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<meta name="DC.Title" content="Cerebral Venous Thrombosis: Diagnostic Accuracy of Combined, Dynamic and Static, Contrast-Enhanced 4D MR Venography" />
<meta name="DC.Identifier" content="10.3174/ajnr.A1869" />
<meta name="DC.Date" content="2010-03-01" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
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Indicates open access to non-subscribers at www.ajnr.org" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: MR including MRV is an established method to diagnose CVT. However, it remains unsettled which MR imaging modalities offer the highest diagnostic accuracy. We evaluated the accuracy of a combined, dynamic (1.5 seconds per dataset) and static (voxel size, 1.1 × 0.9 × 1.5 mm), contrast-enhanced MRV method (combo-4D MRV) relative to other established MR/MRV modalities.

MATERIALS AND METHODS: A total of 39 patients with CVT ( n = 20) and control subjects ( n = 19) underwent combo-4D MRV, 2D TOF MRV, GRE imaging, and T2W imaging. For these modalities, diagnostic accuracy (ROCs) for CVT affecting 53 out of 234 predefined venous segments was determined. Sensitivity and specificity were separately calculated for different stages of CVT (acute/subacute/chronic).

RESULTS: Combo-4D MRV showed the highest accuracy (AUC, 0.99 [95% CI, 0.97–1.0]; sensitivity, 97% [84%–100%]) for thrombosed dural sinuses. For all thrombosed segments including cortical veins, its sensitivity was best (76% [64%–84%]; AUC, 0.92 [0.88–0.96]), followed by TOF MRV (72% [59%–81%]; AUC, 0.93 [0.88–0.97]). Even for chronic CVT, it showed a relatively high sensitivity of 67% (30%–90%). For thrombosed cortical veins alone, GRE images achieved the highest sensitivity (66% [46%–81%]; AUC, 0.88 [0.78–0.97]). Specificities of all modalities ranged from 96% to 99%.

CONCLUSIONS: Combo-4D MRV showed an excellent accuracy for the diagnosis of dural sinus thrombosis. The analysis of dynamic patterns of contrast enhancement in dural sinuses appeared useful to identify chronic thrombosis. To diagnose thrombosed cortical veins, GRE images should primarily be analyzed.

AF
:   acceleration factor
AUC
:   area under the respective reader-specific ROC curve
CI
:   confidence interval
CVT
:   cerebral venous thrombosis
DSA
:   digital subtraction angiography
FA
:   flip angle
GRE
:   gradient recalled-echo
MRV
:   MR venography
NA
:   number of averages
MIP
:   maximum intensity projection
MPRAGE
:   magnetization-prepared rapid acquisition of gradient echo
ROC
:   receiver operating characteristic
T2W
:   T2-weighted
TA
:   acquisition time
TOF
:   time-of-flight
VIBE
:   volumetric interpolated brain examination
TSE
:   turbo spin-echo" />
<meta name="DC.Contributor" content="S. Meckel" />
<meta name="DC.Contributor" content="C. Reisinger" />
<meta name="DC.Contributor" content="J. Bremerich" />
<meta name="DC.Contributor" content="D. Damm" />
<meta name="DC.Contributor" content="M. Wolbers" />
<meta name="DC.Contributor" content="S. Engelter" />
<meta name="DC.Contributor" content="K. Scheffler" />
<meta name="DC.Contributor" content="S.G. Wetzel" />
<meta name="article:published_time" content="2010-03-01" />
<meta name="article:section" content="Brain" />
<meta name="citation_title" content="Cerebral Venous Thrombosis: Diagnostic Accuracy of Combined, Dynamic and Static, Contrast-Enhanced 4D MR Venography" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;MR including MRV is an established method to diagnose CVT. However, it remains unsettled which MR imaging modalities offer the highest diagnostic accuracy. We evaluated the accuracy of a combined, dynamic (1.5 seconds per dataset) and static (voxel size, 1.1 × 0.9 × 1.5 mm), contrast-enhanced MRV method (combo-4D MRV) relative to other established MR/MRV modalities.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;A total of 39 patients with CVT (&lt;i&gt;n&lt;/i&gt; = 20) and control subjects (&lt;i&gt;n&lt;/i&gt; = 19) underwent combo-4D MRV, 2D TOF MRV, GRE imaging, and T2W imaging. For these modalities, diagnostic accuracy (ROCs) for CVT affecting 53 out of 234 predefined venous segments was determined. Sensitivity and specificity were separately calculated for different stages of CVT (acute/subacute/chronic).&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;Combo-4D MRV showed the highest accuracy (AUC, 0.99 [95% CI, 0.97–1.0]; sensitivity, 97% [84%–100%]) for thrombosed dural sinuses. For all thrombosed segments including cortical veins, its sensitivity was best (76% [64%–84%]; AUC, 0.92 [0.88–0.96]), followed by TOF MRV (72% [59%–81%]; AUC, 0.93 [0.88–0.97]). Even for chronic CVT, it showed a relatively high sensitivity of 67% (30%–90%). For thrombosed cortical veins alone, GRE images achieved the highest sensitivity (66% [46%–81%]; AUC, 0.88 [0.78–0.97]). Specificities of all modalities ranged from 96% to 99%.&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;Combo-4D MRV showed an excellent accuracy for the diagnosis of dural sinus thrombosis. The analysis of dynamic patterns of contrast enhancement in dural sinuses appeared useful to identify chronic thrombosis. To diagnose thrombosed cortical veins, GRE images should primarily be analyzed.&lt;/p&gt;" />
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<meta name="twitter:title" content="Cerebral Venous Thrombosis: Diagnostic Accuracy of Combined, Dynamic and Static, Contrast-Enhanced 4D MR Venography" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: MR including MRV is an established method to diagnose CVT. However, it remains unsettled which MR imaging modalities offer the highest diagnostic accuracy. We evaluated the accuracy of a combined, dynamic (1.5 seconds per dataset) and static (voxel size, 1.1 × 0.9 × 1.5 mm), contrast-enhanced MRV method (combo-4D MRV) relative to other established MR/MRV modalities.

