium. ADRs are more frequent in patients who have had a previous adverse reaction to contrast medium, asthmatics, allergic and atopic patients, patients with impaired cardiovascular and renal systems, diabetics ( Table 2.3 ), and patients on beta-adrenergic blockers and possibly on nonsteroidal analgesics.

Idiosyncratic reactions vary greatly in severity and clinically may closely mimic true anaphylactic and allergic reactions, although there is no confirmatory evidence of a true antigen IGE antibody immunological reaction to contrast media.

Some possible mechanisms [5] [6] [10] [11] involved in causing these reactions are:
  	1   	Inhibition of enzymes such as cholinesterase (which de-activates and hydrolyses acetylcholine), resulting in increased concentration of acetylcholine; this may result in symptoms of vagal overstimulation, e.g. cardiovascular collapse, bradycardia, bronchospasm.
  	2   	Release of vasoactive substances such as histamine, serotonin or bradykinin may result in vasomotor collapse.
  	3   	Activation of physiological cascade systems including the complement activation system, the kinin system with bradykinin release, the coagulation system inducing intravascular coagulation and the fibrinolytic system causing lysis of fibrin and blood clots.
  	4   	The immune system disturbances.
  	5   	Anxiety, apprehension and fear of the radiological procedure probably plays a significant part in adverse reactions by activating a hypothalamic reaction resulting in cardiovascular and respiratory collapse and even death.

It is probable that many of these mechanisms are inter-related and that a self-perpetuating vicious circle is established, resulting in severe and perhaps fatal cardiovascular collapse.

Unlike the chemotoxic and hyperosmolar reactions, the earlier mentioned anaphylactoid reactions are not dose dependent and death has been known to occur following a 1 ml IV test dose, or after the full dose of RCM has been given after a negative test dose.

Non-idiosyncratic reactions
Unlike the idiosyncratic reactions, these non-idiosyncratic reactions are dose dependent and therefore relate to the chemical composition, osmolality and concentration of contrast medium and the volume, speed and multiplicity of the injection.
  	1   	Chemotoxic reactions. Chemotoxic adverse reactions are probably due to toxicity to the contrast medium anion rather than to its iodine content, as the iodine is very firmly bound to the benzene ring.

Some patients with a low iodine intake (often geographical), have an increased incidence of endemic goitre, are very sensitive to an increased intake of iodide, and may develop thyrotoxicosis after injection of RCM contrast agents. Presumably in these patients this is due to the very small amount of free iodide ions, which is known to be present in contrast medium solutions. Special care should be taken with patients who are thyrotoxic or goitrous.

Chemotoxic side effects include cardiac, neurological and renal toxicity as well as vascular manifestations.

Cationic toxicity may result from changes (either greater or lesser) in sodium or calcium ion concentration induced by injection of large amounts of RCM.
  	2   	Hyperosmolar reactions. The very high osmolality of high concentrations of HOCM (ratio 3:2) is 5–8 times the physiological osmolality (300 mosmol kg-1 water) of every cell in the body ( Table 2.1 , Fig. 2.1 ). It is not surprising therefore that adverse reactions may occur due to the marked hyperosmolality that develops when large volumes of concentrated HOCM are injected into the circulation. The degree of hyperosmolality is much reduced if non-ionic ratio 3:1 (LOCM) and (even more) if ratio 6:1 products isotonic non-ionic dimeric LOCM are injected instead of injecting HOCM of ratio 3:2 (Tables 2.1, 2.2 [1] [2]).

The adverse reactions due in part to hyperosmolality of the contrast medium include:
  	1   	Erythrocyte damage due to the loss of intra-erythrocytic water, leading to rigidification and reduction of the vital essential deformability of red cells, which is necessary for the erythrocytes (7μm diameter) to pass through capillaries (diameter 2–4μm).
  	2   	Endothelial damage. All RCMs, especially HOCM injure the endothelium by virtue of their chemotoxicity, ionicity and osmolality. The normal endothelium permits passage of molecules less than 50 000 molecular weight (HOCM or LOCM [even dimers] have molecular weights less than 20 000) by freely diffusing through intercellular pores and by transcytosis. Thus all RCMs are readily passed through the endothelium into the tissue fluid except in the CNS (blood–brain barrier – see later).

Damage to the capillary wall of the injected arterial territory (perhaps by RCM) leads to its increased permeability and the passage of toxic substances from the blood into the extravascular tissue fluid that bathes the tissue cells.

In addition to its semi-permeability membrane function, the endothelial cells of the capillaries also constitute a highly significant and very sensitive pharmacological tissue and they are stimulated to produce several active substances such as Factor XII, arachidonic acid, phospholipids, prostacyclins, angiotensin-converting enzymes, nitric oxide, pro-coagulants and anti-coagulants etc., which have considerable effects in vasoregulation and coagulation [6] [10].
  	3   	Blood–brain barrier damage is a specific example of endothelial damage. The central nervous system is the only tissue in the body that is normally protected from the passage of contrast medium molecules through the capillary wall, because the capillaries of the central nervous system are relatively impervious and have very tight intercellular connections. If this capillary blood–brain barrier is damaged, the molecules or ions of RCM may pass through the capillary wall into the extravascular neurological tissue fluid and exert a direct toxic effect on the delicate nerve tissue cells. A pathological increase of permeability of the blood–brain barrier occurs in several conditions, e.g. many cerebral and meningeal tumours, cerebral infarcts and in some infections. This is the basis of the very useful diagnostic sign of tumour staining, which is particularly well seen on CT, even after IV injection of contrast medium.
  	4   	Vasodilatation of the arteriolar and capillary bed of the injected artery is closely related to the hyperosmolality of the contrast medium solution. It may lead within a few seconds to a rapid increase in blood flow to several times the physiological flow rate. This is associated with a local uncomfortable feeling of warmth, heat, discomfort, or severe pain during peripheral arteriography. Systemic generalized vasodilatation following injection of large quantities of hyperosmolar contrast medium may lead to severe systemic hypotension, peripheral venous pooling and a diminished venous return to the heart, resulting in cardiovascular failure that may be extremely severe and even fatal.
  	5   	Hypervolaemia results from the osmotic attraction of extravascular tissue fluid into the circulation induced by the hyperosmolality of RCM. This may increase the blood volume by about 10 per cent within a few minutes, thus reducing haemoglobin concentration and increasing the demand on cardiac output and stress on the left ventricle.
  	6   	Cardiac depression with systemic hypotension, diminished venous cardiac return, myocardial ischaemia and the direct depression of myocardial contractility, particularly after coronary angiography.

All of these hyperosmolar reactions are closely related to the hyperosmolality of RCM and therefore depend on the dose, concentration and volume of RCM injected and are consequently considerably reduced by substituting LOCM for the very hypertonic HOCM.

Vasomotor reactions
These vasomotor ADRs may occur following either idiosyncratic (not dose-dependent) or non-idiosyncratic (dose-dependent) reactions induced by RCM, or may develop independent of other ADRs. There may be severe hypotension, tachycardia or bradycardia with marked apprehension, anxiety, sweating and disturbance, and depression of myocardial contraction with a markedly reduced cardiac output, leading to unconsciousness and cardiopulmonary collapse and possibly death.

Vaso-vagal reactions may also occur, characterized by bradycardia, whereas the vasomotor collapse states mentioned earlier are usually accompanied by tachycardia.

Complications
Minor reactions[7]
Flushing, nausea, arm pain, pruritus, mild urticaria, vomiting and headache[7] ( Table 2.3 ) occur in 5–10 per cent of patients injected with HOCM but less than 1 per cent when LOCM is injected. These are usually mild in severity, of short duration, self-limiting and generally require no specific treatment other than reassurance and restoration of the patient's confidence. Occasionally an oral antihistamine (e.g. chlorpheniramine [Piriton] 4 mg) for urticaria, a tranquillizer (e.g. diazepam [Valium] 5 mg) or a mild analgesic (e.g. aspirin 300 mg or paracetamol 500 mg) may be helpful.

Arm pain may be due to a small unrecognized extravasation, but venous spasm on entirely intravascular injection may also occur, especially with HOCM. There may be local oedema, very rarely resulting in cellulitis, compartment syndrome, or tissue necrosis.

A major problem may arise if there is a large extravasation such as in powered injections of RCM for dynamic CT. A major recent advance is automatically to electrically stop the pump[5]. The electrical skin impedence changes if there is significant extravasation. Electrodes over the site of injection are connected by cable to the power injector, which is automatically immediately cut off if significant extravasation occurs. This is an important safety device that has been adopted by several manufacturers of powered injectors, and permits higher IV flow rates with considerably increased security[5].

Intermediate reactions
More serious degrees of the above generalized symptoms, including moderate degrees of hypotension and bronchospasm occur in 0.5–2 per cent of IV injections of HOCM and is probably reduced to one-quarter of that frequency following IV LOCM[7] ( Table 2.3 ).

These intermediate reactions disturb both the patient and the doctor but do not cause alarm. They usually respond readily to appropriate therapy – reassurance, chlorpheniramine (Piriton) (4–10 mg orally, intramuscularly or intravenously) for urticaria or angioneurotic oedema, diazepam (5 mg) for anxiety, salbutamol β2 agonist inhalation for bronchospasm, hydrocortisone 100–500 mg IM or IV, adrenaline 0.1–0.5 ml of 1/1000 solution intramuscularly or subcutaneously (children 0.01 ml kg-1 body weight up to 3 mg max.) for more severe bronchospasm – repeated if necessary.

Severe life-threatening reactions
These include severe manifestations of all of the above symptoms and occur in about 0.2 per cent after HOCM and about 0.04 per cent following LOCM[7] ( Table 2.3 ).

Severe reactions include convulsions, unconsciousness, laryngeal oedema, severe bronchospasm, pulmonary oedema, severe cardiac dysrhythmias and cardiac arrest, cardiovascular and respiratory collapse. Treatment is urgent: the patient is very alarmed and the doctor is seriously worried about the patient's possible demise. The responsible clinician (usually the radiologist) must be well trained in emergency treatment as these severe ADRs are unpredictable in occurrence and in response to treatment.

Treatment [6] [10] [11] [12] must be urgently and expertly administered according to a pre-arranged well-practised schedule. Additional medical (including anaesthetic) assistance should be immediately available. A crash trolley complete with oxygen cylinders, flow valves, suction equipment, oral airways, nasal tubes, endotracheal tubes, face masks, ambu-type bag, stethoscope, sphygmomanometer, syringes, needles, cannulae and tracheotomy set is essential. A suction machine, electrocardiogram (ECG), blood pressure monitor and DC defibrillator must also be readily available. There must be a comprehensive selection of drugs and IV fluids necessary for resuscitation and the means and the personnel for their safe administration must be readily available.

The airway must be secured and oxygen, artificial respiration, external cardiac massage and electrical DC defibrillation must be administered as and when required. IV fluid infusion (normal saline, lactated Ringer's solution) through an indwelling IV catheter is essential to restore blood volume and to administer IV drugs:
  	•   	a powerful diuretic such as frusemide (Lasix) 20–40 mg IV slowly or IM for pulmonary oedema
  	•   	diazepam and barbiturates for convulsions
  	•   	adrenaline (see later)
  	•   	salbutamol (b2 agonist metered dose inhaler)
  	•   	hydrocortisone or methyl prednisolone (100–1000 mg)
  	•   	aminophylline (very slowly, 250–500 mg) intravenously for intense bronchospasm
  	•   	chlorpheniramine for allergic or anaphylactic symptoms
  	•   	vasopressors, e.g. noradrenaline (or metaraminol [Aramine] 0.5–5 mg slow IV infusion)
  	•   	dihydroxyphenylaline (or dopamine) infusion (2.5–5μg kg-1 min-1) for hypotension with monitoring of the blood pressure

Sodium bicarbonate infusion should be administered to correct any acidosis, and atropine 0.6–1.0 mg IV or IM repeated if necessary (children 0.02 mg kg-1 repeated if necessary to 2 mg total) is used for vasovagal reactions, bradycardia and cardiac failure.

Adrenaline (recently prepared solution and in date) is much more rapidly effective than steroids: it is the main therapeutic agent and should always be readily available for it is the essential treatment. In severe anaphylactoid reactions it should be administered as soon as possible and may be life-saving.

Adrenaline (epinephrine) (0.3–0.5 ml, 1/1000 solution [children 0.01 ml kg-1 body weight] by deep SC or IM injection repeated at 10–20-minute intervals) provides the most rapid and reliable relief for bronchospasm, angioneurotic oedema and other anaphylactoid symptoms. Adrenaline has occasionally precipitated ventricular fibrillation when given by IV injection, but in very severe anaphylactoid reactions, even this route should be considered, injecting 1–5 ml, 1/10 000 solution, very slowly, preferably under ECG control.

Corticosteroids take several hours to become fully effective, even when given intravenously, but they should be administered immediately and intravenously in severe anaphylactoid reactions.

Deaths
The earlier mentioned severe adverse reactions may not respond even to expert, rapidly administered treatment and the patient may die. Death may however be immediate and without warning. It usually results from intractable cardiopulmonary collapse, pulmonary oedema, or intense bronchospasm.

The death rate following IV injection of contrast medium is not known with accuracy. One death in 40 000 IV injections of HOCM is often quoted as a medium figure.

Both the Katayama[7] (in Japan) and Cashman (in Australia) papers were unblinded large surveys, but despite being criticized (reasonably) on methodological grounds, they are very useful contributions to the international literature and knowledge of RCM. They both found that deaths due to LOCM are no fewer than to HOCM[6].

A very interesting analysis of Deaths Related to Iodinated Contrast Radiological Media (ICRM) reported to the United States Federal Drugs Administration between 1979 and 1994 (estimated 170 million IRCM studies) was published in 1997[9] and concluded that despite the increasing availability and usage of the safer LOCMs in the USA in 1978–1994, the data do not show a decrease in RCM-related deaths to LOCM as opposed to HOCM injection.

Factors significantly predisposing to adverse drug reactions ( Table 2.4 )
All ADRs are significantly more frequent with HOCM (12.66 per cent) than with LOCM (3.13 per cent)[7] ( Table 2.3 ).

PATIENTS CONSIDERED TO BE AT GREATER THAN USUAL RISK OF A SEVERE ADVERSE REACTION TO IODINATED RADIOLOGICAL CONTRAST AGENTS
  	1.   	Patients with a previous ADR to RCM (excluding mild flushing, nausea)
  	2   	Asthmatics
  	3.   	Allergic and atopic patients
  	4.   	Cardiac patients with decompensation, unstable arrhythmia, recent myocardial infarction
  	5.   	Renal patients in failure, diabetic nephropathy, on metformin
  	6.   	Feeble infants and aged patients
  	7.   	Patients with a severe general debility
  	8.   	Very nervous, anxious patients
  	9.   	Patients with various metabolic and haematological disorders
  	10. 	Thyrotoxic: goitrous patients

Previous adverse reactions to RCM and a history of asthma are the two most dangerous adverse predisposing factors. These and others include:
  	1   	Previous adverse reaction. A previous adverse reaction to contrast medium increases the risk factor of a reaction to a second LOCM injection (severe ADR 0.18 per cent)[7] ( Table 2.3 ).
  	2   	History of asthma or bronchospasm. Patients with a previous history of bronchospasm, however mild, have an increased risk of an adverse reaction to RCM (0.23 per cent severe ADR, Table 2.3 ). Subsequent reactions to a second RCM injection may be very severe and even fatal.
  	3   	History of allergy or atopy. Patients with known allergy, particularly to foodstuffs and perhaps especially to iodides have an increased incidence of an ADR (0.10 per cent severe ADR)[7] ( Table 2.3 ).
  	4   	Cardiac disease. The risk of severe ADRs in severe cardiac disease is 0.10 per cent severe ADR following LOCM[7] ( Table 2.3 ). A high sodium load caused by a large volume of HOCM containing sodium salts should be avoided, as this may exacerbate cardiac decompensation due to hypervolaemia and myocardial depression.
  	5   	Renal disease[6]. Mild temporary renal dysfunction may occur in around 5 per cent; serious renal impairment occurs in about 0.1 per cent[7] ( Table 2.3 ). The most important safeguard against RCM-induced renal failure is adequate hydration, given orally or intravenously.
  	6   	Dehydration. All patients must be well hydrated (if necessary by IV) before and after contrast medium is injected. The previous practice to dehydrate the patient deliberately for IVU (in order to produce an improved image of the renal calices) is very dangerous and must be abandoned in all patients.
  	7   	Haematological and metabolic conditions. Patients with sickle cell anaemia may react adversely, particularly to HOCM, which may cause an increase in sickling, with potentially serious or even fatal complications following selective cerebral and coronary angiography.
  	8   	Anxiety and apprehension. Anxiety and apprehension definitely predispose to adverse reactions.
  	9   	Other conditions. Manifest hyperthyroidism is a contra-indication to RCM administration. Neonates and aged and infirm patients are probably at increased risk because of their associated morbidities.
  	10   	Delayed adverse reactions. Serious adverse reactions usually begin during or within 15 min of IV injections of RCM. In the last few years it has become apparent that some patients (perhaps as much as 10–20 per cent) experience reactions that may be delayed for a few days. These delayed reactions are usually uncomfortable, time-limited and not dangerous.

Patients with a thrombotic tendency such as severe polycythaemia may have an increased risk, especially after arterial injections of non-ionic LOCM.

HOCM inhibits thrombosis more than LOCM. Patients with myelomatosis may develop renal failure after contrast medium injection, with proteinaceous casts and precipitation of Bence-Jones protein and Tamm-Horsfall protein possibly causing renal tubular obstruction. These reactions are now much less frequent because LOCMs are much less toxic and less protein binding, and the previous practice to dehydrate the patient before IV urography is now completely reversed.

Patients with phaeochromocytoma may develop a hypertensive crisis during angiography or IV urography as a reaction to the contrast agent, to abdominal compression or to manipulation of the tumour. Whenever phaeochromocytoma is suspected, these patients should be prepared with preliminary alpha- and beta-adrenergic blockade before angiography.

Patients with pre-existing renal disease, particularly the renal complications of diabetes mellitus, have an increased risk of an adverse reaction to RCM, which may precipitate renal failure. LOCM is preferred especially if the patient has pre-existing renal impairment [6] [10] [11] [12].

Recent evidence[3] suggests that iso-osmolar dimer (iodixanol) LOCM may be even less nephrotoxic than monomeric LOCM (iohexol), which has twice the physiological osmolality. In a multicentred trial of diabetics with pre-existing renal impairment (serum creatinine 115–308 mmol-1) 129 patients underwent angiography[3]. There was a significant increase in contrast-induced nephrotoxicity with increased serum creatinine in 26.2 per cent of the iohexol (non-ionic monomer) group compared to 3.1 per cent in the iodixanol (non-ionic dimer) group. This important finding is being strongly challenged partially because of the large size of the dimer molecule (which may itself impose a renal problem) and the possibility of an increase in delayed ADRs.

In 2005 an in vitro study considered the cytotoxic adverse effects on renal tubular cells of non-ionic dimers (iodixanol and iotrolan) compared with monomer LOCM (ioversol and iomeprol). This study demonstrated significantly more toxic effects of the dimers when compared on an equi-molar concentration with the monomers[4]. The authors conclude that their in vitro research indicates considerable caution in accepting the advantages of the dimers reported in the previous paper[3].

Metformin (phenoformin), an oral biguanide hyperglycaemic therapy for diabetes mellitus Type 2, is primarily excreted by the kidney. In patients with severe renal impairment, intravascular accumulation of the biguanide may occur after RCM, and this may precipitate biguanide lactic acidosis (vomiting, diarrhoea, somnolence) – a potentially fatal complication. RCM-related lactic acidosis is extremely rare in diabetics receiving metformin if the patient has normal renal function before RCM. It is therefore recommended[12] that metformin need only be discontinued if there is pre-existing renal impairment and it may be recommenced 48h later after re-assurance of good renal function after RCM.

These delayed reactions are more common in women: arm pain (7 per cent), delayed rash (5 per cent), flu-like symptoms (headache, skin lesions, salivary gland swelling – ‘iodide mumps’ (9 per cent) probably due to ‘iodism’) are the more important late manifestations. Presumably the reaction is idiosyncratic and not dose dependent.

A few cases (including deaths) of delayed vasculitis, disseminated lupus erythematosis and Stevens–Johnson syndrome have been reported after injection of LOCM.

Delayed reactions in general may be more frequent with LOCM than with HOCM and with dimers compared to monomers. Iotrolan – a non-ionic dimer – has been voluntarily withdrawn from intravascular clinical usage because of a worryingly high incidence of delayed adverse reactions, mainly reported in Japan. It is possible that similar delayed ADRs may occur after other similar dimeric LOCMs.