MATERIALS AND METHODS: A total of 39 patients with CVT ( n = 20) and control subjects ( n = 19) underwent combo-4D MRV, 2D TOF MRV, GRE imaging, and T2W imaging. For these modalities, diagnostic accuracy (ROCs) for CVT affecting 53 out of 234 predefined venous segments was determined. Sensitivity and specificity were separately calculated for different stages of CVT (acute/subacute/chronic).

RESULTS: Combo-4D MRV showed the highest accuracy (AUC, 0.99 [95% CI, 0.97–1.0]; sensitivity, 97% [84%–100%]) for thrombosed dural sinuses. For all thrombosed segments including cortical veins, its sensitivity was best (76% [64%–84%]; AUC, 0.92 [0.88–0.96]), followed by TOF MRV (72% [59%–81%]; AUC, 0.93 [0.88–0.97]). Even for chronic CVT, it showed a relatively high sensitivity of 67% (30%–90%). For thrombosed cortical veins alone, GRE images achieved the highest sensitivity (66% [46%–81%]; AUC, 0.88 [0.78–0.97]). Specificities of all modalities ranged from 96% to 99%.

CONCLUSIONS: Combo-4D MRV showed an excellent accuracy for the diagnosis of dural sinus thrombosis. The analysis of dynamic patterns of contrast enhancement in dural sinuses appeared useful to identify chronic thrombosis. To diagnose thrombosed cortical veins, GRE images should primarily be analyzed.

AF
:   acceleration factor
AUC
:   area under the respective reader-specific ROC curve
CI
:   confidence interval
CVT
:   cerebral venous thrombosis
DSA
:   digital subtraction angiography
FA
:   flip angle
GRE
:   gradient recalled-echo
MRV
:   MR venography
NA
:   number of averages
MIP
:   maximum intensity projection
MPRAGE
:   magnetization-prepared rapid acquisition of gradient echo
ROC
:   receiver operating characteristic
T2W
:   T2-weighted
TA
:   acquisition time
TOF
:   time-of-flight
VIBE
:   volumetric interpolated brain examination
TSE
:   turbo spin-echo" />
<meta name="og-title" property="og:title" content="Cerebral Venous Thrombosis: Diagnostic Accuracy of Combined, Dynamic and Static, Contrast-Enhanced 4D MR Venography" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/31/3/527" />
<meta name="og-site-name" property="og:site_name" content="American Journal of Neuroradiology" />
<meta name="og-description" property="og:description" content="BACKGROUND AND PURPOSE: MR including MRV is an established method to diagnose CVT. However, it remains unsettled which MR imaging modalities offer the highest diagnostic accuracy. We evaluated the accuracy of a combined, dynamic (1.5 seconds per dataset) and static (voxel size, 1.1 × 0.9 × 1.5 mm), contrast-enhanced MRV method (combo-4D MRV) relative to other established MR/MRV modalities.

MATERIALS AND METHODS: A total of 39 patients with CVT ( n = 20) and control subjects ( n = 19) underwent combo-4D MRV, 2D TOF MRV, GRE imaging, and T2W imaging. For these modalities, diagnostic accuracy (ROCs) for CVT affecting 53 out of 234 predefined venous segments was determined. Sensitivity and specificity were separately calculated for different stages of CVT (acute/subacute/chronic).

RESULTS: Combo-4D MRV showed the highest accuracy (AUC, 0.99 [95% CI, 0.97–1.0]; sensitivity, 97% [84%–100%]) for thrombosed dural sinuses. For all thrombosed segments including cortical veins, its sensitivity was best (76% [64%–84%]; AUC, 0.92 [0.88–0.96]), followed by TOF MRV (72% [59%–81%]; AUC, 0.93 [0.88–0.97]). Even for chronic CVT, it showed a relatively high sensitivity of 67% (30%–90%). For thrombosed cortical veins alone, GRE images achieved the highest sensitivity (66% [46%–81%]; AUC, 0.88 [0.78–0.97]). Specificities of all modalities ranged from 96% to 99%.