PRINCIPLES OF INVESTIGATING PATIENTS AT INCREASED RISK
Manifest active hyperthyroidism is an absolute contra-indication to RCM administration. The following suggestions should be noted:
  	1   	Despite the above extensive list of those patients who have a known predisposition to adverse reactions, many com plications of contrast medium injections are unpredicted and unpredictable.
  	2   	The radiologist must always weigh the possible advantages to the patient of the diagnostic procedure against the very small but ever-present risk of a severe adverse reaction (and even death) to the contrast medium and the technique of its administration.
  	3   	In many patients deemed to be at increased risk of an adverse reaction, the RCM procedure may be replaced by other imaging investigations, such as ultrasound (US), computed tomography (CT) or magnetic resonance imaging (MRI), often not requiring injections of any contrast agent but producing equal or improved diagnostic information.
  	4   	The referring clinician should be consulted and advised if the patient is thought to be at increased risk. The patient should be informed, consulted and reassured as necessary. The discussion and result should be recorded in the patient's notes.
  	5   	Although a routine test dose is generally not necessary, it is advisable to perform a 1 ml or smaller test dose, either by IV or mucosal testing in patients considered to be at increased risk of an ADR.
  	6   	The smallest dose of RCM that will give reliable, comprehensive diagnostic results should be used. This is especially important in patients with pre-existing renal impairment or diabetes, those who are poorly hydrated, infants and those who may require further RCM procedures.
  	7   	All patients receiving RCM, particularly if there is previous renal impairment and those patients receiving large quantities of RCM, must be very well hydrated (if necessary intravenously) before and after the injection in order to excrete the RCM as completely and quickly as possible.
  	8   	Do not leave the patient unattended for the first few min after the injection.
  	9   	Premedication is strongly advised for previous adverse reactors, especially in asthmatic and allergic patients, who should be given pre-injection and post procedure 24h of oral corticosteroids and possibly antihistamines.
  	10   	In all patients considered to be at increased risk, LOCM should be administered in preference to HOCM.
  	11   	Before administering the injection, the emergency trolley, alarm system and availability of experienced assistance must be confirmed.

CONTRAST MEDIA RELATED TO SPECIFIC CLINICAL AREAS
RENAL TRACT [6] [10] [11] [12]
There is no doubt that high doses of contrast media impair renal function, usually peaking at 3–5d, causing a decrease in urine output and an increase in serum creatinine and urea levels, decreased creatinine clearance and reduced glomerular filtration rate (GFR). In some patients this may proceed to renal failure with anuria, uraemia and death. Renal dialysis (either intravascular or peritoneal) is very effective and may be life-saving as an alternative method of excreting RCM and uraemic metabolic products.

These severe adverse reactions are very unlikely to occur if the patient is well hydrated and has normal renal function before the RCM injection. Particularly important adverse factors are pre-existing renal failure and oliguria, diabetic nephropathy, nephrotoxic drugs, patients who are not well hydrated and patients who are liable to be injected with very high doses of RCM for multiple sequential examinations repeated within a few days. Alternative imaging procedures must always be considered.

The usual recommended dose for IV urography in the normally well-hydrated adult with normal renal function is 15–25 g iodine; this dose may be increased provided the patients are well hydrated (by IV normal saline if necessary before, during and after RCM injection). A maximum of about 70 g of iodine (1 g iodine kg-1 body weight in adults) is generally advisable even in patients with good renal function, but considerably larger quantities (up to 200 g or even 300 g of iodine, i.e. up to 600 g of RCM) may be required, particularly in difficult angiographic and interventional procedures.

Nephrotoxic drugs (diuretics, antibiotics, non-steroidal anti-inflammatory drugs, cytotoxic therapy) may enhance the adverse effects of RCM. Diabetic patients receiving metformin should be given special attention (see earlier).

After early uncertainty, it is now established that HOCMs are more nephrotoxic, and LOCMs are preferred for all patients considered to be at increased risk, especially with diabetic nephropathy. There is increasing evidence that RCM (particularly HOCM and large doses) may induce damage to the tubules in the renal medulla and reduce intra-medullary blood flow in patients with acute calculus renal colic.

It is not yet established whether monomer LOCM or dimer LOCM have the lower renal toxicity (see earlier) [3] [4].

NERVOUS SYSTEM
LOCMs are much more comfortable for cerebral arteriography in the conscious patient and are always preferred. Cerebral RCM photographic arteriography is being strongly challenged and partially displaced by CT and MR angiography (MRA).

Cerebral angiography
Adverse reactions to RCM include dilatation of the external carotid arterial territory causing facial pain and heat. Damage to the blood–brain barrier may cause dangerous cerebral oedema, bradycardia and hypotension.

Myelography
Myelography is being rapidly replaced by MRI (and to a lesser extent by CT) and very few myelograms are now performed in well-equipped imaging departments. If contrast medium myelography is essential, then non-ionic LOCM must be injected, for ionic contrast media (both HOCM and LOCM) are very toxic and often fatal when injected into the subarachnoid space.

Myelography with oily products, such as iophendylate (Myodil, pantopaque – standard products in the 1940s–1980s) have been completely abandoned as it is now known that severe chronic adhesive arachnoiditis may follow their injection, sometimes causing considerable pain, disability and compression of the lumbosacral nerve roots with severe neurological deficit.

CARDIOVASCULAR SYSTEM
Peripheral Arteriography
The usual iodine concentration required for conventional film–screen angiography is about 300 mg I ml-1 contrast medium. Conventional HOCM (1500 mosmol kg-1 water) has been completely displaced for peripheral arteriography by LOCM (600–700 mosmol kg-1 water), because the latter causes much less warmth, discomfort, pain and movement. LOCM ( Table 2.3 ) permits almost painless angiography in all territories, usually eliminating discomfort, movement and the need for general anaesthesia.

Peripheral Venography
Venography of the leg for possible deep vein thrombosis (DVT) is the most frequent venographic study. The procedure is performed by injecting RCM into a small vein of the foot, with the leg dependent and tourniquets restricting peripheral venous return. If the deep veins are already compromised and partly thrombosed, peripheral venography of the leg is a potentially dangerous procedure, as both deep and superficial venous return from the leg are compromised, and some cases of venous gangrene due to venous endothelial damage and thrombosis have been induced by attempted venography.

LOCM is strongly advised because of its lower osmolality and its less irritant effect on the venous endothelium. Endothelial contact time should be reduced to the minimum by washing out with saline, massaging and exercising the leg immediately after satisfactory radiographs have been obtained. Termination of the injection of contrast medium must be seriously considered if the injection causes pain or if the deep veins are seen to be extensively thrombosed, for all RCM may induce thrombophlebitis.

Although leg venography is still the ‘gold standard’ for imaging DVT, it is being increasingly replaced by compression ultrasound (without contrast medium).

Cardiac and Coronary Angiography
Intracardiac injections LOCM injections are much preferred as they cause less disturbance of cardiac function, depression of myocardial contractility, peripheral vasodilatation, hypervolaemia, systemic hypotension and ECG changes. They are also much better tolerated subjectively than HOCM.

Pulmonary angiography LOCM injections should be used for pulmonary angiography as they cause less elevation of the pulmonary artery pressure, coughing, movement and discomfort. Separate unilateral pulmonary artery injections should replace main stem pulmonary artery injection.

Aortography Injections of LOCM at the 300–400 mg ml-1 iodine concentration are greatly preferred as they cause much less discomfort and vasodilatation.

Coronary angiography HOCMs (e.g. Urografin 76 per cent) with physiological levels of sodium and which do not bind avidly to serum calcium (related to buffer agents) had a good reputation for selective coronary angiography, but LOCMs are even safer for they cause less marked haemodynamic, myocardial and physiological changes and depression.

Coronary angioplasty (PTCA) and stent placement During therapeutic coronary angioplasty, the intima and the arterial wall are deliberately torn and stretched by the intra-arterial balloon considerably increasing the risk of local arterial occlusion. The most important controllable factor in reducing this risk is the expertise of the operator (see later). Many investigators utilize full heparinization of the patient and LOCM injections.

CONTRAST MEDIA, BLOOD COAGULATION AND THE ENDOTHELIUM[6]
In the 1990s it was confirmed that unlike ionic LOCM, non-ionic contrast media do not strongly inhibit thrombin formation or fibrin polymerization (with the consequent coagulation of blood), nor do they significantly inhibit platelet activity and aggregation.

LOCMs do not inhibit blood coagulation as markedly as do HOCMs. Despite this disadvantage, LOCMs are now utilized for almost all angiographic and angioplasty procedures. Meticulous care must be taken to prevent catheter/guide wire thrombosis or sludging by constant perfusion of heparinized saline, continuous trans-catheter pressure recording and preventing blood entering the syringe (preferably plastic, not glass). Some angiographers routinely heparinize the patient for angiography and most angiographers do so during angioplasty.

The production of many vaso-active physiological agents by the endothelium when exposed to RCM is discussed earlier [6] [11].

PREVENTION OF ADVERSE REACTION TO RCM
There is no known premedication regime that can be relied upon to eliminate completely the risk of a severe adverse reaction to RCM. Several strategies for prophylactic premedication have been suggested, usually involving the use of (some or all of) corticosteroids, antihistaminics, H1 and H2 antagonists and ephedrine.

The present author (Grainger) strongly recommends that in all patients considered to be at increased risk of adverse reactions ( Table 2.4 ), alternative imaging should always be considered; premedication with corticosteroids (and possibly with antihistaminics) should be administered for the 12–24h before and after injection of RCM, and that LOCM (rather than HOCM) should be used in all these patients in whom further administration of contrast medium is considered to be essential.

ETHICAL, FINANCIAL AND COST–BENEFIT CONSIDERATIONS
HIGH-VERSUS LOW-OSMOLAR CONTRAST MEDIA
The incidence of mild, moderate and severe adverse reactions is markedly less frequent with LOCM than with HOCM[7] ( Table 2.3 ). In the late 1990s, the only factor inhibiting the total abandonment of HOCM and its replacement by LOCM was financial, because LOCM was considerably more expensive. Recent major reduction in LOCM prices (industrial competition, expiration of patent protection, improved manufacturing techniques and user pleadings) has markedly changed this late 1990s position.

The strong recommendation must be that LOCM should be used for intravascular injection in all patients, especially those at increased risk.

Unfortunately there are still many impoverished countries where total conversion to LOCM is not a major medical requirement and is not financially justified, and they reasonably continue to use HOCM.

CONCLUSION
Both HOCM and LOCM are probably the safest drugs used in clinical medicine. It is not yet proven that LOCM reduces the fatality rate compared to HOCM. There is no doubt that LOCMs produce less discomfort on IV injection, less pain on intra-arterial injection, less physiological and haemodynamic disturbance and fewer adverse reactions to contrast agents than does HOCM. Recent major reduction in cost has encouraged the use of LOCM in about 80–90+ per cent of all intravascular radiographic injections in Europe, North America, Australasia, Japan and many other countries.

Because of the concern about the ill-effects of radiation exposure, it is probable that in the next few years, radiological methods will be progressively replaced by MRI using blood pool and other specific contrast agents.

The Manual on Contrast Media, 4th edition, published by the American College of Radiology in 1999 and The European Society Guidelines on Contrast Media (2003) Version 3.0 are excellent practical handbooks. Two encyclopaedic textbooks (Dawson, Cosgrove and Grainger[6] and Thomsen, Muller and Mattrey[11]) dealing exclusively with contrast agents (radiological, US and MRI) with contributions from internationally respected clinicians and industry scientists were published in 1999 and are recommended if further information is required.

MRI CONTRAST MEDIA
EXTRACELLULAR MRI CONTRAST AGENTS
Henrik S. Thomsen and Sameh K. Morcos

Extracellular MRI contrast agents are diagnostic pharmaceutical compounds containing paramagnetic metal ions that affect MR signal properties of surrounding tissues. Paramagnetic agents are mainly positive enhancers that reduce the T1 and T2 relaxation times and increase tissue signal intensity on T1-weighted MR images and have almost no effect on T2-weighted images. Initially it was thought that MRI did not need contrast media due to the excellent soft tissue contrast compared to CT. However, in 2005, up to 40 per cent of all MRI examinations worldwide were performed with contrast agents.

The majority of contrast-enhanced MRI examinations are performed with extracellular, not organ-specific agents. However, organ-specific agents (e.g. liver, lymph nodes) have recently become available (see later section).

Almost 25 years ago, copper (Cu2+), manganese (Mn2+) and gadolinium (Gd3+) were considered as potential paramagnetic ions to be used for MRI. However, Gd is the most powerful, with seven unpaired electrons, but unfortunately gadolinian is the most toxic of those ions and therefore it is necessary to encapsulate it by a chelate.

The first agent to be introduced into clinical practice was the gadolinium diethylene triamine pentacetic acid salt (Gd-DTPA). The chelate DTPA was already known from its use in nuclear medicine (99mTc-DTPA). Several extracellular Gd chelate MRI contrast agents are currently available for clinical use in addition to Gd-DTPA. Some of these agents are ionic with high osmolality; others are non-ionic with osmolality twice that of the blood ( Table 2.5 ). All the extracellular MRI contrast agents have a high tolerability in animal studies and good relaxation properties.

In this chapter the pharmacokinetics, clinical use and safety of these agents will be discussed, including possible interaction with clinical tests and their use for radiographic examinations.

PHARMACOKINETICS
The pharmacokinetics of all extracellular MRI contrast agents with the exception of gadobenate dimeglumine (Gd-BOPTA) are similar to iodinated water-soluble contrast media. They have low molecular mass and after IV injection they are rapidly diffused into the interstitial extravascular space. Reverse diffusion into the intravascular compartment also occurs and a state of equilibrium between diffusion in and out is usually reached within 2h. Gd chelates are eliminated unchanged from the intravascular compartment by passive glomerular filtration and by 24 hours >95 per cent of the injected dose is excreted in urine with normal renal function. A very small amount (<0.1 per cent) is eliminated via faeces. The biological half-life is approximately 1.5h. Extracellular MRI contrast agents do not cross the intact specialized vascular blood–brain barrier. They do not bind to proteins or receptors and there is no intracellular penetration.

Unlike all other Gd chelates, gadobenate dimeglumine has a capacity for weak and transient protein binding and is eliminated through both the renal and hepatobiliary pathways. The hepatic uptake represents 2–4 per cent of the injected dose. It behaves as a conventional extracellular contrast agent in the first minutes following IV administration and as a liver-specific agent in a later delayed phase (40–120 min after administration) when it is taken up specifically by normal functioning hepatocytes.[13]

CLINICAL USE OF EXTRACELLULAR MRI CONTRAST AGENTS
These agents accumulate in tissues with abnormal vascularity (malignant and inflammatory lesions) and in regions where the blood–brain barrier is disrupted. Owing to their rapid equilibration in the interstitial space of both normal and tumour/inflammatory tissues, the use of dynamic MR imaging after bolus injection makes the best use of the narrow imaging window with a transiently increased tumour/inflammatory to normal tissue contrast. Generally the recommended dose for clinical use is 0.1 mmol kg-1 body weight but up to 0.3 mmol kg-1 may be used, particularly in MRA. [13] [14] [15]

SAFETY OF EXTRACELLULAR MRI CONTRAST AGENTS
Extracellular MRI contrast agents are well tolerated with a low incidence of adverse effects. There are no differences in the safety of the various agents except when it comes to extravasation in soft tissue; then the osmolality is important and high osmolar agents are likely to induce more local damage. In blood, the osmotic load of all Gd-based contrast media is very low, compared to iodinated contrast media, because only a small amount of the contrast agent is required to produce a diagnostic MRI examination.

Adverse reactions such as nausea/vomiting, urticaria, bronchospasm, laryngeal oedema, hypotension and generalized anaphylactoid reaction, which are observed with radiographic iodinated contrast media, may also be seen with extracellular MRI contrast agents but the incidence is much lower. The incidence of mild adverse effects is less than 5 per cent. Life-threatening reactions are very rare, with an incidence around 1:100 000. Fatal reactions may however occur but are extremely rare.[13]

CONTRAST MEDIUM-INDUCED NEPHROPATHY
Extracellular MRI agents are more nephrotoxic than iodinated contrast media in equimolar doses. However, nephrotoxicity after contrast-enhanced MRI examinations is not common even in patients with renal disease as the dose of Gd-based contrast medium required for a diagnostic MRI examination is small in comparison to the doses of iodinated contrast media that are routinely used for CT or other radiographic examinations. However, in patients with marked reduction in renal function (particularly due to diabetes mellitus), contrast medium-induced nephropathy may occur even at the standard doses of extracellular MRI contrast agents (see later section on NSF).[16]

NEPHROGENIC SYSTEMIC FIBROSIS (NSF)
Recently (2006 and 2007) several reports have suggested that the administration of extracellular gadolinium based contrast agents (Gd-CA) may trigger the development of NSF in patients with advanced renal impairment (GFR < 30 ml/min) or on dialysis. The incidence of this condition in this group of patients is around 3–5% and the onset varies from a few days to 3 months after administration of Gd-CA. The disease is characterised by scleroderma-like skin changes that mainly affect the limbs and trunk. The induration of the skin can progress to cause flexion contracture of joints. The fibrotic changes may also affect other organs such as mus cles, heart, liver and lungs. The disease can be aggressive, in some patients leading to serious physical disability or even death. The considerable majority of reported NSF complications followed the administration of non-ionic gadodiamide, but in a few patients NSF followed injection of gadopentate dimeglamine, gadovestomide and other gadolinium contrast agents. [18] [19] [20] [21]

The stability of the binding of the gadolinium ion (Gd+++) within the chelate could be an important factor in the pathogenesis of NSF and may explain the strong association between gadodiamide and this condition. The stability of the Gd-chelates is influenced by the configuration of the molecule whether linear or macrocyclic and ionicity. Macrocyclic chelates offer better protection and binding to Gd+++ in comparison to the linear molecules. Replacement of carboxyl group by a less strongly coordinating group to produce a non ionic Gd-CA also weaken the binding of the chelate to Gd+++ particularly in the non ionic linear molecule. Stability measurements ( Table 2.5 ) indicate that the least stable molecules are the non ionic linear chelates, and most stable is the ionic cyclic chelate. In vivo, transmetallation with endogenous ions leading to the release of the highly toxic gadolinium ions (Gd+++) is likely to occur with unstable Gd-CA particularly if they remain in the body for a long period, as is the case in patients with advanced renal impairment or on dialysis. Recent reports demonstrated gadolinium in the skin lesions of patients with NSF strengthening the hypothesis that free gadolinium play an important role in triggering this condition. It is advisable at this stage of our understanding to [*]avoid the administration of non-ionic linear chelates in patients with advanced renal impairment (GFR <30 ml/min) including those on dialysis. A more stable Gd-CA such as macrocyclic Gd-chelates might prove less hazardous if contrastenhanced MRI examination is thought to be necessary in such a group of patients, including pregnant and lactating women with end-stage renal failure. There is no evidence that immediate haemodialysis after administration of Gd-CA protects the patient against NSF[*]. [20] [21]

PREVENTION OF ADVERSE REACTIONS
It is not recommended to give any prophylaxis before administering extracellular MRI agents. However, if there has been a previous hypersensitivity-like reaction to a gadolinium-based compound, an alternative imaging investigation should be considered. If the administration of a Gd-based contrast agent is deemed essential, a different MRI contrast agent to the one incriminated in the previous reaction should be used and corticosteroid prophylaxis might offer some protection. There is no cross-reaction between extracellular MRI contrast agents and radiographic iodinated contrast media. Patients with multiple allergies may react to both iodinated and gadolinium-based contrast media.[13]

USE OF EXTRACELLULAR MRI CONTRAST AGENTS IN SPECIAL GROUPS OF PATIENTS
Patients on dialysis
Extracellular MRI contrast agents are easily removed by haemodialysis or continuous ambulatory peritoneal dialysis. There is no need to schedule the MRI examination in relation to the dialysis session.

Pregnancy and lactation
Mutagenic and teratogenic effects have not been described after administration of gadolinium-based contrast media. Therefore, if the MR examination is deemed necessary, an extracellular MRI contrast agent may be given to a pregnant female.

Only tiny amounts of gadolinium-based contrast media given to a lactating mother reach the milk and only a minute proportion is absorbed from the baby's gut. Therefore, stopping breast-feeding for 24h following administration of a gadolinium-based contrast media is not warranted.[13]

INTERACTION BETWEEN EXTRACELLULAR MRI CONTRAST AGENTS WITH CLINICAL TESTS
Extracellular MRI contrast agents may cause spurious hypocalcaemia as they can interfere with the assay method of calcium measurement. Awareness of this effect on calcium measurements by some MRI contrast agents is important in order to avoid incorrect and potentially hazardous treatment. Caution should be exercised when using colorimetric assays for angiotensin-converting enzyme, calcium, iron, magnesium, total iron binding capacity and zinc in serum samples of patients who have recently received Gd-based contrast media. Therefore, biochemical assays are better performed before contrast media injection, or delayed for at least 24h afterwards or longer in patients with renal impairment. Urgent laboratory tests performed on specimens collected shortly after contrast media injection should be carefully assessed. Accuracy of unexpected abnormal results should be questioned and discussed with colleagues from the hospital laboratories.[22]

USE OF EXTRACELLULAR MRI CONTRAST AGENTS FOR RADIOGRAPHIC EXAMINATIONS
Gadolinium attenuates X-rays and hence their use for radiographic examinations instead of iodinated contrast media has been advocated in patients with history of serious adverse reactions to iodinated contrast media and in patients who shall undergo imminent thyroid treatment with radioactive iodine, providing the renal function of these patients is normal. In patients with renal impairment, Gd-based contrast media should not be used for radiographic examinations as they can induce nephrotoxicity at the doses required to produce adequate radiographic enhancement.

It is also important to point out that Gd-based contrast agents have not been approved for radiographic examinations or intra-arterial injection and the doses approved for MRI examinations will provide only a limited enhancement of radiographic examinations.[16]

CONTRAST-ENHANCED MR IMAGING OF THE LIVER AND PANCREAS
Dow-Mu Koh

The IV contrast media currently available for MR imaging the liver can be classified into three broad categories. The types, actions and common side effects of these contrast media are summarized in Table 2.6 .

NON-SPECIFIC EXTRACELLULAR GADOLINIUM CHELATES
These contrast compounds distribute freely in the extracellular space and shorten the T1-relaxation time, resulting in T1 signal enhancement.

Dynamic MR imaging of the liver is performed after bolus IV contrast injection. The use of fat-saturated three-dimensional (3D) volume interpolated MR imaging (e.g. VIBE, THRIVE, FAME) allows high spatial resolution imaging of the entire liver to be acquired in a 20-second breath hold. Imaging is repeated in the arterial, portovenous and parenchymal phases of liver enhancement.

ARTERIAL PHASE
In the hepatic arterial phase (typically 20–30s after IV injection), both benign (e.g. focal nodular hyperplasia, adenoma and haemangiomas) and malignant lesions (e.g. hepatocellular carcinoma and metastases arising from neuroendocrine tumours) may appear hypervascular. Further differentiation depends on the pattern and rate of contrast medium change within the lesion. For example, haemangiomas typically demonstrate peripheral nodular enhancement[23] ( Fig. 2.2 ), while focal nodular hyperplasia shows intense uniform enhancement. Heterogeneous irregular enhancement is typical of hepatocellular carcinoma.

[img[f4-u1.0-B978-0-443-10163-2..50005-1..gr2.png]]

PORTOVENOUS PHASE
The portovenous phase occurs at 60–90s after IV contrast medium administration during which maximum liver parenchymal enhancement is achieved. This increases conspicuity of hypovascular (e.g. hypovascular metastases) and non-vascular (e.g. hepatic cysts) lesions.

During this period, benign lesions such as adenoma and focal nodular hyperplasia may fade to isointensity with the liver. Hypervascular metastases can also appear isointense. The pseudo-capsule and internal septae associated with hepatocellular carcinoma become more prominent.

INTERSTITIAL PHASE
This phase occurs from approximately 90s to 5 min after administration of IV contrast agent. Differential washout of contrast agent from the hepatic parenchyma and focal liver lesions aids lesion characterization.

In this phase, haemangiomas continue to enhance centripetally ( Fig. 2.2 ); adenomas and focal nodular hyperplasia are typically isointense with the liver, although late enhancement of the central scar of focal nodular hyperplasia may be visible[24]. Small hepatocellular carcinoma fades to contrast hypointensity. Delayed enhancement of cholangiocarcinoma becomes apparent.

HEPATOCYTE-SELECTIVE GADOLINIUM CHELATES
These are also administered intravenously as a bolus. However, a proportion of the contrast medium is selectively excreted by hepatocytes into the bile ducts. The percentage of hepatic uptake is 5 per cent for MultiHance and up to 50 per cent for Primovist.

Dynamic T1-weighted MR imaging is performed in the arterial, portal and interstitial phases after injection, similar to the nonspecific extracellular gadolinium contrast media. However, a delayed hepatic enhancement phase is observed ( Fig. 2.3 ). This occurs at 15–30 min for Primovist and approximately 1–3h for MultiHance.

[img[p.png]]

MultiHance has been used to distinguish between adenomas and focal nodular hyperplasia[25]. As adenomas do not contain normal biliary radicals, they appear hypointense at delayed T1-weighted imaging. Metastases (nonhepatocellular) and hepatocellular carcinoma (poorly functioning hepatocytes) also frequently appear hypointense. By comparison, focal nodular hyperplasia appears hyper- or isointense at delayed imaging. Primovist results in a much more intense parenchymal enhancement due to increased biliary excretion. However, its role in detection and characterization of focal liver lesions is still under investigation.

NON-GADOLINIUM CONTRAST MEDIA
Unlike the gadolinium-based contrast media, dynamic imaging is not performed with the use of these MRI agents. These contrast media are actively transported into liver and can be divided into two subcategories:
  	1   	Hepatocyte-selective manganese-based contrast medium. Teslascan (MNDPDP) is infused intravenously and its selective uptake by hepatocytes results in intense T1 liver signal enhancement at approximately 30 min, which persists for several hours.[26] There is normally complete clearance of contrast agent from the liver by 24h. The contrast medium is also taken up by the pancreas, adrenal glands and the pituitary.
  	2   	Cysts, haemangiomas and metastases from non-neuroendocrine primary tumours remain hypointense at T1-weighted imaging. There is variable enhancement of focal nodular hyperplasia, adenomas and hepatocellular carcinomas.[26] Metastases from neuroendocrine tumours also show enhancement by an uncertain mechanism. It has been found that delayed imaging at 24h may be useful for detection and characterization of colorectal hepatic metastases due to delayed clearance of contrast material surrounding the metastases[27] ( Fig. 2.4 ).

[img[f4-u1.0-B978-0-443-10163-2..50005-1..gr4.jpg]]

Reticulo-endothelial system targeted iron-based contrast media
These comprise small paramagnetic iron oxide particles that are administered intravenously. The iron accumulates within Kupffer cells in the normal liver, resulting in reduction in signal intensity of the liver at T2[*]-weighted gradient-echo imaging. Lesions containing Kupffer cells demonstrate signal reduction whereas lesions that are Kupffer cell depleted would remain high signal. Immediately following IV administration, the contrast agent also causes T1 relaxation and early T1-weighted imaging may be performed.

Iron oxide-based contrast media have been shown to increase the detection of small hepatic metastases prior to surgery.[28] ( Fig. 2.5 ). The contrast agent can also be used to demonstrate the extent of cholangiocarcinomas in the liver. However, its role in distinguishing between hepatocellular carcinoma, focal nodular hyperplasia and adenomas is less certain, as variable amounts of Kupffer cells in these lesions results in considerable overlap of their imaging appearances.

[img[f4-u1.0-B978-0-443-10163-2..50005-1..gr5.jpg]]

ONTRAST-ENHANCED MR IMAGING OF THE PANCREAS
An MR cholangio-pancreaticogram (MRCP) is usually performed in conjunction with MR imaging of the pancreas.

GADOLINIUM CONTRAST-ENHANCED IMAGING
Low molecular weight extracellular gadolinium chelates are most frequently used to characterize pancreatic lesions. Before contrast enhancement, unenhanced MR imaging should be carefully reviewed for focal signal abnormalities. In particular, fat-suppressed T1-weighted imaging is useful for identifying low signal intensity foci within the pancreas. T2-weighted imaging is helpful for visualizing high signal cystic lesions. Most solid pancreatic tumours appear hypointense or isointense on T1-weighted imaging, and isointense or mildly hyperintense on T2-weighted imaging.

Following bolus contrast injection, T1-weighted MR imaging is performed. The use of a fat-suppressed 3D volume interpolated T1-weighted imaging sequence, performed in repeated breath-holds, is particularly useful for detecting small focal lesions [29] [30] and for assessing vascular involvement.

In the arterial phase, there is enhancement of hypervascular neuroendocrine tumours of the pancreas. Both cystic and solid hypovascular pancreatic carcinomas are also well demarcated in the arterial phase ( Fig. 2.6 ). In the portovenous phase, hypervascular tumours usually fade to isointensity. Despite the superior contrast resolution of MR imaging, it is still controversial whether the technique is better than multi-detector CT for the detection and characterization of focal pancreatic lesions. However, there is gathering enthusiasm for using MR imaging to assess for tumour resectability.[31]

[img[f4-u1.0-B978-0-443-10163-2..50005-1..gr6.jpg]]

Mn-DPDP-ENHANCED MR IMAGING
Mn-DPDP is also excreted by the normal pancreatic parenchyma. Anecdotal reports have demonstrated the potential utility of the technique in detecting pancreatic carcinoma as relative hypointense lesions against the enhancing pancreas at T1-weighted imaging[4]. However, no studies have shown a clear advantage over the extracellular gadolinium chelates. Furthermore, the uptake of the contrast agent (Mn-DPDP) by neuroendocrine tumours can result in reduction of contrast between the tumour and the enhancing pancreatic tissue.

MRI CONTRAST AGENTS AND TECHNIQUES FOR CONTRAST-ENHANCED MR ANGIOGRAPHY
Giles Roditi

The flow-sensitive MRA techniques of time-of-flight and phase contrast imaging first developed in the 1980s rely on maximization of signal difference between flowing blood in the vessel lumen versus static vessel wall and surrounding tissues. These have now in large part been superseded by contrast-enhanced MRA (CE-MRA) techniques, wherein gadolinium-based paramagnetic contrast agents increase the blood pool signal by causing a profound shortening of the T1 relaxation time. A fast T1-weighted gradient-echo pulse sequence is used, specifically designed with short TR, short TE and RF spoiling to produce an image with low background signal while vascular contrast depends on T1 shortening due to the gadolinium rather than flow effects. Since CE-MRA is not susceptible to in-plane flow saturation, it can be performed in the plane of the vessel, increasing the practicable field of view and reducing acquisition time [32] [33]. Breath-hold techniques are desirable (i.e. a volume acquired in 30s or less) as they improve diagnostic accuracy for branch vessels. Most modern MRI scanners are now capable of imaging a clinically useful MRA volume in a comfortable breath-hold, and parallel imaging techniques are starting to allow time-resolved imaging.

CONCEPTS OF CONTRAST MEDIUM ADMINISTRATION
Delivery of contrast agents (Gd-CA) for CE-MRA by IV injection is more complex than for ‘simple’ MRI studies and necessitates an understanding of their mode of action and kinetics to maximize contrast effect and minimize artefacts. In order to provide contrast, a sufficient concentration of gadolinium contrast agent must be achieved in the vessels of interest to reduce the T1 of blood to less than 270 ms (equivalent to the T1 of fat for a 1.5 T system). The effect of a contrast agent on a tissue is given by the equation:

R' = R + rC

where R is the original relaxation rate (1/relaxation time), r is the agent's specific relaxivity rate, C its concentration and R' the resultant new relaxation rate (Figs 2.7 and 2.8 [7] [8]).

[img[f4-u1.0-B978-0-443-10163-2..50005-1..gr7.jpg]]

Blood has a T1 of 1200 ms, hence with a conventional extracellular fluid (ECF) gadolinium contrast agent with a T1-specific relaxivity rate of 4 mmol-1 s-1 a concentration of 1 mmol l-1 will reduce this to approximately 200 ms, and 2 mmol l-1 will reduce it to 100 ms – a useful contrast difference. Unfortunately, at concentrations above 5 mmol l-1 the T2[*] shortening effects of gadolinium come to predominate and signal on a T1w (T1-weighted) sequence rapidly declines. These T2 and T2[*] effects also act over a wider region than the T1 effects that are very local to the agent; this explains the artefacts seen from residual ‘neat’ venous contrast after arm injection, resulting in loss of signal in adjacent arteries on aortic arch and subclavian studies. To help combat this and ensure efficient contrast use, IV contrast should be immediately flushed with a suitable volume of saline (e.g. 30 ml) at the same injection rate to move the bolus into the central venous pool, where it is propelled on to the right heart, maximizing efficiency of the dose. To further minimize these effects, it is recommended that contrast agents are administered via a vein in the right arm since any artefact from contrast in the left brachiocephalic vein (where flow tends to be sluggish) across the origins of the aortic arch branches may seriously degrade their depiction. A right arm injection is also beneficial even when studying territories remote from the arch, since the route is shorter with less contrast travel time variability than with left arm intravenous injections ( Fig. 2.9 ). Contrast agent injection for MRA studies is simplified by the use of an MRI compatible pump injector ensuring reproducibility while allowing medical and radiographic staff to remain in the MRI control room. The phenomenon of signal abolition at high agent concentrations also informs the use of contrast for ‘direct’ MR venography when injecting into the relevant veins, e.g. pedal injection for a lower limb study or for arteriovenous fistula studies. For this, an injection of diluted contrast is required and this also applies for direct MR arteriography studies.

Peak arterial blood pool contrast concentration after IV injection is proportional to contrast agent flux (which is the product of agent concentration and rate of injection) and inversely proportional to cardiac output. The effect of differing cardiac output is lessened at injection rates over 1 ml s-1 and so on modern systems, apart from trying to minimize patient anxiety, cardiac output is generally not directly manipulated (reduced) and varying the rate of contrast administration is used to maximize contrast efficacy. ‘Double dose’ (0.2 mmol kg-1) is usually employed for single station examinations (e.g. carotid, thoracic aortic, renal arteries etc.) and to maximize efficient use of contrast, the bolus should last for the duration of the CE-MRA sequence covering central and peripheral k-space data acquisition. For example, for a typical 20-second breath-hold sequence then 30 ml of a 0.5 mol l-1 ECF agent could be injected at a rate of 1.5 ml s-1. In practice somewhat higher rates are used as the bolus injected peripherally becomes ‘stretched’ as it passes through the pulmonary circulation and heart, hence rates of 2.0–2.5 ml s-1 are used.

For a 1.0 mol l-1 agent (such as gadobutrol) half the volume is required for the same gadolinium flux at any given rate. If this reduced volume is injected at the same rate as a 0.5 mol l-1 medium, this will result in a higher intra-arterial concentration at the bolus peak. However, this may adversely affect image quality if the bolus no longer covers the whole of the acquisition in terms of peripheral k-space lines, hence a 30 per cent lower rate is recommended. Optimum timing of the contrast bolus to scan acquisition is required to ensure that the peak concentration in the vessel of interest, and therefore the most profound T1 shortening of blood, coincides with the collection of the contrast defining central lines of k-space data. Most MRI systems are now supplied with automated triggering and/or fluoroscopic monitoring simplifying scan performance with centrically encoded pulse sequences acquiring low frequency contrast defining k-space profiles at the beginning of the scan[34].

These doses have generally been shown to be safe, particularly in terms of nephrotoxicity, even in renal impairment [35] [36] though the potential of some agents (Gadodiamide and Gadoversetamide) to interfere with colorimetric assays for serum calcium may result in a spurious ‘pseudohypocalcaemia’ and this phenomenon is potentiated/prolonged in patients with chronic kidney disease. However, the recent reports of an association between Gd-CA (Contrast Agent) use in patients with severe renal impairment (particularly those on dialysis) and the subsequent development of nephrogenic systemic fibrosis (NSF) introduces a note of caution. Whether gadolinium is the specific and sole necessary factor triggering NSF is not yet resolved at the time of writing. Certainly most patients with renal impairment administered Gd-CA do not develop the disorder with an incidence of 3 – 5% in dialysis patients administered Gd-CA.[37] While the exact relationship and any causality are not yet determined this is a particularly important issue for CE-MRA, which has hitherto been embraced as a safe means of investigation in these patients who are prone to vascular problems. This is especially so since there appears to be a dose-response relationship with development of NSF more likely with high dose examinations. Despite no conclusive evidence of protection, the current ACR guidelines advise dialysis where practicable in such patients promptly after contrast administration. [38] [39] (Please see preceding section by Thomsen and Marcos).

PERIPHERAL RUN-OFF AND WHOLE-BODY CE-MRA
CE-MRA is not restricted to a single station field of view with the use of stepping table techniques (analogous to those used in conventional angiography) and that allow scanning of the lower body arterial tree from abdominal aorta to feet[40] with extended tables and whole body MRA. Mask images are used to allow subtraction of regions of high signal pre-contrast (such as subcutaneous and marrow fat) from the post-contrast images. Image subtraction is particularly crucial for the tibial station as the image scaling effect of high signal due to contrast agent is negligible within small crural arteries while both the subcutaneous and marrow fat are in close proximity to the vessels.

Whereas a total dose of 0.2 mmol kg-1 standard (0.5 mol l-1) ECF gadolinium contrast is used for single station studies, this is increased to 0.3 mmol kg-1 for multiple-station CE-MRA of the aorta and lower limb arterial run-off. Biphasic injection protocols are also recommended, for example a rate of 1.5 ml s-1 for the first phase dropping to 0.8 ml s-1 for the second phase. This second phase lower rate helps to prolong the bolus and also reduce venous enhancement.

The main problems with peripheral run-off CE-MRA revolve around the classic MRI trade-offs of spatial resolution versus signal-to-noise ratio (SNR) versus image acquisition time. There is also the drawback of so-called ‘venous contamination’ whereby the crural arteries may be obscured by early enhancement of calf veins. High spatial resolution is particularly critical for the small tibial arteries (equating to longer scan times) yet this is also the region where venous contamination is most likely, particularly in patients with Fontaine class III and IV critical ischaemia who demonstrate rapid arteriovenous shunting bypassing tissue diffusion/extraction. IV contrast agent travel time variability depends on contrast passage from the venous compartment through the pulmonary circulation and heart. Once in the abdominal aorta, the leading edge of the contrast bolus travels at approximately 6s per station down the lower limbs (groin, popliteal, ankle). However, the arterial-venous transit times at the calf vary depending on disease status with much more rapid transit in those with critical ischaemia and/or cellulitis compared to simple claudication.[41] This has led to different strategies to optimize tibial arterial imaging.
  	1   	Imaging the crural arteries first with a dedicated injection of contrast and a centric-encoded sequence designed for venous suppression, e.g. elliptic centric, CENTRA. Aortoiliac and femoral levels are subsequently imaged with standard stepping table technique and a second contrast injection.
  	2   	The imaging time window at the calf can be prolonged by venous compression techniques, whereby compression cuffs around the thighs inflated to subdiastolic pressures prolong arterial and venous transit times and also increase the venous volume of dilution (reducing contrast conspicuity in the venous compartment).
        3   	Another strategy is to image the calf vessels first with either fast thick slab 2D subtraction imaging or 3D time-resolved imaging, followed by a standard bolus chase 3D acquisition for the aortoiliac and femoropopliteal stations.
  	4   	The use of parallel imaging and phased array coils at all stations with variable acquisition parameters can allow tailored and more rapid bolus chase such that venous contamination is minimized, e.g. following the aortoiliac station, the femoral segment is rapidly acquired with lower resolution and then highest resolution for the tibial station.[42]

These techniques listed are not mutually exclusive and the strategy used will depend upon scanner capability, coil availability and operator experience/preference.

BLOOD POOL CONTRAST AGENTS
Blood pool contrast agents (BPCAs – also known as persistent vascular agents) are specifically designed for vascular imaging through persistence in the intravascular space without the passage to interstitial extracellular fluid spaces that is the hallmark of conventional ECF agents (i.e. their vascular half-life is much greater than ECF agents). Blood pool persistence is achieved either by high molecular weight preventing diffusion through the capillaries or through protein binding to serum albumin, which has the same effect. BPCAs are either based on gadolinium compounds or ultrasmall paramagnetic iron oxides (USPIOs) though these latter iron based agents are as yet not commercially available for blood pool imaging.

Gadobenate dimeglumine is predominantly an ECF fluid agent but its weak protein interaction provides higher relaxivity compared with standard 0.5 mol l-1 ECF agents and this weak (but still positive) protein binding also helps prolong blood pool residency. This results in a relatively higher signal intensity peak and longer duration of enhancement compared with standard agents for similar dose and injection rates. The safety profile of gadobenate dimeglumine is similar to the conventional ECF agents.

Gadofosveset has been specifically designed for CE-MRA as a blood pool agent with strong protein binding to albumin, up to 20 molecules of gadofosveset can bind to one molecule of albumin but in clinically used doses it is usually only one or two per albumin molecule. Binding to albumin is rapid with 75 per cent bound 1 min after IV injection, reaching a steady state with approximately 88 per cent bound. The high protein binding has two effects; firstly it markedly increases relaxivity (hence the lower doses/concentrations required) and secondly it results in the agent effectively being confined to the vascular space with little passage to extracellular fluid spaces and an increased half-life in the blood pool. This binding is reversible and the agent is ultimately excreted unchanged by the kidneys through glomerular filtration; it is also eliminated by routine renal dialysis, with 92 per cent cleared after three sessions.

Gadofosveset has a safety profile similar to other gadolinium contrast compounds with a low rate of adverse reactions consisting of transient mild tingling sensations (particularly in the perineum), pruritus, flushing, headache and taste perversion. One possible serious adverse anaphylactoid event to gadofosveset was reported, resolving within 5 min. There is apparently no potential nephrotoxicity at clinically used doses nor interference with proper binding drugs such as warfarin.

As a commercial BPCA for CE-MRA, gadofosveset provides currently unique properties, particularly through the very prolonged time window available for imaging as with a T ½ of 28 min (compared to 90s for Gad-DTPA) diagnostic imaging can be performed up to 1 h post injection. Arterial first-pass CE-MRA can be performed just as with the ECF agents, perhaps even with greater signal through the increased specific relaxivity of the agent. It is the possibilities of delayed imaging performed with high intravascular signal that are intriguing since this is not limited to the short time of a first-pass bolus and can therefore be performed at very high spatial resolution. Steady state imaging can start from 2 min after injection up to approximately 1 h. Imaging should be designed for high spatial resolution, ideally to create an isotropic dataset to allow for reformatting of images in any plane. In order to obtain best contrast, the sequence used should be optimised with a reduced flip angle of 20°–25°, increased TR of 10–12 msec, TE of 2–4 msec and appropriately reduced bandwidth (increased water-fat shift). Since imaging is no longer confined to a brief period of contrast passage, these high spatial resolution sequences can be used with phase oversampling for wrap suppression, increased signal averages for improved SNR etc. However, since these will now be longer sequences than usual MRA, they should be used with respiratory gating and/or cardiac pulsatility compensation in appropriate body regions (Fig. 2.10). For imaging of systemic and portal venous disorders, as well as arteriovenous malformations, this prolonged time window and excellent contrast are a major advantage over the rapidly excreted conventional agents.