CONCLUSIONS: Combo-4D MRV showed an excellent accuracy for the diagnosis of dural sinus thrombosis. The analysis of dynamic patterns of contrast enhancement in dural sinuses appeared useful to identify chronic thrombosis. To diagnose thrombosed cortical veins, GRE images should primarily be analyzed.

AF
:   acceleration factor
AUC
:   area under the respective reader-specific ROC curve
CI
:   confidence interval
CVT
:   cerebral venous thrombosis
DSA
:   digital subtraction angiography
FA
:   flip angle
GRE
:   gradient recalled-echo
MRV
:   MR venography
NA
:   number of averages
MIP
:   maximum intensity projection
MPRAGE
:   magnetization-prepared rapid acquisition of gradient echo
ROC
:   receiver operating characteristic
T2W
:   T2-weighted
TA
:   acquisition time
TOF
:   time-of-flight
VIBE
:   volumetric interpolated brain examination
TSE
:   turbo spin-echo" />
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    <div class="highwire-article-citation highwire-citation-type-highwire-article node9605--7" data-node-nid="9605" id="top-node-9605--81737330042" data-pisa="ajnr;31/3/527" data-pisa-master="ajnr;ajnr.A1869" data-apath="/ajnr/31/3/527.atom" data-hw-author-tooltip-instance="highwire_author_tooltip"><div class="highwire-cite highwire-cite-highwire-article highwire-citation-jcore-article-title-complete clearfix has-author-tooltip highwire-citation-highwire-article-top-a">
  
  
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      <h1 class="highwire-cite-title" id="page-title">Cerebral Venous Thrombosis: Diagnostic Accuracy of Combined, Dynamic and Static, Contrast-Enhanced 4D MR Venography</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">S. Meckel</span>, <span class="highwire-citation-author" data-delta="1">C. Reisinger</span>, <span class="highwire-citation-author" data-delta="2">J. Bremerich</span>, <span class="highwire-citation-author" data-delta="3">D. Damm</span>, <span class="highwire-citation-author" data-delta="4">M. Wolbers</span>, <span class="highwire-citation-author" data-delta="5">S. Engelter</span>, <span class="highwire-citation-author" data-delta="6">K. Scheffler</span> and <span class="highwire-citation-author" data-delta="7">S.G. Wetzel</span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">March 2010,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">31 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(3) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">527-535; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A1869 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-9605--81737330042" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">S. Meckel </div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=S.%2BMeckel%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Meckel%20S&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link last"><a href="/search/author1%3AS.%2BMeckel%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">C. Reisinger </div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=C.%2BReisinger%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Reisinger%20C&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link last"><a href="/search/author1%3AC.%2BReisinger%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">J. Bremerich </div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=J.%2BBremerich%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Bremerich%20J&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link last"><a href="/search/author1%3AJ.%2BBremerich%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-3"><div class="author-tooltip-name">D. Damm </div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=D.%2BDamm%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Damm%20D&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link last"><a href="/search/author1%3AD.%2BDamm%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-4"><div class="author-tooltip-name">M. Wolbers </div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=M.%2BWolbers%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Wolbers%20M&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link last"><a href="/search/author1%3AM.%2BWolbers%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-5"><div class="author-tooltip-name">S. Engelter </div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=S.%2BEngelter%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Engelter%20S&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link last"><a href="/search/author1%3AS.%2BEngelter%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-6"><div class="author-tooltip-name">K. Scheffler </div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=K.%2BScheffler%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Scheffler%20K&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link last"><a href="/search/author1%3AK.%2BScheffler%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-7"><div class="author-tooltip-name">S.G. 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    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-volume highwire-cite-metadata">vol. 31 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">no. 3 </span><span  class="highwire-cite-metadata-page-string highwire-cite-metadata">527-535 </span></div>
  
  
  
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    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0"><span class="nlm-given-names">S.</span> <span class="nlm-surname">Meckel</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">C.</span> <span class="nlm-surname">Reisinger</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">J.</span> <span class="nlm-surname">Bremerich</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">D.</span> <span class="nlm-surname">Damm</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">M.</span> <span class="nlm-surname">Wolbers</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">S.</span> <span class="nlm-surname">Engelter</span></span>, <span class="highwire-citation-author" data-delta="6"><span class="nlm-given-names">K.</span> <span class="nlm-surname">Scheffler</span></span>, <span class="highwire-citation-author" data-delta="7"><span class="nlm-given-names">S.G.</span> <span class="nlm-surname">Wetzel</span></span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-oa-ind highwire-cite-metadata"><i class="highwire-oa-indicator"></i> </span><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">Mar 2010, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">31 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(3) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">527-535; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A1869 </span></div>
  
  
  
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