Gadofosveset or similar products may well become the optimum agent in suspected pulmonary embolism for it will demonstrate both the pulmonary areterial tree in the early phase and the pelvic and leg veins (where the thrombus may arise) in the later phase of the same examination.

The use of blood pool agents in coronary MRA may boost signal from the coronary vessels with respect to myocardium and might dramatically improve image quality. With its high relaxivity and long imaging window gadofosveset may well more reliably detect endoleak after aortic stent grafting than conventional imaging with ECF gadolinium agents and CT techniques. It is also thought that the use of a blood pool agent may allow the detection and localization of occult gastrointestinal haemorrhage.

The downside to the use of a blood pool agent is that during later phase imaging, arteries and veins will now be equally conspicuous. Software programs are being developed to isolate arterial structures from the veins though these are currently not commercially available. An interesting further observation with gadofosveset is that late imaging reveals contrast uptake in atherosclerotic plaque: no doubt this will provide fertile ground for further research as regards plaque activity and morphology.
Ultrasound is an important technique for tomographic imaging of soft tissues. It provides images in real-time and so can also be used to interrogate the movement of structures such as cardiac valves, interactive guidance of biopsies and drainage procedures and, using the Doppler mode, the patterns of blood flow in both large and small vessels. Although ultrasound contrast agents are now available, images are generally obtained without them and thus are not dependent on organ function. As far as is known, ultrasound used at diagnostic intensities is harmless and it can be used without concern for injury to sensitive tissues such as the eye and the developing fetus. Ultrasound technology continues to improve; even low-end and portable systems are now digital and new transducer and beam-forming technologies allow higher frequencies to be used at depth.

Although ultrasound has found major applications in the heart, abdomen and pelvis, as well as in the neck, breast, peripheries and neonatal brain, perhaps its most important clinical impact is in obstetrics, where the combination of safety and tomographic imaging of the fetus has rendered it indispensable.

The parts of the body that can be imaged with ultrasound are, however, limited because it does not readily cross a tissue–gas or tissue–bone boundary, so they and deeper-lying structures cannot be studied. Thus, ultrasound is not generally useful for the lungs and is difficult to use in the head—except in the neonate, when the open fontanelles provides an excellent ‘window’. In other areas, overcoming the barrier caused by the bony skeleton and gas-containing viscera requires technical expertise. Ultrasound is also subject to many artefactual signals which complicate interpretation and add to the operator skills required.

Patients readily accept an ultrasound examination because the procedure requires only light pressure on the skin and preparation is minimal: bladder filling is required for pelvic ultrasound and fasting is necessary for the gallbladder, but otherwise the patient may be examined with this technique as and when convenient, a major advantage for emergency uses. In addition, mobile ultrasound systems that can be taken to the bedside, to intensive care and into the operating room are widely available.

NATURE OF ULTRASOUND
Ultrasound is simply sound with a frequency above the limits of human hearing. In most diagnostic applications, frequencies in the 2–20MHz (megahertz = million cycles per second) range are used, corresponding to wavelengths of 1–0.1 mm in tissue.

Ultrasonic transducers
Ultrasound is generated by piezoelectric materials, which have the property of changing thickness when a voltage is applied across them. Lead zirconate titanate (PZT) is the most widely used. Its piezoelectric effect derives from movements of the heavy charged lead atom that is loosely bound within a complex crystal: when an electrical field is applied, the atom moves and distorts the crystal. PZT is a ceramic that is cast as a thin plate that may be disc shaped or, more usually, is formed into a strip that is then sliced into several hundred tiny elements as an array, with metal electrodes on the two surfaces. It is polarized by heating it above a critical temperature and then allowing it to cool in an electric field. When electrically pulsed, the crystal rings at a resonant frequency that is mainly determined by its thickness. Higher frequency crystals are thinner and thus more difficult to manufacture. The piezoelectric effect is reversible, so the same or a similar crystal is used as the receiver to produce small electrical signals when struck by an ultrasound wave.

The crystal is mounted in a conveniently shaped holder, which contains the electrodes and any associated electronics, as well as the lenses and matching layers required to improve the beam shape. The whole assembly is known as the probe, transducer or head.

An interesting new approach to designing transducers relies on photo etching, as used in semiconductor construction, to produce arrays of capacitance elements in which a pair of electrodes is separated by a small air gap; these capacitative microfabricated ultrasound transducers (CMUTs) are easily mass produced and integration of the associated electronics is simple (MEMS and Nanotechnology Clearinghouse website: www.memsnet.org/mems/what-is.html).

Propagation in tissue
Ultrasound travels through tissue as a beam that is usually focused to improve lateral resolution. It propagates as a sequence of compression and rarefaction waves, transmitted by the elastic forces between adjacent tissue particles. The particles move in the same direction as the wave—thus ultrasound is a longitudinal wave in comparison to the transverse wave that occurs at the surface of water where the particles move up and down as the wave travels horizontally. The frequency of the oscillations is inversely proportional to the wavelength (f = c/λ, where f is frequency, c is the velocity of ultrasound and λ is the wavelength).

The way in which the ultrasound wave is transmitted varies with the strength of the elastic forces between adjacent particles (which relates to the elasticity of the tissue and thus to the velocity of ultrasound) and the masses of the particles (which determine density). These two factors determine the acoustic impedance (Z) of the tissue (Z ≅ ρc, where ρ is density and c is the velocity of ultrasound). When the particles are heavy, a given amount of energy is transmitted with small movements of the particles: when they are light, larger excursions are involved; however, the actual distance a particle is moved at diagnostic ultrasound intensities is only a few Ångstroms. In clinical practice, since the velocity of ultrasound in tissue is almost constant (at 1540 m s-1), changes in impedance are mainly attributable to differences in density.

The constant speed of ultrasound in soft tissues allows the depth of reflecting structures to be calculated by measuring the delay in the return of echoes after the ultrasound pulse has been transmitted. This is the essence of the pulse-echo method used in both ultrasound imaging and most forms of Doppler ultrasound. The position of reflecting structures across the image is determined by the direction in which the ultrasound beam is transmitted.

Attenuation
Provided that the constituent particles of a tissue are small enough to move as a single entity, the acoustical vibrations are transmitted in an orderly and efficient manner. However, when very large molecules are involved, the vibrations become disorganized, one part of the molecule responding more or less than another. While coherent vibration is what we know as sound, chaotic vibration is heat. This loss of coherence, the most important cause of dissipation of ultrasound energy, is known as absorption and is approximately proportional to the concentration of large molecules which correlates with viscosity.

Absorption is also highly dependent on the ultrasound frequency, higher frequencies being more strongly absorbed. For average soft tissues, the loss amounts to approximately 1dB per cm tissue depth for each MHz. Thus, when using a 3MHz probe, for every 2 cm of tissue penetration there will be a loss of 6dB, which is a halving of the signal's strength. The noise floor (produced by random vibrations in the tissue and the transducer as well as by imperfections in the scanner electronics) typically lies some 60–90dB below the peak signal, so the penetration of such a probe would be limited to about 20 cm depth.

Ultrasound energy is also lost to the receiving transducer if it is reflected or refracted away from the returning line of sight or if the beam diverges. The total loss from all these mechanisms is called attenuation.

High-frequency ultrasound gives good resolution because of its short wavelength, but the rapid attenuation of high-frequency ultrasound by tissue is the limiting factor to the maximum frequency that can be used in any given clinical application. Frequencies as high as 20MHz can be used when only a few millimetres of tissue are to be traversed, such as for imaging the eye and skin, and for intravascular ultrasound (IVUS). For superficial tissues, 10–15MHz is appropriate. For the heart, abdomen and second and third trimester obstetrics, 3–7MHz is optimal; however, for some difficult applications, such as the abdomen in obese subjects, and for transcranial studies (most of which use Doppler), it is necessary to resort to 1 or 2MHz transducers, with consequent reduction in spatial resolution.

This frequency limitation can be mitigated by the use of coded transmit pulses, which impose a signature on the pulse (e.g. by making its frequency rise during the pulse, so called chirp encoding); long pulses are used and the scanner contracts them back to a short pulse using a matched decoding filter. Thus, the spatial resolution is regained but more acoustic energy can be transmitted without an increase in acoustic pressure so that the signal-to-noise ratio is improved.

Compensation for the loss of signal with depth is achieved by applying progressively increasing amplification (gain) to later echoes using a time-varying amplifier that is triggered when each ultrasound pulse is sent. This is the time gain compensation (TGC), an important user control that must be set to equalize the image brightness for superficial and deep structures. Many modern ultrasound machines incorporate automatic TGC software that simplifies image optimization.

This trade-off between depth and resolution is the chief reason for the development of intracavitary probes. Examples are transrectal probes for the prostate and transvaginal probes for gynaecology and early obstetrics, as well as transoesophageal probes for echocardiography. These can operate at 7–15MHz to give good quality images and, as the barriers caused by impenetrable overlying structures are obviated, high-quality images are reliably achieved. Intracavitary probes can be combined with endoscopes for transoesophageal and transgastric data acquisition to evaluate the submucosal and deeper layers of the viscera and to provide high-resolution images of adjacent structures such as regional lymph nodes.

Reflection
The other important ultrasonic interaction with tissue is reflection. Some of the transmitted energy is reflected whenever the beam crosses an interface where the transmission properties change, the proportion depending on the degree of impedance mismatch (change of Z). The phenomenon is similar to that occurring in a rope that is fixed at one end and made to oscillate by shaking the free end up and down: provided the rope is of uniform construction, waves travel along it until they die out or reach the fixed end. However, if a part of the rope is thicker or more rigid, then the waves are partly reflected back when they reach this ‘obstruction’.

The intensity of the reflection mainly depends on the degree of change in the tissue density. Ultrasound that is not reflected passes through and is available for imaging deeper tissues. Only a small fraction (2–10%) is reflected at each soft tissue interface but almost total reflection occurs at tissue–gas interfaces, and some two-thirds of the incident ultrasound is reflected at a tissue–bone or tissue–calculus interface so that an acoustic ‘shadow’ is produced deep to these surfaces. They are essentially opaque to ultrasound, which therefore cannot be used to interrogate aerated lung, and imaging through bone is difficult.

Two main types of echo are encountered clinically, depending on the structure of the reflecting surface ( Table 3.1 ). Where the interface is smooth compared with the ultrasonic wavelength (i.e. the surface is flat over an extent of several millimetres), the reflected wave obeys Snell's law just as in optics and is reflected at an angle equal to the angle of incidence. By analogy, these echoes are known as specular or mirror-like echoes. In the usual arrangement for ultrasound imaging, when the transducer is used both for generation and reception of the ultrasound, only those smooth surfaces that lie at right angles to the sound beam return specular echoes. The directed reflection means that the echo is of high intensity: strength and directionality are the cardinal features of these echoes from flat surfaces. They arise from the linings of hollow viscera and blood vessels, from the valves of the heart, from organ capsules and fascial planes, from the skin and from gas and bone surfaces.


Table 3.1   -- ECHO-PRODUCING MECHANISMS
Specular: mirror-like reflections from flat surfaces	Strong, directional echoes
Scattered: interference patterns from small parenchymal discontinuities	Weak, nondirectional echoes

When the irregularities in the surface are similar in size as the ultrasound wavelength itself, i.e. 0.01–1 mm, a different mechanism, known as scattering, produces echoes; here each small interface (e.g. a lobule of an organ, arterioles, venules, etc.) is vibrated by the mechanical shock it has received from the incident ultrasound pulse. The energy is re-radiated more or less equally in all directions, so that each discontinuity behaves as an isolated point source of ultrasound. The echoes are isotropic and potentially detectable from any direction but, because the energy is distributed across the surface of an expanding sphere, the signal received by the transducer from any single vibrating particle is extremely weak and, in practice, is only detectable when several wavelets from adjacent particles happen to be superimposed and produce an additive effect. Low intensity and detectability from any angle are the cardinal features of these scattered echoes. They arise from soft tissue parenchyma and thus are important diagnostically. The texture in the resulting image is an interference pattern, known as speckle and, although deterministic, is not a one-to-one representation of the histological reality. This is why tissues of very different composition (e.g. liver and spleen) can produce indistinguishable echo textures. Many body tissues actually display properties intermediate between specular and scattered echoes.

If the beam is sent into a tissue region from several angles and the echoes combined, the speckle pattern is reduced and specular echoes are more likely to be picked up. This approach, known as compounding, can improve image contrast and is widely used in high-end machines.

Ultrasound is generally considered to be conducted in a linear manner whereby the waveform of the pulse is preserved with depth. In fact, this is not quite true and nonlinear propagation is an important phenomenon in which the wave of the original pulse from the transducer becomes distorted so that it comes to contain higher frequency components or harmonics. This occurs because the speed of sound increases with increasing density of the conducting medium so that the compression part of the cycle travels slightly faster than the rarefaction part; this distorts the wave much the same way that an ocean wave builds and breaks as it approaches the shore. The development of these harmonics depends on the sound intensity: higher acoustic powers produce stronger harmonics and therefore they are weak in the parts of the sound beam away from the central, desired portion. They are also weak for the first few millimetres of tissue depth because they take a few cycles to build up. These facts have been exploited in machines that use filters to select for the harmonics in the returning echoes by transmitting at, say, 1.5MHz and tuning the receiver to 3MHz to remove the fundamental echoes. In doing so, the beam aberrations from side lobes and from reverberations in the superficial tissue layers are suppressed (see below, Resolution). The tissue harmonic image is cleaner with higher contrast: this has been especially useful in echocardiography and in abdominal data acquisition

[img[f4-u1.0-B978-0-443-10163-2..50006-3..gr1.jpg]]

MAGING METHODS
Pulse-echo method
In conventional pulse-echo ultrasound imaging, signals are displayed according to the depth calculated from the time elapsed between transmission and receipt of the echoes, using the speed of sound in tissue to convert from time to depth; the same principle is used in radar and sonar.

In the simplest system, only the depth of the interface is determined. It is displayed as a vertical deflection on a monitor and is known as A-mode (A for amplitude). It has one spatial dimension and the strength of the echoes is indicated by the height of the deflection 

[img[f4-u1.0-B978-0-443-10163-2..50006-3..gr2.jpg]]

If the transmitted pulse is repeated rapidly, then the position and intensity of any interfaces that arise from moving structures change with time. A simple way to display these changes is to modulate the intensity of the spot on the monitor in proportion to the intensity of the echoes and then to sweep the line of echoes across the screen. The resultant trace shows depth versus time and is known as an M-mode display (M for movement). It is especially useful in echocardiography for evaluating the rapid movements of valve leaflets

[img[f4-u1.0-B978-0-443-10163-2..50006-3..gr3.jpg]]

A two-dimensional tomographic ultrasound image is formed by sweeping the beam through a slice of tissue and mapping the echogenicity of the reflectors as shades of grey to form a B-mode image (B for brightness), also known as a grey scale display. This is the commonest mode used for ultrasound imaging. While the depth of the reflectors is determined by the delay in the return of the echoes to the transducer (the pulse-echo principle), their lateral position is determined by the direction in which the ultrasound beam was sent. Combining a series of B-mode images swept through a volume provides a three-dimensional display and, if the sweeping is sufficiently rapid, a real-time 3D display can be achieved, known as 4D. This has proved to be valuable in echocardiography and obstetrics.

Beam steering
The direction in which the beam is sent can be determined mechanically or electronically. Mechanical steering systems are used in intracavitary examinations where their small size is an advantage. They use a simple, single crystal transducer, which is mechanically swept through an arc (typically of 360 degrees) by spinning it on a wheel ( Fig. 3.4 ). The resulting image has a circular shape, with the transducer itself at the centre and the tissues arranged around it, with the mucosa or intima closest to the transducer. Electronic sector systems (also known as phased arrays) have replaced mechanical systems for other applications. The beam direction is controlled by building up interference patterns between the waves transmitted from an array of a large number of small transducer elements. The usual arrangement consists of numerous PZT crystals (512 in state-of-the-art systems), each 1 mm or less in width and 5–10 mm in length, stacked up in a block. Each has separate electrical contacts and the pulses to each element are serially delayed from one end of the array to the other. These minute differences in timing occur within the short time needed to form an individual pulse and they produce interference patterns in which the troughs and peaks of the pressure waves add where they coincide and subtract where they are out of phase (hence the title ‘phased array’) ( Fig. 3.5 ). This results in a beam that is angled away from the straight-ahead direction. For the next pulse, a slightly different set of delays is applied to adjust the steering.

During receipt of the returning echoes, the electrical signals from the individual elements are delayed before they are summed in the beam former, exploiting the same summing and cancelling approach; the resulting signal is the electronic equivalent of angling the transducer face in the required direction. Although the concept is easy to understand, the underlying mathematics is complex and its implementation generally requires dedicated hardware, although software emulations have been developed so that beam forming can be performed on a PC, thus opening the way to cheaper and more flexible scanners. The resulting image has a triangular or sector shape, which has the important practical advantage of requiring only a small skin-contact area (or ‘footprint’), although it provides only a limited display of the superficial tissues. It is widely used in echocardiography.

The operation of electronic linear array transducers is a little simpler. They are made longer than phased arrays and the beam is moved across the scanned plane by firing the elements in groups, starting from one end of the array and stepping along to the other ( Fig. 3.6 ). This produces an image with a rectangular shape, best suited for the superficial structures that are of prime interest in small parts imaging ( Fig. 3.7 ). In a simple variant, the linear array is curved so that the field of view is trapezoidal, as with a sector scanner, but with a longer skin line. This compromise is particularly useful when both superficial and deeper structures need to be imaged, for example in obstetrics ( Fig. 3.8 ).

An important limit to the rate at which ultrasound information can be acquired is set by its speed in tissue (average in soft tissue, 1540 m s-1). It is necessary to wait for each pulse to have faded away before the next is transmitted because, if the second pulse is sent too early, the last echoes from the first overlap early echoes from the second and are falsely registered on the image as superficial structures. To avoid this range ambiguity artefact, the pulse repetition frequency (PRF) must allow a delay of at least the time taken for the most distant echoes to return. In practice, this limits the PRF to about 1000 pulses per second. The clinical application dictates the way these pulses are distributed in time and space. They are spread apart and the field of view restricted to maximize the frame rate for echocardiography but the sacrifice in spatial resolution and the small image size are not ideal for general applications in which image quality is paramount. Here, the low frame rate is generally less of a sacrifice, so a high line density and wider field of view provide a reasonable compromise.

Resolution
Ultrasound resolution must be considered separately for the two dimensions, along and across the beam. Depth or range resolution is simply determined by the length of the ultrasound pulse, which is kept as short as possible, usually about two wavelengths in length; this equates to a shorter pulse if higher frequencies can be used and this is the main reason for the improved resolution of high-frequency systems.

Lateral resolution, in contradistinction, depends on the width of the ultrasound beam. This is mainly controlled by mechanical or electronic lenses.

The ultrasound emitted from a point source spreads in a hemisphere; however, as the source is enlarged, it forms a beam with near-parallel sides for several centimetres before the beam diverges again ( Fig. 3.9 ). The changeover is the transition between the near (Fresnel) and far (Frauenhofer) fields. In fact, it is the point beyond which the ultrasound waves from the edge of the transducer arrive less than a wavelength later than those from the transducer's centre, and this is why larger aperture transducers have a longer near field. The beam is actually formed by the same interference effects that are exploited to steer the beam in electronic transducers and which occur because the compression and rarefaction phases of the ultrasound pulse summate in the direction of the beam but cancel elsewhere.

Adding a converging lens (usually a curved layer of plastic bonded to the front of the piezo material), or simply shaping the transducer face into a shallow dish, acts to narrow the beam. This can be thought of as working in the same way as an optical lens, i.e. by beam refraction, but a more useful concept is based on the fact that the lens conducts ultrasound more rapidly than tissue, so that waves emanating from the transducer edge are fractionally ahead of those from the centre as they enter the body. Thus, interference patterns are set up across the sound field that emphasize the centre region of the ultrasound beam and cancel ultrasound waves that would otherwise spread laterally.

The same effect can be produced with a multi-element array by sending the transmit pulses to the outer elements fractionally ahead of those to more central elements; this is the electronic equivalent of shaping the transducer surface into a dish ( Fig. 3.10 ). Focusing also occurs on receipt of the echoes, in a reciprocal fashion. While electronic focusing is complex, it confers two benefits. First, the focal position can be altered by changing the delays within the transmit pulse so that the probe can be optimized for each clinical situation. Secondly, on receipt of the echoes, the focus can be set close to the transducer initially (to optimize resolution of superficial tissues) and then be progressively refocused deeper into the body to track the train of echoes returning from deeper interfaces. This dynamic focusing optimizes resolution over the entire depth of the image.

Tight focusing of the ultrasound beam has the undesired effect of accentuating its divergence in the far field, so that the beam is only optimal over a short depth ( Fig. 3.9d ). While such a transducer would be appropriate for structures where only a narrow strip of tissue is of interest (e.g. the eye), generally a better compromise is to use weak focusing together with as large an aperture as can reasonably be maintained in contact with the skin.

In practice, the ultrasound beam achieved is far from perfect ( Fig. 3.11 ). Not only is the optimum beam width achieved over only a relatively short focal depth, but its profile also leads to smearing of signals from strong reflectors because they are detected from some distance off-axis ( Fig. 3.12 ). In addition, any real beam has side lobes that are emitted at steep angles from the main beam so that unwanted echoes may be received from interfaces that lie a long way off-axis. These signals further smear the image, particularly when strong reflectors such as gas bubbles lie in their direction. These limitations also apply across the imaging plane, so that out-of-plane reflectors may also interfere. Minimizing the loss of spatial and contrast resolution that results from these deficiencies is a major emphasis of the art and science of transducer design and is an area in which marked progress continues to be made (e.g. by using tissue harmonic imaging).

ARTEFACTS: CLINICAL INSIGHTS INTO ULTRASOUND PHYSICS
The assumptions made in generating ultrasound images are that ultrasound travels at a constant speed in tissue and that the beam is ‘well behaved’. Artefacts arise whenever these principles are violated.

The speed of ultrasound varies by only a few per cent in watery soft tissues but fat conducts approximately 20% more slowly. This means that the depth of echoes arising beyond large fatty regions is overestimated so that they are depicted as being further away from the skin than they actually are. It may be seen as a shelf in the diaphragm behind a fatty tumour in the liver (e.g. a lipoma). An even more dramatic illustration of this same artefact occurs with silicone implants, in which the ultrasound velocity is about half that of soft tissue ( Fig. 3.13 ). The chest wall deep to a breast prosthesis, for example, can appear to be twice its true distance from the skin.

The difference between the velocity in adipose and watery tissues can refract the ultrasound beam so that it deviates from its straight-line path. A gross version of this artefact occurs in the hypogastrium, where the fatty wedge lying between the lower ends of the two rectus abdominis muscles acts like an optical prism. The refraction of the ultrasound beam in transverse suprapubic images can produce double outlines of pelvic structures and even, in extreme cases, complete double images. This artefact may well be the cause of the ‘vanishing twin’ phenomenon (when one of a pair of twin embryos disappears early in pregnancy), described when ultrasound was first introduced in obstetrics.

More generally, the different velocities at multiple small tissue–fat interfaces produce minor deviations of the ultrasound beam that defocus and disperse it. The clinical effect of this is loss of contrast, the image appearing noisy and blurred ( Fig. 3.14 ). The problem is worse when there is marked admixture of fatty and watery tissues, as may occur in fatty infiltration of muscle, a feature that may explain why poor images may be obtained from an out-of-training athlete. The degradation of ultrasound images and its variability from patient to patient are two of the most important limitations to the diagnostic use of ultrasound: strenuous efforts are being made by equipment manufacturers to investigate and minimize these problems. The use of tissue harmonics has greatly reduced this interpatient variability and thereby the number of unsuccessful examinations.

[img[f4-u1.0-B978-0-443-10163-2..50006-3..gr14.jpg]]

A ‘well-behaved’ beam would be laser-thin and travel directly through the tissues to and from the transducer. The real-life situation is far from this ideal: the effects of beam spreading, side lobes, refraction and diffraction on spatial and contrast resolution have been mentioned. Multiple reflections are another common artefact that produces a series of parallel false images of flat interfaces that happen to lie parallel to the skin. They are the result of repeated reflections of the incident ultrasound pulse between the transducer and the flat surface or between two such surfaces within the body. A common example is seen as parallel lines deep to the superficial fascia produced by the ultrasound being reflected from the transducer back into the tissue a second time. Similar linear artefacts are commonly seen in the superficial portions of the lumen of viscera such as the bladder and gallbladder and in blood vessels. The difficulty in measuring the thickness of the superficial intima–media layer of the carotid artery results from this artefact ( Fig. 3.15 ). Rereflection from the transducer surface is reduced by applying matching layers which make it less reflective by reducing the impedance mismatch between the transducer and the skin, resulting in much less noisy images.

[img[f4-u1.0-B978-0-443-10163-2..50006-3..gr15.jpg]]

A similar situation is produced by the closely packed bubbles in the foam that may occur in bowel gas. Here, the intense reflections repeat in near-random sequence, depending on the precise arrangement of the bubbles, to produce a train of echoes that fades over a few millimetres as the ultrasound energy dissipates. On the screen, a bright streak, the ‘comet tail’ artefact, is seen extending for a few millimetres deep to the gas. The same effect may occur deep to foci of calcification and behind metallic or plastic foreign bodies.

Where a flat reflector lies at an angle to the ultrasound beam, ultrasound may be sent back into the tissue at an angle and then be reflected back from any interface it encounters. These echoes retrace the incident pathway and are picked up by the transducer, to be depicted as though lying deep to the angled reflector, exactly as objects are seen ‘through’ an optical mirror. This ‘mirror image’ artefact is commonly encountered at the air–pleura interface above the diaphragm: the echoes apparently above the diaphragm actually arise from the hepatic or splenic parenchyma ( Fig. 3.16 ). They are quite different from the appearance of the lung examined intercostally when a very strong linear echo is seen, usually followed by strong reverberation echoes that fade over a few millimetres.

[img[f4-u1.0-B978-0-443-10163-2..50006-3..gr16.jpg]]

NTERPRETATIVE PRINCIPLES
Shadowing and increased through transmission
Acoustic shadowing and increased through transmission of sound (often referred to as enhancement, a term better reserved for the signal-augmenting effects of microbubble contrast agents) are important components of the ultrasound image. Shadowing occurs when little or no ultrasound can penetrate an interface and results in a dark band over the deeper tissues, bounded by the ultrasound beam lines, which are parallel for a linear transducer and radiating for a curved or sector transducer ( Fig. 3.17 ). Shadowing is reduced when compounding is used.

[img[f4-u1.0-B978-0-443-10163-2..50006-3..gr17.jpg]]

Absorption and reflection are the two main causes of shadowing. If a portion of the tissue being imaged absorbs ultrasound faster than the background for which the TGC is adjusted, tissues deeper to the highly attenuating region are undercorrected and appear darker than adjacent tissue. Fibrous tissue and, to a lesser extent, fat attenuate more than average and are common causes of acoustic shadowing (e.g. in a fatty liver, behind scars, and behind scirrhous breast carcinomas). High attenuation also partly accounts for the shadows seen deep to calcific lesions such as biliary and renal stones; note that in this case the intense reflection is the main factor. Whatever proportion of the incident ultrasound is reflected is not available to continue through for imaging. For stones, this amounts to about 60% of the incident energy, but for tissue–gas interfaces almost all the incident ultrasound is reflected and these produce dense shadows. In this case, the shadows are often partially filled in by reverberant echoes caused by the efficiency of these gas–tissue boundaries as reflectors, so that reverberation artefacts commonly occur. This noise in gas shadows has given rise to their designation as ‘dirty shadows’, as compared to the ‘clean shadows’ behind stones, and this is a useful differential diagnostic feature.

Whether a stone or gas bubble actually casts a shadow depends on its size because about three-quarters of the beam must be obstructed to cause a shadow. If a stone is smaller than this, or lies away from the central axis of the beam, enough ultrasound passes beside it to insonate the deeper tissues. In practice, shadowing is usually apparent behind renal and biliary stones of 5 mm or more in diameter; much smaller calcifications may shadow if high-resolution transducers are used. Groups of fine calcifications can also shadow if their aggregate size and density is high enough (e.g. in nephrocalcinosis).

A third important type of shadowing is ‘edge shadows’, sometimes known as ‘refractive shadows’, a description based on one explanation of their origin. They are seen as fine, dark lines extending deep to strongly curved surfaces. Cysts and the fetal skull are typical examples and fascia is often also responsible; for example, the fine shadows seen beyond Cooper's ligaments in the breast and those caused by the neck of the gallbladder. These edge shadows must be recognized as being different from attenuating and reflective shadows to avoid errors in their interpretation.

Increased through transmission is the opposite of attenuation shadowing: a region of tissue has a lower than average attenuation and so the TGC (which is adjusted to compensate for the average attenuation) is inappropriately high for that region so that echoes from deeper tissues are overamplified. The phenomenon is the hallmark of cystic spaces and the ‘bright up’ is often accentuated by the darker banding lines of the edge shadows typically formed from the cyst wall ( Fig 3.18 ). Even those fluid cavities that contain echogenic material, such as suspended crystals in the gallbladder, pus, blood or necrotic tissue, usually still produce increased transmission, depending largely on the proportion of fluid present. However, some solid tissues also show increased sound transmission, usually because they have a high proportion of fluid. Many tumours fall into this category, especially fibroadenomas in the breast, while lymphomatous deposits and inflammatory masses may behave in the same way.

[img[f4-u1.0-B978-0-443-10163-2..50006-3..gr18.jpg]]

Echogenicity
The prime determinant of the strength of ultrasonic echoes is the impedance mismatch (Z) between adjacent tissue components. At the risk of being somewhat simplistic, in practical clinical terms this may be understood as interfaces between tissues of different densities. The larger the mismatch, the stronger the echo, so that interfaces between soft tissues and bone, for example, give very strong echoes; however, within soft tissues, the most significant components are fibrous tissue (often in the form of the perivascular microskeleton) and fatty tissue. Thus, while uniform regions of fibre or fat are echo-poor (subcutaneous fat and retroperitoneal fibrosis are examples), admixtures between them and watery tissues give stronger echoes.

A second important factor is the concentration of the scatterers: for a given impedance mismatch, a region that contains a large number of scatterers is more echogenic than one where they are spread out. Commonly, the ‘dilution’ of scatterers is caused by high water content. The low reflectivity of the congested liver in right heart failure is an example. Malignant tumours are a general case: until they grow large enough to undergo necrosis or calcification they tend to be echo-poor ( Fig. 3.19 ). Similarly, the oedematous tissues in acute inflammation give low-level echoes (e.g. the echo-poor pancreas in acute pancreatitis). On the other hand, the high concentration of reflectors is the cause of the echogenic kidneys in recessive (infantile) polycystic renal disease—the interfaces between the innumerable cysts cause strong echoes ( Fig. 3.20 ). Strong echoes are also obtained from the multiple interfaces of the vessel walls of haemangiomas, and even stronger ones from angiomyolipomas in which there is also admixed fatty tissue.

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DOPPLER ULTRASOUND
The Doppler principle has been utilized in diagnostic ultrasound since 1954. Colour Doppler is a refinement of the technique whereby the regions of blood flow are displayed in colour as an overlay on the grey scale 2D image. ‘Duplex’ is used to imply that two types of information are being collected simultaneously: typically 2D imaging (possibly with colour Doppler) and spectral Doppler.

The Doppler effect is a change in the frequency of sound being reflected from a moving target. In its simplest form in diagnostic ultrasound equipment, it is used to detect the beating fetal heart lying anywhere in the sound field of a large, unfocused and continually transmitting transducer. With these systems there is no way of determining either the direction of motion or depth of the fetal heart beneath the transducer, an advantage in this clinical application because the fetal heart beat can be detected successfully without accurate positioning of the transducer.

In vascular applications, a wide, continuous ultrasound beam might result in confusing signals being received from several vessels simultaneously. This limitation is overcome by utilizing a narrow beam, similar to that used for imaging, and by transmitting the ultrasound in short pulses and processing only the information returning from a specific depth. Accurate positioning of the sensitive area of the beam (the sample volume) is achieved by positioning an electronic marker in the 2D image. Array transducers permit the collection of Doppler information while continuing with real-time imaging, albeit at a reduced frame rate since the machine has to share the pulses between the modes.

Theoretical basis of Doppler studies
An ultrasound beam insonating a blood vessel is partially reflected by red blood cells. If these are moving, there is a change in the frequency of the reflected pulse: an increase in frequency if the flow is towards the probe and a decrease if it is away from it. This is the Doppler effect and the changes in frequency, referred to as the Doppler shift, may be calculated from the equation:



This indicates that the Doppler frequency shift (fd) depends on the transmitted frequency (fo), the velocity of the blood (v) and the angle between the ultrasound beam and the direction of flow (θ). The speed of ultrasound (c) is constant. If the angle is known and the frequency shift measured, the blood flow velocity may be calculated by the scanner's computer. The operator places a cursor appropriately in the vessel and marks the direction of the vessel axis. It is necessary to achieve an angle of considerably less than 90 degrees between the direction of blood flow and the direction of the ultrasound beam, as no Doppler signal results if the beam/vessel angle is 90 degrees (cos 90° = 0 in the above equation). The accuracy of the calculated velocities is inversely proportional to the beam/vessel angle. At an angle of zero degrees the error is up to 3%, at 70 degrees it is 30% and at 80 degrees it may approach 100% (see Fig. 3.38 ).

Characteristics of blood flow
When blood is flowing in a straight vessel, the drag effects of the vessel wall and the viscosity of blood slow the flow near the vessel wall so blood can be considered as flowing in a series of concentric layers (laminae), the blood in adjacent laminae having different velocities ( Fig. 3.21 ). This type of flow is termed ‘laminar flow’ which is assumed in many of the calculations made from Doppler data. However, flow is nonlaminar in many vessel segments, including near bends, branches and junctions, and around plaques of atheroma. Values derived from Doppler signals in these circumstances may be inaccurate.

If flow is not pulsatile and the velocity is not high, the ‘velocity profile’ across the vessel is approximately parabolic ( Fig. 3.22 ). If the blood is flowing fast or is being accelerated rapidly, it tends to move with the same velocity, so-called ‘plug flow’ ( Fig. 3.23 ). In a major artery the flow usually approximates to plug flow during systole and to parabolic flow during diastole. Venous flow is normally parabolic.

The term turbulent flow is frequently misused to imply any form of flow disturbance: strictly speaking, it should only be applied to describe the complex flow disturbance that results from blood being forced at high velocity through a small orifice. The mildest form of flow disturbance (usually encountered near a moderate stenosis) results in an increase in the range of velocities present, giving rise to spectral broadening in the Doppler trace. More severe lesions may be accompanied by ‘disturbed flow’ in which eddies or vortices of flow occur beyond the lesion, giving rise to simultaneous forward and reverse flow components in the Doppler signal.

The flow velocity waveform through the cardiac cycle depends on cardiac function, the type of blood vessel and the state of the distal vascular bed. Elastic arteries such as the femoral, supplying high-resistance beds, exhibit a pronounced triphasic flow pattern ( Fig. 3.24 ). There is a rapid systolic upstroke but, because of the combination of elasticity and high peripheral resistance (if the supplied muscles are at rest), almost immediate flow reversal occurs, resulting in a transient negative Doppler component. There may be no forward flow during diastole. However, if the peripheral resistance is low, as in the internal carotid, hepatic and renal arteries, a uniphasic pattern is seen with forward flow throughout diastole ( Fig. 3.25 ). A switch from the former to the latter occurs in the limb vessels with exercise and in the mesenterics with digestion. The waveform of the display may also be modified by many factors above, at, or below the sampling site. In a major artery the waveform is determined by cardiac contractility, aortic valve function, the proximal arterial tree, the state of the vessel at the examination site and disease in the distal arterial tree supplied by the vessel.

When quantifying the severity of a stenosis, it is important to be clear as to whether a reduction in cross-sectional area (CSA) or diameter is being described; for example, a 70% diameter reduction gives rise to a 90% area reduction ( Table 3.2 ).
Table 3.2   -- RELATIVE VALUES FOR AREA AND DIAMETER REDUCTION IN STENOSES
|10	|20|
|20	|36|
|30	|51|
|40	|64|
|50	|75|
|60	|84|
|70	|91|
|80	|96|
|90	|99|
|95	|99.75|

When the CSA of an artery is narrowed by up to 50% (diameter reduction 30%) there is no reduction in the volume of blood flowing and there must therefore be an increase in the peak flow velocity. This is usually accompanied by an increase in the range of velocities present (spectral broadening) ( Fig. 3.26 ). If the stenosis is greater than 50%, there is a much greater increase in the velocity, and the flow beyond the stenosis forms eddies (disturbed flow) that give rise to 100% spectral broadening with small amounts of simultaneous reverse flow ( Fig. 3.27 ). The disturbed flow propagates for a few centimetres beyond the lesion. Narrowing of the CSA by more than 75% (50% diameter reduction) reduces volume flow, which produces a fall in flow velocity in the proximal vessel segment. Stenoses of more than 90% CSA reduction (70% diameter reduction) give rise to a severe reduction in volume flow, very high jet velocities through and beyond the lesion and turbulence beyond the lesion ( Fig. 3.28 ). In addition, there is an increase in the pulsatility of the flow proximal to the lesion and a decrease beyond. These indirect signs may be the only available indicators of disease in some clinical situations; for example, in renal artery stenosis, where the stenotic segment may not be accessible to ultrasound examination.

Information in the Doppler signal
The spectral Doppler signal consists of a mixture of continually varying frequencies that, by chance, fall in the audible range so that the signal may be evaluated simply by amplifying it and feeding it to a loudspeaker. The frequency content and waveform of the signal, however, contain a wealth of information about the nature of the blood flow in the vessel and it is easier to appreciate and interpret these if a visual display is created. This is derived from a ‘spectrum analyser’ which determines the strength of components in the Doppler signal that fall into each of numerous frequency bands during a time interval of typically 5–20 ms. The resultant display represents frequency on the vertical axis and time on the horizontal axis. The brightness of the tracing at any point indicates the amount of signal at each specific frequency over each time interval and is proportional to the number of red cells in the sample volume that are moving at each velocity ( Fig. 3.29 ). The outline of the spectral display gives information about the direction of the flow, the maximum Doppler frequency at any time, and the nature and magnitude of any pulsations or other periodic changes in flow velocity. By convention, flow towards the transducer is displayed above the baseline and away from the transducer below.

Clearly there is a great deal of information in the Doppler signal and currently we do not have techniques for extracting it all. There are, however, several simple observations that permit the diagnosis and grading of disease, and some of these can be supported by simple mathematical calculations.

Pulsatility measurements
Many indices of waveform analysis have been devised but only two are in regular clinical use. These are the resistance index (RI) (also known as the Porcelot index) and the pulsatility index (PI) (also known as the Gosling index). Because they are ratios, they are independent of the beam/vessel angle (although obtaining a good quality Doppler trace from which to make the measurement does require a beam/vessel angle of < 60 degrees). Their derivations are:

[img[g4-u1.0-B978-0-443-10163-2..50006-3..si2.gif]]

[img[g4-u1.0-B978-0-443-10163-2..50006-3..si3.gif]]

The PI was devised to characterize the triphasic flows typically seen in the femoral artery. Its main disadvantage is that it requires calculation of the mean peak frequency, whereas the RI only requires the measurement of two values. The RI is particularly sensitive to changes in downstream flow resistance and was devised to assess changes in diastolic flow in low-resistance vascular beds. The resistance may be increased by vascular stenosis or by disease in the organ supplied by the vessel. However, as it also depends on the ‘end diastolic’ velocity, the RI increases as the heart rate decreases, allowing a longer duration for the diastolic flow to fall ( Fig. 3.30 ). In theory, it is possible to correct the RI for a normalized heart rate; in practice, however, this is seldom done.

Spectral content
The distribution of the shades of grey in each time slot indicates the range of flow velocities present in the vessel at that time. If there is plug flow, this distribution is very narrow ( Fig. 3.31A ), whereas parabolic flow gives rise to a wider range of frequencies ( Fig. 3.31B ). The spectral broadening produced by a stenosing lesion is shown in Figure 3.28 .

Colour Doppler
With this form of display, areas of blood flow are represented as colour within the image. It has become common practice to represent flow towards the transducer as red and flow away as blue ( Fig. 3.32 ). The operator can reverse these assignments and select alternative colours. The velocity information used is a cruder estimate of the mean velocity in each location compared to the spectral information described above. For some clinical applications the colour may be set to vary with the variance of the velocity rather than mean velocity; this may be helpful for the detection of flow disturbance or turbulence as an indication of the site of significant vascular disease. The Doppler information is collected in rapid sequence from a large number of discrete picture elements. The derived velocity information displayed at each pixel is built up from a number of consecutive ultrasound echoes, and this necessarily reduces the number of complete frames of Doppler information that can be acquired in any time period. The frame rate for colour Doppler is therefore about one-quarter of that for grey scale imaging, although this problem can be alleviated by reducing the width of the Doppler gate and by increasing the size of each pixel. In practice, a compromise between frame rate, image area spatial resolution and accuracy of the colour velocity information has to be accepted.

The main advantages of colour Doppler are the ease with which vessels can be detected and their patency confirmed. In many applications this may be all that is required for confirming that a structure is a vessel, or that a known vessel is patent. Where relevant, the direction of flow can also be easily confirmed (e.g. in the portal vein). The wealth of information contained in the Doppler spectrum is not available in the colour image, however, and it is often necessary to perform a conventional spectral Doppler study as well. The positioning of the Doppler gate is greatly facilitated by colour Doppler and made more accurate. In addition, colour Doppler readily shows up vessels that are too small to be resolved in the 2D image and that otherwise could not be studied.

The major clinical applications of colour Doppler are the same as those for conventional spectral Doppler, although the ease of examination is improved and the operator's confidence enhanced. In addition, colour Doppler permits the detection of very small vessels and the assessment of the number and distribution of vessels within a tissue volume. This is of relevance when attempting to record blood flow signals from vessels such as the renal arcuate arteries or the uterine arteries, and in the assessment of the vascularity in and around focal lesions. For example, the colour Doppler-detected vascular pattern around malignant breast lesions shows more numerous vessels, often with abnormal courses, than are seen in benign lesions, and primary hepatomas appear more obviously vascular than metastases in the liver.

Power Doppler
The Doppler information used in power Doppler is the same as for colour Doppler but the velocity information is discarded and usually also the direction information. The colour hue is modulated by the strength of the Doppler signal, which, in turn, is proportional to the number of red cells moving within the sample volume. The display is thus a map of the distribution of moving red cells above the sensitivity threshold of the system. Large vessels give high signals, while the presence of both tissue and small vessels in the sensitive region gives a weaker signal. Fortunately, the random noise that impairs conventional velocity colour Doppler is self cancelling with this form of display, thus enabling higher gains (around 10dB) to be used and increasing the sensitivity for vessel detection.

Power Doppler is useful for depicting slow flow in smaller vessels—for example, in the kidney ( Fig. 3.33 )—and in malignancies. The reduction in signal strength when a volume element is only partially within a vessel gives an apparent improvement in vessel wall definition ( Fig. 3.34 ). A further practical advantage is the reduced dependence on the beam/vessel angle. This is mainly because the direction information is averaged in colour Doppler and cancels out if the beam/vessel angle is close to 90 degrees ( Fig. 3.35A ). In power Doppler the direction information is ignored and the signal amplitudes are averaged. As these are all positive, a strong signal results ( Fig. 3.35B ).

VOLUME FLOW MEASUREMENT
It is theoretically possible to measure the volume of blood flowing within a vessel using Doppler ultrasound. This requires calculation of the mean blood velocity in the vessel and the cross-sectional area of the vessel. The product of these two values should be the volume of blood flowing. In practice, there are significant uncertainties about both values, which may lead to errors in excess of 100%. Calculation of the mean velocity should take into consideration the distribution of velocities across the vessel in each time interval and the average of these over several cardiac cycles ( Fig. 3.36 ). It is also assumed that the vessel is uniformly insonated and that signals are detected from all the blood in the cross-section of the vessel. In practice, slow-moving blood is missed and the range gate or beam width may encompass only a fraction of the cross-sectional area. These errors may not be obvious from visual inspection of the spectral display. If the cross-sectional area of a vessel is calculated from a single diameter, any error is squared. Measuring the area from an image at right angles to the vessel axis may be more accurate, but this information cannot be obtained at the same time and site as the Doppler signal, owing to the inappropriate beam/vessel angle. Volume blood-flow measurement in the carotid and femoral vessels and in the abdomen has not been shown to be of clinical value.

DOPPLER ARTEFACTS, ERRORS AND PITFALLS
Doppler examinations are subject to a range of artefacts and potential errors that are not encountered in 2D imaging.

Sample volume size and position
The shape of the sample volume is determined by the length of the range gate and the width of the ultrasound beam at the depth of the gate. The depth and length of the sample volume are determined by the operator and should be matched to the size of the vessel under investigation. If the sample volume is too small or does not encompass the whole cross-section of the vessel, the resulting spectrum underestimates the range of velocities present in the vessel. In scanners with array transducers, the beam width can be altered and many automatically focus the beam at the depth of the range gate. This is seldom advisable since, although it may improve sensitivity, it leads to undersampling in large vessels such as the portal vein. Similarly, if the sample volume is small and the vessel to be studied is mobile, a discontinuous Doppler signal results. If the movement of the vessel is due to respiration, the cause for the changes in the spectral display can usually be recognized. If, however, an artery moves as a result of intrinsic pulsations it may move in and out of the beam with each cardiac cycle. This can give rise to loss of the diastolic signal in each cycle, resulting in falsely high PI and RI values ( Fig. 3.37 ).

If the range gate is too large or the beam width too great, more than one vessel may lie in the beam at the same time and give rise to a confusing spectral display, especially if flow in both vessels is in the same direction. Sometimes such a feature is of positive advantage; for example, when searching for a renal vein signal alongside the renal artery. The actual length of the sample volume is usually greater than that displayed on the image. This has led to the false assertion that it is acceptable to have a sample volume smaller than the vessel diameter.

Velocity information
An important source of error when attempting a velocity calculation is the effect of the beam/vessel angle. This shows the percentage error in velocity calculation that may be expected for different angles. At angles greater than 50 degrees there is a rapid increase in error that approaches 100% at 80 degrees ( Fig. 3.38 ). Major errors may also arise from the way the mean velocity is calculated: calculating the mean value of the peaks is only accurate for pure plug flow ( Fig. 3.39 ). Strictly, the mean velocity should be calculated for each time interval, taking into account the distribution of velocities in that time interval. The mean of a large number of these values over several cardiac cycles should then be calculated ( Fig. 3.36 ). For a vessel with true laminar flow and a parabolic profile, this more accurate method produces a value half that of the mean peak method.

The pulse repetition frequency (PRF) of the ultrasound system imposes limitations on the range of Doppler frequencies that can be measured. The maximum value of the PRF is limited by the depth from which echoes are to be recorded. In abdominal diagnosis this may be up to 15 cm. In order to allow time for the echoes to be received before the next pulse is transmitted, about 250μs must elapse between pulses. Thus, the pulses can only be repeated at about 4000s-1 (4kHz). The Doppler detectors can only measure frequencies accurately if they are less than half of the PRF (the Nyquist limit), i.e. less than 2kHz in this example. Doppler shift frequencies above this level are frequently encountered in the abdomen, are misinterpreted by the apparatus, and displayed on the wrong side of the baseline, giving rise to a characteristic discontinuous waveform display ( Fig. 3.40A ). The technical term for this phenomenon is ‘aliasing’ and it may sometimes be overcome by viewing the vessel from a steeper angle, using a lower ultrasound frequency, a higher PRF or continuous Doppler beam, or by electronic correction ( Fig. 3.40B ).

Wall filters
The pulsating walls of arteries give rise to high-amplitude, low-frequency Doppler signals that may overload the spectrum analyser and appear in the spectral display as high-intensity spikes. This ‘wall thump’ can be filtered out by rejecting the very low frequencies in the Doppler signal. If the ‘wall filter’ is set too high, however, true flow information may be lost ( Fig. 3.41 ). For abdominal venous studies, a filter value as low as 25–50Hz is appropriate. In some makes of scanner, settings up to 800Hz are available for arterial studies and would eliminate the Doppler information from many veins.

The most common problem with colour Doppler is failure to appreciate that the colours represent flow direction with respect to the transducer. If a vessel curves or bifurcates in the image plane, the flow in different segments will be represented in different colours. The same artefact may result if a straight vessel is imaged with a curvilinear or sector transducer ( Fig. 3.42 ).

As with spectral Doppler, aliasing also occurs in colour flow imaging and results in reversal of colour and thus apparent flow reversal. Aliasing can be identified by noting that the areas of colour reversal are contiguous ( Fig. 3.43 ). If the flow reversal is genuine, the forward and reverse flow colours are separated by a black margin.

SAFETY OF ULTRASOUND
An important feature of diagnostic ultrasound, especially in obstetric applications, is its apparent safety. No study has shown any damaging effect of pulsed ultrasound at diagnostic intensities when applied to the intact fetus in utero. These studies include follow-up assessments of growth, the development of cataracts and hearing loss, and the induction of childhood malignancies. Occasional reports of effects (usually unimportant and found on searching the data collected for other purposes, a statistically unacceptable methodology) have failed to be substantiated on repeat studies. One curiosity that does seem to be statistically sound was the unexpected finding in a Norwegian study that male fetuses imaged with ultrasound were less likely to be right-handed (23% were left-handed or without a dominant hand, compared with 17% in controls). While unimportant in itself, this suggests that ultrasound can induce changes in cell migration at an early developmental stage.

There have been several reports of biochemical alterations to cells in suspension, including changes to DNA and surface membrane behaviour, both of which are obvious at high intensities but are demonstrable also (at least in some studies) at diagnostic power levels. It is debatable whether these effects are significant for the intact animal and it is notable that many of them have proved to be elusive when repeat studies have been attempted. They do, however, inject a note of caution and reinforce the importance of using common sense in restricting the use of high-power modes and long imaging durations to situations in which the clinical benefit outweighs any possible ill effects: there is no place in medicine for a quick (i.e. inadequate) ultrasound or for ‘just to have a look’ (e.g. at a fetus). The entire subject of safety is under continuous review and up-to-date information is available from the European Federation of Societies for Ultrasound in Medicine and Biology (www.efsumb.org).

Ultrasound intensity is the energy flowing across a surface in unit time; the usual units are watts per square centimetre. For pulsed ultrasound, a peak or average value may be taken. Because of focusing, the energy distribution along and across the beam is nonuniform, and the peak intensity at the maximum point is usually quoted. Mean spatial peak temporal average intensities for B-mode imaging are ∼175 mWcm-2, and for spectral Doppler ∼1600 mWcm-2.

High intensities of ultrasound are capable of causing significant biological effects. These are used to therapeutic benefit both in physiotherapy, when the changes sought (mainly local heating) are often reversible in nature, and in ultrasound surgery, when cell killing is the aim. The primary mechanism inducing biological change is thermal. The ultrasound beam is attenuated during its passage through tissue, some of the lost energy (20–40%) being scattered by tissue structures and the remainder absorbed, thus leading to heating. In the case of B-mode imaging and Doppler examinations of soft tissue, this phenomenon results in a biologically insignificant temperature rise. Significant temperature rises may, however, be induced when a Doppler beam at its highest power is incident on a bone surface because of the high absorption at this interface where the impedance changes markedly. The problem is worst in the case of spectral Doppler, in which the beam is held over one tissue region for long periods of time. It is therefore recommended that Doppler exposures should be performed at the lowest power level consistent with obtaining the desired information and that the time the beam is held stationary is kept to a minimum. Particular care is advised when Doppler is used during late pregnancy, when the skull has begun to calcify, and in examining the neonatal brain in the vicinity of the skull.

The vibration of particles caused by a high-intensity ultrasound beam may produce mechanical disruption of intracellular membranes, and the pressures can cause fluids to flow in streaming movements. Extreme ultrasound powers can produce regions of such low pressure during the rarefaction phase of the cycle that dissolved gases (mainly nitrogen) can come out of solution, or water may vaporize to produce minute gas bubbles that pulsate in the sound field. This process, known as cavitation, can cause mechanical damage to the tissue and even lead to ionization. Cavitation is unlikely to occur at diagnostic imaging intensities in vivo but has been demonstrated with the higher powers and continuous-wave conditions used in ultrasound therapy.

Safety-related information as presented to the operator is regulated by the FDA's output display standards (ODS) which are calculated predictions of the possible effects in tissue. There are two indices, one of which, the mechanical index (MI), indicates the probability of mechanically induced damage: an MI of 1 warns of the possibility of mechanical effects in tissue. The second is the thermal index (TI), which is related to possible heating of tissues. Separate indices have been defined for soft tissue and for bone (TIS and TIB, respectively) because heating at a bone surface is likely to be higher. A TIS of 1 suggests that, in the worst case, tissue could be heated by 1°C; since damage is unlikely until temperature rises of 1.5°C or more are achieved (and maintained for some time), this is a conservative estimate, as is the MI indication. Although rather vague in their real-life meaning, the ODS does provide guidance to users, who can then decide whether any possible risk to, for example, the fetus, is outweighed by the potential benefit of the examination.

DEVELOPMENTS IN ULTRASOUND
High frequencies, 3D, elastography
Three-dimensional ultrasound (3D US) has become available on many machines and the data can be acquired rapidly enough to allow display in real-time at low frame rates (called 4D). It has found niche applications, mainly for the display of complex anatomy such as the fetal face and the heart. In most parts of the body the clean surfaces that are required for true 3D rendering are not present; however, reslicing in otherwise unobtainable planes has proved useful in some situations; for example, to display the uterus in the coronal plane for depicting developmental anomalies.

Elasticity imaging (or elastography) is a new imaging method that is promising because of the very high contrast it offers between masses, especially tumours, and the host tissue. The principle is simple: obtain signals before and after applying a distorting force (stress) that moves the tissues by a few millimetres, and create an image of the tissue's response (strain) by comparing the two. In principle, any imaging method can be used: ultrasound has the advantage that the transducer can be used to apply the stress and of working in real-time; magnetic resonance imaging has also been used successfully. The information used to create the elastograms is similar to clinical palpation except that it is much more sensitive, especially to deeper structures. It has been applied to the breast and the prostate and is an active research area. A commercial device that estimates liver elasticity as a measure of fibrosis to assess the need for antiviral therapy in hepatitis has been developed.

Contrast agents
An important development has been the introduction of microbubble agents to enhance ultrasound signals. They exploit the very high reflectivity of microbubbles small enough to cross the lung capillary bed, so that systemic (including myocardial) ultrasound enhancement can be achieved following an intravenous injection. Their gas content makes them very reflective, even at high dilution, and initially this was exploited using Doppler to enable signals to be obtained from small vessels and from those where the signals are attenuated by overlying tissue such as the intracranial arteries under the skull.

However, by virtue of their compressibility, microbubbles display unique properties in an ultrasound beam, which sets them into resonance when there is a match between their diameter and the ultrasonic wavelength. Fortuitously, for microbubbles in the 2–7μm range (needed to allow transcapillary passage) this occurs at ultrasound frequencies of 2–10MHz. As the acoustic pressure increases and still well within diagnostic levels, the compression and expansion phases become asymmetrical because it is harder to compress a bubble than to expand it. This nonlinear behaviour produces echoes that contain frequencies not present in the transmitted pulses. Many of these are higher frequency harmonics at twice the transmitted frequency. An elegant way to extract these nonlinear signals is to send a series of pulses down each line, varying their phase and amplitude; the returning signals are combined to cancel the linear signals from tissue and the remaining bubble-specific signals are used to form an image that can be presented as a colour overlay on the B-mode image or shown on a side-by-side display, all in real-time. As these contrast-specific methods are exquisitely sensitive, low transmit powers can be used (MIs of 0.1 or 0.2) such that the fragile microbubbles are not destroyed, allowing continuous imaging for their life of around 5 min after injection. Since they do not depend on microbubble motion, they can be detected even in the microcirculation, a major advantage over Doppler techniques.

A major technical difficulty with making small bubbles is that their surface tension is so high that they collapse and dissolve within a few seconds of formation. To produce enhancement of useful duration, the microbubbles must be stabilized by encapsulating them in a membrane such as denatured albumen or a phospholipid. The gas is also critical to achieving good resonance (and therefore echogenicity) as well as providing a useful duration after injection. Air or inert gases such as perfluorocarbon compounds are the most frequently used ( Fig. 3.44 ).

Microbubbles extend to ultrasound many of the features of angiography, such as demonstrating tissue perfusion where infarction is a clinical question and demonstrating bleeding points (the microbubbles are confined to blood vessels unless there is active haemorrhage). The temporal filling patterns of focal lesions such as liver masses can be studied in similar ways to dynamic CT and MRI methods and this has become an important clinical application. Contrast-enhanced ultrasound is now incorporated into European guidelines for hepatoma detection in cirrhosis. They have proved invaluable in monitoring the extent of liver ablation using ultrasound-guided RF or laser techniques because remaining perfused tumour can be detected immediately and treatment extended to complete ablation in the same session; previously, contrast CT was required and the patient would have to return for a second ablation session.

In addition, using these agents as tracers to measure time–intensity curves analogous to those used in dynamic radioisotope studies is now possible, launching ultrasound into a new functional era of great potential. One promising approach reveals the arterialization of the hepatic blood flow in cirrhosis and in malignancy by timing the delay from injection to the appearance of microbubbles in the hepatic veins: a long delay of around 40s is normal and reflects the fact that three sets of microcirculation have to be crossed by portal blood. Arterialization, however, leads to a much earlier arrival (< 25s) and this seems to be a sensitive marker for these diseases.

An approach that may be especially important for the myocardium depends on the fragility of many types of microbubble such that they are destroyed by the ultrasound beam at the higher ranges of permitted intensity. If, after such a destructive pulse (or ‘flash’), the tissue is interrogated with a low-power, nondestructive beam, the speed with which microbubbles (and therefore red blood cells) reperfuse the slice can be measured ( Fig. 3.45 ). The slope of this refill curve relates to flow rate, while its peak level relates to the fractional vascular volume, the two measurements needed to estimate true perfusion. Although its potential importance in ischaemic heart disease is obvious, it also illustrates the innovative ways that the special properties of microbubbles can be used—in this example to create a ‘negative bolus’ for haemodynamic measurements.

Microbubbles can be modified as vehicles to carry useful compounds such as therapeutic agents, including DNA and oligonucleotides, as well as ligands for biochemical processes such as activated endothelium. This opens up possibilities for molecular imaging and for directed drug/gene delivery. Physiotherapy-level ultrasound can be used not only to release the payload but also to create transient pores in cell membranes that facilitate cell uptake. The therapeutic applications of microbubbles could overtake their diagnostic uses.

Ultrasound therapy
Ultrasound also seems likely to find a role in tissue ablative therapy, particularly in oncology. Therapeutic ultrasound uses the thermal effects of high-power ultrasound beams that are tightly focused so that very small target tissue regions can be heated and coagulated, and dedicated transrectal therapy systems have been marketed. There is also considerable research interest for the treatment of hepatic and renal lesions. Although the general approach is similar to radiotherapy, ultrasound therapy has the advantages of being much more precise, rapid (the entire process could be completed in one session), easy to handle and of not damaging adjacent tissues. It is also possible to monitor its effects in real-time with diagnostic ultrasound. The physical limitations to accessible anatomical regions are the same as for diagnostic ultrasound.
There are a lot of interesting people using ~TiddlySpace that you might like to keep track of and interact with. There are a number of ways of doing this.

If you see a number in the speech bubble in one of your tiddlers, it means that someone is writing about the same thing as you. You can find out what they're saying by clicking on it. Likewise, if you see something interesting in someone else's space, you can respond to it and write up your own thoughts on the subject by clicking "Reply to this tiddler".

Additionally, if you find anyone interesting, or you find an interesting looking space and you'd like to know when it's changed, you can "follow" that space. To do this, simply create a tiddler with the title: {{{@space-name}}} and tag it {{{follow}}}. If you want, you can store some notes about that space in the body of the tiddler.

If you then want to know what happening, simply [[include|How do I include/exclude spaces?]]@docs the @tivity space and then visit your activity stream at [[/activity|/activity]], or just visit the @tapas space directly.

!Not sure who to follow?
Here's a few suggestions:
* @fnd
* @cdent
* @pmario
* @bengillies
* @dickon
/***
|''Name''|TiddlySpaceFollowingPlugin|
|''Version''|0.7.1|
|''Description''|Provides a following macro|
|''Author''|Jon Robson|
|''Requires''|TiddlySpaceConfig TiddlySpaceTiddlerIconsPlugin ErrorHandler|
|''License''|[[BSD|http://www.opensource.org/licenses/bsd-license.php]]|
!Usage
Tag a tiddler with "follow" to express a list of followers.
Using the {{{<<followTiddlers X>>}}}
will reveal the number of tiddlers with name X in the set of spaces the *current* user viewing your space follows.
{{{<<following jon>>}}} will list all the users following Jon.
{{{<<followers jon>>}}} will list all the followers of jon.
{{{<linkedTiddlers>>}}} will list all tiddlers across TiddlySpace linked to the current tiddler
{{{<linkedTiddlers follow:yes>>}}} will list all tiddlers across TiddlySpace that come from your list of followers
adds spaceLink view type {{{<<view server.bag spaceLink>>}}} creates a link to the space described in server.bag
{{{<<view server.bag spaceLink title>>}}} makes a link to the tiddler with title expressed in the field title in space server.bag
If no name is given eg. {{{<<following>>}}} or {{{<<follow>>}}} it will default the current user.
!StyleSheet
.followTiddlersList li {
	list-style:none;
}

.followButton {
	width: 2em;
}

.followTiddlersList li .siteIcon {
	height:48px;
	width: 48px;
}

#sidebarTabs .followers li a,
.followers .siteIcon,
.followers .siteIcon div {
	display: inline;
}

.followTiddlersList li .externalImage, .followTiddlersList li .image {
	display: inline;
}

.scanResults li {
	list-style: none;
}
!Code
***/
//{{{
(function($) {
var LIMIT_FOLLOWING = 100;

var tweb = config.extensions.tiddlyweb;
var tiddlyspace = config.extensions.tiddlyspace;
var currentSpace = tiddlyspace.currentSpace.name;

var shadows = config.shadowTiddlers;
config.annotations.ScanTemplate = "This tiddler is the default template used in the display of tiddlers founding using the tsScan macro. To access attributes use the view macro e.g. {{{<<view title text>>}}}";
shadows.ScanTemplate = "<<view modifier SiteIcon width:24 height:24 spaceLink:yes label:no>> <<view title link>>";
shadows.FollowersTemplate = "<<view server.bag SiteIcon width:24 height:24 spaceLink:yes label:no>> <<view server.bag spaceLink>>";
shadows.FollowingTemplate = "<<view title SiteIcon width:24 height:24 spaceLink:yes label:no>> <<view title spaceLink>>";
shadows.FollowTiddlersBlackList = "";
shadows.FollowTiddlersHeading = "There are tiddlers in spaces you follow using the follow tag which use the title <<view title text>>";
shadows.FollowTiddlersTemplate = ["* <<view server.space SiteIcon width:24 height:24 spaceLink:yes label:no>> ",
	"<<view server.space spaceLink title external:no>> modified by <<view modifier spaceLink>> ",
	"in the <<view server.space spaceLink>> space (<<view modified date>> @ <<view modified date 0hh:0mm>>).\n"].join("");

var name = "StyleSheetFollowing";
shadows[name] = "/*{{{*/\n%0\n/*}}}*/".
	format(store.getTiddlerText(tiddler.title + "##StyleSheet"));
store.addNotification(name, refreshStyles);

// provide support for sucking in tiddlers from the server
tiddlyspace.displayServerTiddler = function(src, title, workspace, callback) {
	var adaptor = store.getTiddlers()[0].getAdaptor();
	var localTitle = tiddlyspace.getLocalTitle(title, workspace);
	var tiddler = new Tiddler(localTitle);
	tiddler.text = "Please wait while this tiddler is retrieved...";
	tiddler.fields.doNotSave = "true";
	store.addTiddler(tiddler);
	src = story.displayTiddler(src || null, tiddler.title);
	tweb.getStatus(function(status) {
		var context = {
			host: tweb.host, // TODO: inherit from source tiddler?
			workspace: workspace,
			headers: { "X-ControlView": "false" }
		};
		var getCallback = function(context, userParams) {
			var tiddler = context.tiddler;
			tiddler.title = localTitle;
			store.addTiddler(tiddler);
			story.refreshTiddler(localTitle, null, true); // overriding existing allows updating
			if(callback) {
				callback(src, tiddler);
			}
		};
		adaptor.getTiddler(title, context, null, getCallback);
	});
};

tiddlyspace.scroller = {
	runHandler: function(title, top, bottom, height) {
		var i;
		var handlers = tiddlyspace.scroller.handlers;
		var tidEl = story.getTiddler(title);
		if(tidEl) {
			var topEl = $(tidEl).offset().top + 20;
			if(top === false || (topEl > top && topEl < bottom)) {
				var h = handlers[title];
				for(i = 0; i < h.length; i++) {
					h[i]();
				}
				tiddlyspace.scroller.clearHandlers(title);
			}
		} else {
			tiddlyspace.scroller.clearHandlers(title);
		}
	},
	clearHandlers: function(title) {
		tiddlyspace.scroller.handlers[title] = [];
	},
	registerIsVisibleEvent: function(title, handler) {
		tiddlyspace.scroller.handlers[title] = tiddlyspace.scroller.handlers[title] || [];
		tiddlyspace.scroller.handlers[title].push(handler);
	},
	init: function() {
		this.handlers = {};
		this.interval = window.setInterval(function() {
			var top = $(window).scrollTop();
			var height = $(window).height();
			var bottom = top + height;
			var title;
			for(title in tiddlyspace.scroller.handlers) {
				if(title) {
					tiddlyspace.scroller.runHandler(title, top, bottom, height);
				}
			}
		}, 2000); // every 2 seconds check scroll position
	}
};
tiddlyspace.scroller.init();

var followMacro = config.macros.followTiddlers = {
	locale: {
		followListHeader: "Here are tiddlers from spaces you follow using the follow tag which use this title.",
		noTiddlersFromFollowers: "None of the spaces you follow contain a tiddler with this name.",
		errorMessage: "There was a problem retrieving tiddlers from the server. Please try again later."
	},
	init: function() {
		followMacro.lookup = {};
	},
	followTag: "follow",
	getHosts: function(callback) {
		tweb.getStatus(function(status) {
			callback(tweb.host, tiddlyspace.getHost(status.server_host, "%0"));
		});
	},
	getBlacklist: function() {
		return store.getTiddlerText("FollowTiddlersBlackList").split("\n");
	},
	handler: function(place, macroName, params, wikifier, paramString, tiddler) {
		var args = paramString.parseParams("anon")[0];
		var containingTiddler = story.findContainingTiddler(place).getAttribute('tiddler');
		var title = (args.anon && args.anon[0]) || tiddler.fields["server.title"] || tiddler.title;
		var tid = store.getTiddler(title);
		var user = params[1] || false;
		if(tid) {
			followMacro.makeButton(place, {
				url: "/search?q=title:%22" + encodeURIComponent(title) + "%22",
				containingTiddler: containingTiddler,
				blacklisted: followMacro.getBlacklist(), title: title, user: user,
				consultFollowRelationship: (args.follow &&
					args.follow[0] === 'false') ? false : true });
		}
	},
	makeButton: function(place, options) { // this is essentially the same code in TiddlySpaceFollowingPlugin
		var title = options.title;
		var blacklisted = options.blacklisted;
		var tiddler = store.getTiddler(title);
		var btn = $('<div class="followButton" />').addClass("notLoaded").appendTo(place)[0];
		if(blacklisted.contains(title)) {
			$(btn).remove();
			return;
		} else {
			var user = options.user;
			window.setTimeout(function() { // prevent multiple calls due to refresh
				tiddlyspace.scroller.registerIsVisibleEvent(options.containingTiddler, function() {
					var mkButton = function(followers, ignore) {
						if(!followers && !ignore) {
							$(btn).remove();
						} else {
							$("<a />").appendTo(btn);
							var scanOptions = { url: options.url,
								spaceField: options.spaceField || "bag", template: null, sort: "-modified",
								callback: function(tiddlers) {
									$(btn).removeClass("notLoaded");
									followMacro.constructInterface(btn, tiddlers);
								}
							};
							if(!ignore) {
								scanOptions.showBags = followMacro._getFollowerBags(followers);
							}
							scanOptions.hideBags = [tiddler.fields["server.bag"]];
							scanMacro.scan(null, scanOptions, user);
						}
					};
					if(options.consultFollowRelationship) {
						followMacro.getFollowers(mkButton);
					} else {
						mkButton([], true);
					}
				});
			}, 1000);
		}
	},
	constructInterface: function(container, tiddlers) {
		var txt = tiddlers.length;
		var className = txt > 0 ? "hasReplies" : "noReplies";
		var el = $(story.findContainingTiddler(container));
		$(container).empty().addClass(className);
		var btn = $("<a />").addClass("followedTiddlers").text(txt).
			click(function(ev) {
				followMacro.followingOnClick(ev);
			}).appendTo('<div class="followedTiddlers" />').appendTo(container)[0];
		$.data(btn, "tiddlers", tiddlers);
	},
	followingOnClick: function(ev) {
		var target = ev.target;
		var locale = followMacro.locale;
		var el = $('<div class="followTiddlersList" />')[0];
		var popup = Popup.create(target,"div");
		$(popup).addClass("taggedTiddlerList followList").click(function(ev) { // make it so only clicking on the document outside the popup removes the popup
			if(ev.target.parentNode != document) {
				ev.stopPropagation();
			}
		}).append(el);
		var tiddlers = $.data(target, "tiddlers") || [];
		scanMacro.template(el, tiddlers.slice(0,1), "FollowTiddlersHeading");
		scanMacro.template(el, tiddlers, "FollowTiddlersTemplate");
		if(tiddlers.length === 0) {
			$("<li />").text(locale.noTiddlersFromFollowers).appendTo(el);
		}
		Popup.show();
		ev.stopPropagation();
		return popup;
	},
	_getFollowerBags: function(followers) { // XXX: private or not?
		return $.map(followers, function(name, i) {
			return name != currentSpace ? "%0_public".format(name) : null;
		});
	},
	getFollowers: function(callback, username) {
		// returns a list of spaces being followed by the existing space
		var followersCallback = function(user) {
			if(!user.anon) {
				scanMacro.scan(null, { 
					url: "/search?q=bag:%0_public tag:%1 _limit:%2".format(user.name, followMacro.followTag, LIMIT_FOLLOWING),
					spaceField: "title", template: null, cache: true,
					callback: function(tiddlers) {
						var followers = [];
						for(var i = 0; i < tiddlers.length; i++) {
							followers.push(tiddlyspace.resolveSpaceName(tiddlers[i].title));
						}
						callback(followers);
					}
				});
			} else {
				callback(false);
			}
		};
		return !username ? tweb.getUserInfo(followersCallback) : followersCallback({ name: username });
	}
};

var scanMacro = config.macros.tsScan = {
	init: function () {
		this.scanned = {};
	},
	_tiddlerfy: function(jsontiddlers, options) {
		var tiddlers = [];
		var spaceField = options.spaceField || "bag"; // TODO: phase out use view types instead
		$.each(jsontiddlers, function(i, t) {
			var use = false;
			if(!options.showBags || (options.showBags && options.showBags.contains(t.bag))) {
				use = true;
			}
			if(options.hideBags && options.hideBags.contains(t.bag)) {
				use = false;
			}
			if(use) {
				var spaceName = t[spaceField];
				var tiddler = config.adaptors.tiddlyweb.toTiddler(t, tweb.host);
				tiddler.fields["server.space"] = tiddlyspace.resolveSpaceName(spaceName);
				tiddlers.push(tiddler);
			}
		});
		return tiddlers;
	},
	_scanCallback: function(place, jsontiddlers, options) {
		var locale = followersMacro.locale;
		var tiddlers = scanMacro._tiddlerfy(jsontiddlers, options);
		
		if(options.sort) {
			tiddlers = store.sortTiddlers(tiddlers, options.sort);
		}
		if(options.filter) {
			var _store = new TiddlyWiki();
			config.lastStore = _store;
			for(var i = 0; i < tiddlers.length; i++) {
				var clone = tiddlers[i];
				clone.title = tiddlyspace.getLocalTitle(clone.title, clone.fields['server.workspace']);
				_store.addTiddler(clone);
			}
			tiddlers = _store.filterTiddlers(options.filter);
		}
		if(place) {
			$(place).empty();
			var list = $("<ul />").appendTo(place)[0];
			scanMacro.template(list, tiddlers, options.template);
			if(tiddlers.length === 0) {
				$("<li />").text(options.emptyMessage || locale.noone).appendTo(list);
				$(list).addClass("emptyList");
			}
		}
		if(options.callback) {
			options.callback(tiddlers);
		}
	},
	constructSearchUrl: function(host, options) {
		if(options.url) {
			return options.url;
		}
		var inputs = options.searchValues;
		var tag = options.tag;
		var searchField = options.searchField || "title";
		var searchQuery = [];
		for(var i = 0; i < inputs.length; i++) {
			searchQuery.push('%0:"%1"'.format(searchField, inputs[i]));
		}
		var query = searchQuery.join(" OR ");
		query = tag ? "(%0) AND tag:%1".format(query, tag) : query;
		query = options.query ? "%0;%1;".format(query, options.query) : query;
		query = options.fat ? "%0&fat=1".format(query) : query;
		return '%0/search?q=%1'.format(host, query);
	},
	scan: function(place, options) { // TODO: make use of list macro with url filter
		var locale = followersMacro.locale;
		options.template = options.template ? options.template : "ScanTemplate";
		followMacro.getHosts(function(host, tsHost) {
			$(place).text(followersMacro.locale.pleaseWait);
			options = options ? options: {};
			var url = scanMacro.constructSearchUrl(host, options);
			if(options.cache && scanMacro.scanned[url]) {
				var tiddlers = scanMacro.scanned[url].tiddlers;
				var run = function(tiddlers) {
					scanMacro._scanCallback(place, tiddlers, options);
				};
				if(tiddlers) {
					run(tiddlers);
				} else {
					scanMacro.scanned[url].callbacks.push(run);
				}
			} else {
				var callback = function(tiddlers) {
					scanMacro._scanCallback(place, tiddlers, options);
				};
				if(scanMacro.scanned[url] && scanMacro.scanned[url].callbacks) {
					scanMacro.scanned[url].callbacks.push(callback);
				} else {
					scanMacro.scanned[url] = {
						callbacks: [callback]
					};
				}
				ajaxReq({
					url: url,
					dataType: "json",
					success: function(tiddlers) {
						scanMacro.scanned[url].tiddlers = tiddlers;
						var callbacks = scanMacro.scanned[url].callbacks;
						while(callbacks.length > 0) {
							callbacks.pop()(tiddlers);
						}
					},
					error: function(xhr) {
						$(place).empty();
						$("<span />").addClass("annotation error").text(locale.error.format(xhr.status)).appendTo(place);
					}
				});
			}
		});
	},
	template: function(place, tiddlers, template) { // TODO: make use of list macro.
		for(var i = 0; i < tiddlers.length; i++) {
			var tiddler = tiddlers[i];
			var item = $('<li class="spaceName" />').appendTo(place)[0];
			var spaceName = tiddler.fields["server.space"] || "";
			var templateText = store.getTiddlerText(template).replace(/\$1/mg, spaceName);
			wikify(templateText, item, null, tiddler);
		}
	},
	getOptions: function(paramString, tiddler) {
		var args = paramString.parseParams("name", null, true, false, true)[0];
		var options = { query: false, sort: false, tag: false, template: false, showBags: args.show || false,
			hideBags: args.hide || false, filter: false, spaceField: "bag", searchField: "title", fat: false,
			emptyMessage: false };
		for(var name in args) {
			if(name != "name") {
				if(name == "fat") {
					options[name] = true;
				} else {
					options[name] = args[name][0];
				}
			}
		}
		// if user has set searchField to modifier, then use the modifiers value if available otherwise use searchValues.
		var searchField = options.searchField;
		var searchValues = args[searchField] ? args[searchField] : args.searchValues;
		// if neither of those were used use the first parameter
		var defaultValues = tiddler ? [ tiddler.title ] : [];
		options.searchValues = searchValues ? searchValues : ( args.name ? [args.name[0]] : defaultValues);
		return options;
	},
	handler: function(place, macroName, params, wikifier, paramString, tiddler) {
		var container = $("<div />").addClass("scanResults resultsArea").appendTo(place)[0];
		var options = scanMacro.getOptions(paramString, tiddler);
		scanMacro.scan(container, options);
	}
};

var followersMacro = config.macros.followers = {
	locale: {
		loggedOut: "Please login to see the list of followers",
		noSupport: "We were unable to retrieve followers as your browser does not support following.",
		pleaseWait: "Please wait while we look this up...",
		error: "Error %0 occurred whilst retrieving data from server",
		noone: "None."
	},
	handler: function(place, macroName, params, wikifier, paramString, tiddler) {
		var locale = followersMacro.locale;
		var args = paramString.parseParams("name", null, true, false, true)[0];
		var username = args.name ? args.name[0] : false;
		var container = $('<div class="followers" />').text(locale.pleaseWait).
			appendTo(place)[0];
		var followersCallback = function(user) {
			if(user.anon) {
				$("<span />").text(locale.loggedOut).appendTo(container);
			} else {
				var options = scanMacro.getOptions(paramString);
				$.extend(options, {
					url: "/search?q=title:@%0 OR title:%0 tag:%1 _limit:%2".
						format(user.name, followMacro.followTag, LIMIT_FOLLOWING),
					spaceField: "bag",
					template: options.template ? options.template : "FollowersTemplate"
				});
				scanMacro.scan(container, options);
			}
		};
		return !username ? followersCallback({ name: currentSpace }) : followersCallback({ name: username });
	}
};

var followingMacro = config.macros.following = {
	locale: {
		pleaseWait: followersMacro.locale.pleaseWait,
		loggedOut: "Please login to see who you are following",
		noSupport: followersMacro.locale.noSupport,
		error: followersMacro.locale.error,
		noone: followersMacro.locale.noone
	},
	handler: function(place, macroName, params, wikifier, paramString, tiddler) {
		var locale = followingMacro.locale;
		var args = paramString.parseParams("name", null, true, false, true)[0];
		var fat = args.fat ? true : false;
		var username = args.name ? args.name[0] : false;
		var container = $('<div class="following" />').text(locale.pleaseWait).
			appendTo(place)[0];
		var followingCallback = function(user) {
			if(user.anon) {
				$("<span />").text(locale.loggedOut).appendTo(container);
			} else {
				var options = scanMacro.getOptions(paramString);
				$.extend(options, {
					url: "/search?q=bag:%0_public tag:%1 _limit:%2".format(user.name, followMacro.followTag, LIMIT_FOLLOWING),
					spaceField: "title",
					template: options.template ? options.template : "FollowingTemplate"
				});
				scanMacro.scan(container, options);
			}
		};
		return !username ? followingCallback({ name: currentSpace }) : followingCallback({ name: username });
	}
};

var linkedMacro = config.macros.linkedTiddlers = {
	handler: function(place, macroName, params, wikifier, paramString, tiddler) {
		var args = paramString.parseParams("anon")[0];
		var title = params[0] || tiddler.fields["server.title"] || tiddler.title;
		var tid = store.getTiddler(title);
		var containingTiddler = story.findContainingTiddler(place).getAttribute('tiddler');
		if(tid) {
			followMacro.makeButton(place, {
				spaceField: "recipe",
				url: "/bags/%0/tiddlers/%1/backlinks".format(tid.fields['server.bag'],
					encodeURIComponent(tid.title)),
				blacklisted: followMacro.getBlacklist(),
				title: title,
				containingTiddler: containingTiddler,
				user: params[1] || false,
				consultFollowRelationship: args.follow ? true : false });
		}
	}
};

if(config.options.chkFollowTiddlersIsLinkedTiddlers) {
	merge(config.macros.followTiddlers, config.macros.linkedTiddlers);
	config.shadowTiddlers.FollowTiddlersHeading = "These are the other tiddlers that link to this tiddler.";
}

})(jQuery);
//}}}
Radiologia
<hr/>
[[Resumos]]
[[CasosdeInteresse]]
/*{{{*/
body {
	font-size: 1em;
	font-family: helvetica, arial, sans-serif;
	background-color: #fff;
	color: [[ColorPalette::Foreground]];
}

body ul { margin: 0; }

#popup {
	background-color: [[ColorPalette::TertiaryPale]];
}

#popup.confirmationPopup, .followList {
	font-size: 0.8em;
	padding: 1em;
	border: solid 1px [[ColorPalette::SecondaryMid]];
	background-color: [[ColorPalette::SecondaryPale]];
}

.followList .listTitle {
	text-decoration: underline;
}

#popup .followTiddlersList a {
	display: inline;
	padding: 0;
}

#popup li a {
	color: [[ColorPalette::PrimaryMid]];
	font-weight: bold;
}

#popup li a:hover {
	color: [[ColorPalette::PrimaryPale]];
	background: [[ColorPalette::PrimaryMid]];
}

#popup li.listTitle {
	border-bottom: 1px solid #000;
	font-weight: bold;
	margin-bottom: 10px;
}

#popup.followList {
	margin-left: 50px;
	margin-top: -30px;
}

.followTiddlersList .label {
	display: block;
	left: 10px;
	top: 0px;
	line-height: 16px;
	position: relative;
}

#popup .followTiddlersList .siteIcon{
	height: auto;
}

#popup .followTiddlersList li{
	clear: both;
	display: block;
	height: 48px;
	margin-bottom: 8px;
	position: relative;
}

#popup .followTiddlersList a{
	display: inline;
}

#displayArea {
	margin: 0;
	top: 0px;
	left: 0px;
	width: 100%;
	position: relative;
}

.revisionCloak {
	position: absolute;
	position: fixed !important;
	height: 100%;
	width: 100%;
	top: 0;
	left: 0;
	border: 0;
	margin: 0;
	padding: 0;
	opacity: 0.5;
	filter: alpha(opacity=50);
	background-color: #000;
}

/* *** Header *** */
.header {
	position: relative;
	background-color: [[ColorPalette::PrimaryMid]];
	_width: 100%; /* ie 6 demands */
}

.headerForeground {
	background-color: [[ColorPalette::PrimaryMid]];
	float: left;
	margin: 24px 16px 0px 72px;
	padding: 0;
	position: relative;
	top: 0;
	_width: 70%; /*ie6: needed for the background to actually be transparent*/
	_background-color: transparent; /*ie6: needed to show the search box*/
}

.clearFloat {
	clear: both;
}

#contentWrapper {
	position: relative;
	padding-top: 1px;
	top: -1px;
}

#tiddlerDisplay {
	_position: relative; /* ie 6*/
}

.siteTitle {
	clear: both;
	display: block;
	font-size: 32px;
	font-weight: bold;
	line-height: 32px;
}

.siteSubtitle {
	display: block;
	font-size: 14px;
	height: 16px;
	margin-bottom: 8px;
}

#sidebarSearch {
	padding: 0;
	position: absolute;
	right: 80px;
	top: 8px;
	width: 176px;
}

#sidebarSearch .txtOptionInput {
	width: 100%;
	margin-top: 5px;
	_color: #bbb; /* ie6 danger */
}

#sidebarSearch .txtOptionInput:focus {
	color: #000;
}

#sidebarSearch .searchButton {
	display: none;
}

/* *** Menu Bar *** */

#mainMenu {
	position: static;
	text-align: left;
	margin-left: 72px;
	float: left;
	width: auto;
	padding: 0;
	font-size: 1em;
	line-height: normal;
}

#mainMenu a {
	color: #fff;
	padding: 8px;
	font-size: 0.9em;
	margin-right: 16px;
}

#mainMenu a:hover {
	background-color: [[ColorPalette::PrimaryMid]];
	color: [[ColorPalette::Background]]
}

#sidebarOptions {
	margin-right: 72px;
	float: right;
	font-size: 1.1em;
	line-height: 1.6em;
	min-height: 1em;
	padding-top: 0;
}

#sidebarOptions a {
	margin-right: 8px;
}

.confirmationPopup .button,
#sidebarOptions .button {
	cursor: pointer;
	line-height: 1.4em;
	text-align: center;
	margin-right: 8px;
	margin-left:-2px;
}

.confirmationPopup .button {
	font-size: 0.9em;
	padding: 2px;
}

#sidebarOptions .button {
	font-size: 0.7em;
	float: left;
	width: 80px;
	padding: 0px;
        color: #fff;
}

.confirmationPopup a.button,
#sidebarOptions a {
	border: none;
	margin: 0 0.2em;
	padding: 0.6em 0.25em;
	display: inline;
	color: #666;
}

.confirmationPopup a.button:hover,
#sidebarOptions a:hover {
	color: #000;
}

.confirmationPopup a.button:active,
#sidebarOptions a:active {
	border: solid 1px [[ColorPalette::PrimaryMid]];
	background-color: #fff;
	background: -webkit-gradient( linear, left bottom, left top, color-stop(0.1,rgb(200,200,200)), color-stop(1, rgb(100,100,100)));
	background: -moz-linear-gradient(center bottom , rgb(200,200,200) 10%,rgb(100,100,100) 100%) repeat scroll 0 0 transparent;
}
/* *** Sidebar *** */

#sidebar .wizard table {
	margin: 0px;
}

.tabContents .listTitle:first-child {
	margin-top: 0px;
}

#menuBar {
	background: [[ColorPalette::PrimaryLight]];
	left: 0;
	right: 0;
	position: relative;
	margin: 0;
	padding: 0.5em 0 0.5em 0;
	min-height: 1em;
	overflow: hidden;
	_width: 100%; /* for ie 6 */
}

#sidebarOptions a.button:hover {
	color: [[ColorPalette::PrimaryPale]];
    background: [[ColorPalette::PrimaryMid]];
}

#tiddlerDisplay, #searchResults {
	margin: 16px 448px 0 72px;
}

#sidebarTabs {
	position: absolute;
	right: 72px;
	width: 352px;
	top: 0;
}

#sidebarTabs .tabsetWrapper .tabset {
	width: 87px;
	border-top: 1px solid [[ColorPalette::PrimaryPale]];
	border-left: 1px solid [[ColorPalette::PrimaryPale]];
	border-bottom: 1px solid [[ColorPalette::PrimaryPale]];
	height: auto;
	float: left;
	word-wrap: break-word;
	top: 0;
	padding: 0;
}

#sidebarTabs .tabsetWrapper .tabContents {
	background-color: [[ColorPalette::PrimaryPale]];
	border: 3px solid [[ColorPalette::PrimaryMid]];
	width: 242px;
	_width: 238px;
	left: -3px;
	_left: -5px;
	position: relative;
	min-height: 34em;
	padding: 8px;
	font-size: 0.8em;
}

/* ---- Side style --- */

#sidebarTabs .tabsetWrapper .tabset .tab {
	font-size: 0.9em;
	padding: 0.7em 8px 0.5em;
	color: #fff;
	background: [[ColorPalette::PrimaryLight]];
	border: none;
	line-height: 16px;
	position: relative;
	display: block;
	margin: 0;
}

#sidebarTabs .tabsetWrapper .tabset .tabSelected {
	color: [[ColorPalette::PrimaryMid]];
	background: [[ColorPalette::PrimaryPale]];
	border-top: 3px solid [[ColorPalette::PrimaryMid]];
	border-bottom: 3px solid [[ColorPalette::PrimaryMid]];
	border-left: 3px solid [[ColorPalette::PrimaryMid]];
	z-index: 10;
	margin-top: -1px;
	font-weight: bold;
}

#sidebarTabs .tabContents li {
	border: none;
	margin-left: 0;
	word-wrap: break-word;
}

.tabContents .timeline {
	background: [[ColorPalette::PrimaryPale]];
	margin-bottom: 8px;
}

#sidebarTabs .timeline li.listTitle {
	color: #132E43;
	margin-left: 8px 0;
	padding: 0.3em 0.11em;
	font-size: 1em;
	border-bottom: none;
}

#sidebarTabs .tabContents li a {
	display: block;
	text-align: left;
	margin: 0 0 1px 0;
	padding: 0.3em 1em;
	background: [[ColorPalette::PrimaryPale]];
}

#sidebarTabs .tabsetWrapper .tabset a:hover,
#sidebarTabs .tabContents li a:hover {
	color: [[ColorPalette::PrimaryPale]];
	background: [[ColorPalette::PrimaryMid]];
}

/* Activity Stream */
#sidebarTabs .tabContents .activityStream .feedItem a {
	display: inline-block;
	padding: 0;
	background: none;
}

/* ---- Tagging box --- */
.tagInfo {
	border: 1px solid #cccccc;
	padding: 10px 15px;
	-moz-box-shadow: 0 2px 2px rgba(0, 0, 0, 0.2);
	box-shadow: 0 2px 2px rgba(0,0,0,0.2);
	color: [[ColorPalette::TertiaryMid]];
	background: -moz-linear-gradient(100% 100% 90deg, #f4f4f4, #e5e5e5);
	background: -webkit-gradient(linear, left top, right top, from(#e5e5e5), to(#f4f4f4));
	margin-top: 1em;
	font-size: 13px;
	margin: 0 0 0 56px;
}

.tagInfo ul {
	list-style: none;
	padding-left: 2.2em;
}

.tagInfo ul li {
	display: inline;
}

.tagInfo ul li.listTitle,
.tagInfo .tagging ul li.listTitle {
	color: [[ColorPalette::PrimaryMid]];
	font-size: 13px;
}

.tagInfo ul li a {
	border: none;
}

.tagInfo .tagging ul li {
	float: none;
	display: inline-block;
}

.tagInfo .tagging {
	padding: 0;
}

.viewRevision .toolbar {
	right: 48px;
	top: 8px;
}

.viewRevision .modifierIcon img,
.viewRevision .modifierIcon svg {
	margin-right: 8px;
}

.viewRevision .toolbar svg {
	width: 32px;
	height: 32px;
}

/* --- IE hacks from lattice --- */

/* ie hacks */
* html #menuBar {
	margin-bottom: 8px;
}
.toolbar .svgIconText {
	*display: inline;
}

div.tiddler .toolbar a {
	cursor: pointer;
	float: left\9;
	display: inline\9;
}

* html .toolbar {
	right: 8px;
}
* html .followButton a {
	margin-top: 0px;
	margin-right: 8px;
}
* html #tiddlerDisplay {
	margin-top: 0px;
}

/* for printing purposes */
@media print {
	#mainMenu,
	#sidebar,
	#messageArea,
	.toolbar,
	.followPlaceHolder,
	#backstageButton,
	#backstageArea,
	#sidebarTabs,
	#sidebarSearch .txtOptionInput,
	#sidebarOptions {
		display: none !important;
	}
	#displayArea {
		margin: 1em 1em 0em;
	}
	noscript {
		display:none; /* Fixes a feature in Firefox 1.5.0.2 where print preview displays the noscript content */
	}
	#tiddlerDisplay {
		margin: 16px 16px;
	}
}

@media all and (max-width: 960px){
	#tiddlerDisplay,
	#searchResults {
		margin: 16px 366px 0 16px;
	}

	#mainMenu {
		margin-left: 16px;
	}

	.headerForeground {
		margin-left: 16px;
	}

	#sidebarSearch {
		right: 16px;
	}

	#sidebarOptions {
		margin-right: 16px;
	}

	#sidebarTabs {
		right: 16px;
		width: 326px;
	}

	#sidebarTabs .tabsetWrapper .tabset {
		font-size: 0.9em;
		width: 77px;
	}

	#sidebarTabs .tabsetWrapper .tabContents {
		width: 226px;
		_width: 222px;
	}

	#sidebarTabs .tabContents li a {
		font-size: 0.9em;
	}
}
/*}}}*/
[[StyleSheetTiddler]]
!usage
{{{[img[f4-u1.0-B978-0-443-10163-2..50005-1..gr6.jpg]]}}}
[img[f4-u1.0-B978-0-443-10163-2..50005-1..gr6.jpg]]
!notes
Carcinoma of the pancreas (A) T2-weighted axial image showing a mildly hyperintense lesion within the pancreatic tail (arrows), which appears hypointense (arrows) on the (B) fat-suppressed T1-weighted MR image. (C) Immediately following IV extracellular gadolinium contrast administration, the mass is well seen as a hypointense mass (arrows) against the enhancing pancreatic parenchyma using a fat-suppressed T1-weighted imaging sequence.
!type
image/jpeg
!file
file:////Users/iki/Desktop/f4-u1.0-B978-0-443-10163-2..50005-1..gr6.jpg
!url

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Frequency and severity of repeat contrast reactions in premedicated patients (so-called  breakthrough reactions) was recently studied resulting in several important conclusions: 
#Breakthrough reaction severity, signs, and symptoms are most often similar to the index reaction
#The majority of low-osmolality contrast injections in  remedicated patients with a prior breakthrough reaction will not result in a repeat breakthrough reaction
#Patients with a mild index reaction have an extremely low risk of developing a severe breakthrough reaction
#Patients with a moderate or severe index or breakthrough reaction are at higher risk for developing another moderate or severe reaction should breakthrough occur
#Severe allergies to any other substance (which includes IV iodinated contrast) are associated with a somewhat higher risk of developing a moderate or severe breakthrough reaction. 
**This is also true of patients with use of oral corticosteroids
!!Issue
—In many laboratories, stratification or diagnosis of minor (<50%) degrees of ICA stenosis is based on Doppler findings.
!!Recommendation
—Because Doppler is inaccurate for subcategorizing stenoses less than 50%, these stenoses should be reported under a single category as “<50% stenosis.” Subcategories for minor degrees of stenosis should not be used.
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—Other common technical shortcomings in ICA examinations include incorrect positioning of the sample volume, incomplete sampling through an area of stenosis, and failure to depict the distal end of a carotid plaque.
!!Recommendation.
Care should be taken to position the sample volume within the area of greatest stenosis. The ICA must be sampled through the region of stenosis completely until the distal end of the plaque is visualized, to ensure that the site of highest velocity has been located.
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The three major vessels interrogated at liver Doppler US are the 
**hepatic arteries
***pulsatile
***antegrade
***low-resistance vessel, with an expected RI ranging from 0.55 to 0.7
**hepatic veins
***the bulk of hepatic venous flow is antegrade
****Although there are moments of retrograde flow, the majority of blood flow must be antegrade to get back to the heart
***pressure changes in the right atrium will be transmitted directly to the hepatic veins
****not applicable in cases of cirrhosis, since the fibrotic parenchyma compresses the veins and limits free transmission of right atrial pressure changes
***W shape of the hepatic venous waveform
***normally phasic and predominantly antegrade.
**portal veins
***physiologic flow should always be antegrade
***hepatic venous pulsatility is partially transmitted to the portal veins through the hepatic sinusoids,
****accounts for the cardiac variability seen in this waveform
***flow velocity in this vessel is relatively low (16–40 cm/sec) 
***antegrade and hepatopetal
***gently undulate and always remain above the baseline
***The degree of undulation is highly variable but may be quantified with a PI
****PI is used to quantify pulsatility. 
*****Normal phasicity results in a PI greater than 0.5
*****lower calculated PIs correspond to higher pulsatility
****note that the PI calculation for the portal vein is different from that for the hepatic arteries (arterial PI = (V1–V2)/Vmean)
*****In the portal veins, the PI is calculated as V2/V1, with V1 normally being greater than 0.5

*Liver disease
**hepatic arteries
***abnormally elevated (RI >0.7) or decreased (RI <0.55) resistance
***High resistance is a nonspecific finding that may be seen in the 
****postprandial state, 
****patients of advanced age, and 
****diffuse peripheral microvascular (arteriolar) compression or 
****disease, as seen in chronic hepatocellular disease (including cirrhosis), 
****hepatic venous congestion, cold ischemia (posttransplantation), and 
****any stage of transplant rejection
***Low hepatic arterial resistance is more specific for disease and has a more limited differential diagnosis, including 
****conditions associated with proximal arterial narrowing (transplant hepatic artery stenosis [anastomosis], 
****atherosclerotic disease [celiac or hepatic], 
****arcuate ligament syndrome) and 
****distal (peripheral) vascular shunts (posttraumatic or iatrogenic arteriovenous fistulas, cirrhosis with portal hypertension and associated arteriovenous or arterioportal shunts, Osler-Weber-Rendu syndrome with arteriovenous fistulas)
**hepatic veins
***Increased pulsatility (pulsatile waveform)
***Caused by tricuspid regurgitation or right-sided heart failure without tricuspid regurgitation
****associated with a pulsatile portal venous waveform 
***Decreased phasicity (decreased pulsatility) and spectral broadening
****inspiration and expiration both affect the systolic/diastolic ratio, and that the Valsalva maneuver can markedly reduce pulsatility, even to the point of nonphasicity
****pathologic causes of nonphasicity
*****cirrhosis, 
*****hepatic vein thrombosis ([[Budd-Chiari syndrome]]), 
*****hepatic veno-occlusive disease, and 
*****hepatic venous outflow obstruction from any cause
****Decreased venous compliance is seen as a waveform with a proportional loss of phasicity
****As long as the a wave remains above the baseline, there is normal phasicity
*****once the a wave goes below the baseline, there is at least mildly decreased phasicity, which has been observed in less than 10% of healthy patients
*****Once the peak of the a wave is at least halfway between the baseline and the peak negative excursion of the waveform, there is at least moderately decreased phasicity
******This degree of decreased phasicity is never normal
*****When the waveform loses all phasic variation (ie, becomes nonphasic) and no component waves can be distinguished, phasicity is severely decreased.
*****Spectral broadening is due to the narrowed caliber of compressed hepatic veins, such as occurs in cirrhosis
******The hepatic veins are large enough that their waveforms should normally have a thin spectral window
***Absent (aphasic) hepatic venous flow
****venous outflow obstruction ([[Budd-Chiari syndrome]])
****this syndrome may also manifest with 
*****(a) incomplete obstruction, which may have a spectral waveform with decreased phasicity (eg, nonphasicity); or
*****(b) increased flow velocities and turbulence at the level of stenosis
****approximately 25% of patients with [[Budd-Chiari syndrome]] also have portal vein thrombosis
**portal veins
***Normal and abnormal portal venous phasicity
***hepatopetal (physiologic) or hepatofugal (pathologic)
***Abnormal (pathologic) portal venous flow
****Increased pulsatility (pulsatile waveform)
*****In the normal state, the arteries do not contribute significantly to pulsatility, whereas the hepatic veins contribute as described earlier
*****Anything that abnormally transmits pressure to the sinusoids will result in a pulsatile portal venous waveform
******tricuspid regurgitation and right-sided CHF transmit pressure and increase pulsatility
******arteriovenous shunting (as seen in severe cirrhosis)
******arteriovenous fistulas (as seen in hereditary hemorrhagic telangiectasia) may have this effect
****Slow portal venous flow
*****diagnostic for [[portal hypertension]], which is diagnosed when peak velocity is less than 16 cm/sec
***Hepatofugal
****diagnostic for portal hypertension from whatever cause.
***Absent (aphasic) portal venous flow
****stagnant flow (portal hypertension)
*****In severe portal hypertension, there is a period of time during the disease course when flow is neither hepatopetal nor hepatofugal, but stagnant
*****absent portal venous flow  at Doppler US
*****increased risk for portal vein thrombosis
****occlusive disease (bland or malignant thrombosis)
*****Hepatocellular carcinoma is the most common cause of malignant thrombosis (tumor thrombus)
*****other possible causes include 
******pancreatic carcinoma, 
******cholangiocarcinoma, 
******metastatic disease, and 
******primary portal venous leiomyosarcoma.
****benign vs malignant portal vein thrombosis 
*****At gray-scale US, both benign and malignant forms typically manifest as an echogenic intraluminal filling defect. 
*****The echogenicity of the filling defect cannot be used to distinguish benign from malignant thrombosis
*****the echogenicity of a clot may vary, depending on its age
*****portal vein enlargement has been described as a gray-scale US feature of malignant thrombosis
******tumor thrombus can be seen in the setting of a normal-sized portal vein
******bland thrombus, when acute, can sometimes enlarge the portal vein
******therefore, portal vein diameter is not considered a reliable distinguishing feature
*****The most reliable distinguishing gray-scale US feature of malignant thrombus is the combination of an echogenic filling defect with an adjacent liver mass.
****In some cases of malignant thrombosis, there may be color signals within the thrombus; this finding has been referred to as the “thread and streak sign” at both CT angiography and color Doppler US
*****arterial (pulsatile) waveforms, which is a specific sign of tumor thrombus
****Another feature of occlusive portal vein thrombosis (especially the nonacute variety) is the development of collateral vessels in or around the occluded portal vein; this condition is referred to as cavernous transformation
*****tends to be a marker for bland thrombus
*****these collateral vessels usually take a long time (months to years) to develop
*****when patients have tumor thrombus, they usually do not live long enough for this development to occur
*****Nonetheless, cavernous transformation has been documented as occurring within a matter of weeks in occlusive malignant portal vein thrombosis

!!!Causes of Decreased Hepatic Arterial Resistance (RI <0.55)
*Cirrhosis
**Arterial resistance has been shown to be decreased, normal, or increased in cirrhotic patients 
**inflammatory edema, arterial compression by regenerative nodules, and arterial compression by stiff noncompliant (fibrotic) parenchyma, have been thought to increase resistance 
**the “hepatic arterial buffer response” (compensatory small artery proliferation and increased numbers of arteriolar beds) and arteriovenous shunting, are thought to decrease resistance 
**hepatic arterial RI is not useful for diagnosing cirrhosis or predicting its severity

!!!Characteristic color Doppler US finding in Budd-Chiari syndrome
*bicolored, curving hepatic venous collateral vessels
**The two colors are generated by the different drainage pathways in these collateral vessels, since they transmit blood to any other patent vein, whether systemic or portal. 
***Potential systemic drainage pathways are 
****intrahepatic (ie, to other hepatic veins, or to the caudate lobe, which usually has its own hepatic venous drainage to the IVC) or 
****extrahepatic (ie, to subcapsular draining veins)
*Spectral Doppler US of 
**bland thrombus will show no appreciable waveform other than noise; however, as in 
**malignant portal vein thrombosis, arterial waveforms may be seen in tumor thrombus. 

*Recent research indicates that contrast material–enhanced US may offer a diagnostic advantage in the detection of malignant hepatic and portal vein thrombosis compared with conventional gray-scale, color Doppler, and spectral Doppler US 

*History of “kidney disease” as an adult, including tumor and transplant .
*Family history of kidney failure. 
*Diabetes treated with insulin or other medications prescribed by a licensed physician
*Paraproteinemia syndromes or diseases (e.g.,multiple myeloma)
*Collagen vascular disease (e.g., scleroderma,systemic lupus erythematosa)
*Prior renal surgery. 
*Certain medications:
**Metformin or metformin-containing drug combinations
**Chronic or high dose use of non-steroidal anti-inflammatory drugs. 
**Regular use of nephrotoxic medications, such as aminoglycosides
*All inpatients

*Although there is little data to support a specific time interval between the date of measurement of the serum creatinine and the proposed contrast administration, in otherwise stable outpatients, many authorities will accept an interval of 30 days as being sufficiently recent to proceed with contrast administration
*For inpatients, a much shorter interval seems prudent
!Patient Surveillance
The panel discussed the issue of appropriate follow-up of asymptomatic patients with known ICA stenosis, as well as of patients at high risk for ICA stenosis or stroke. The panelists agreed that patients with a >=50% stenosis of the ICA who do not undergo carotid endarterectomy and who may be candidates for prophylactic carotid endarterectomy should be followed up at 6–12-month intervals, and high-risk patients with visible plaque and <50% stenosis should be evaluated every 1–2 years. Patients who have normal carotid US studies but marked risk factors might be evaluated every 3–5 years. In all cases of follow-up or surveillance, a complete examination should be performed. 
Follow-up studies should be compared with results from prior examinations.
Research Topics
The panel identified several important unanswered questions that merit future research.
#What is the role of ICA plaque characterization in carotid disease?
#What is the role of the ICA intimalmedial thickness? There are several ongoing large clinical trials in which the intimal-medial thickness is being evaluated as a marker of atherosclerotic disease, but there are not yet enough data to establish the role of this measurement in the assessment of carotid disease in individual patients.
#At follow-up examination, how much of a change in estimated ICA stenosis or ICA PSV should be considered relevant?
#What criteria should be used to assess patients after ICA surgery or stent placement?
#Should US be used to screen for carotid disease? 

Other issues that need to be addressed include the following:
#There is considerable variation in Doppler measurements from machine to machine and manufacturer to manufacture. This should be rectified, because such variation leads to inconsistencies and inaccuracies in diagnosing ICA stenosis. 
#Phantoms for Doppler US need to be developed to facilitate calibration of Doppler US equipment.
#Improved methods for calculating velocity with angle correction should be developed to eliminate or minimize the inconsistency in velocity measurements as the Doppler angle of insonation is changed.
#Reliable quality assessment methods should be developed so that laboratories can assess their performance of the carotid US examination. This should lead to greater consistency in the performance of carotid US within each laboratory, as well as from laboratory to laboratory.
!usage
{{{[img[f4-u1.0-B978-0-443-10163-2..50005-1..gr2.png]]}}}
[img[f4-u1.0-B978-0-443-10163-2..50005-1..gr2.png]]
!notes
Dynamic T1-weighted MR images obtained using a 3D volume interpolated technique after IV bolus of non-specific extracellular gadolinium chelate. Imaging was performed in the (A) arterial, (B) portovenous, (C) interstitial and (D) delayed (10 min) phases of hepatic enhancement. Note the discontinuous peripheral nodular enhancement of the lesion (arrows) in segment VI of the right lobe, which increases centripetally, typical of a haemangioma. Lesion characterization is possible by evaluating the rate and pattern of contrast enhancement.
!type
image/png
!file
file:////Users/iki/Desktop/f4-u1.0-B978-0-443-10163-2..50005-1..gr2.png
!url

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