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<meta name="DC.Title" content="3D Black-Blood Luminal Angiography Derived from High-Resolution MR Vessel Wall Imaging in Detecting MCA Stenosis: A Preliminary Study" />
<meta name="DC.Identifier" content="10.3174/ajnr.A5770" />
<meta name="DC.Date" content="2018-10-01" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: 3D high-resolution vessel wall imaging is increasingly used for intracranial arterial diseases. This study compared the diagnostic performance of black-blood luminal angiography derived from 3D vessel wall imaging with source images of vessel wall imaging and TOF-MRA in detecting middle cerebral artery stenosis.

MATERIALS AND METHODS: Sixty-two patients with suspected MCA atherosclerosis underwent TOF-MRA, vessel wall imaging, and CTA. Intracranial black-blood luminal angiography was created from source images of vessel wall imaging using minimum intensity projection. The degree and length of MCA stenosis were measured on source images of vessel wall imaging, TOF-MRA, and black-blood luminal angiography and compared using CTA as a reference standard.

RESULTS: The image quality of black-blood luminal angiography was diagnostic in most patients. The intra- and interobserver agreement for both stenosis degree and length measurements was excellent for black-blood luminal angiography. It was comparable with that of source images of vessel wall imaging in grading stenosis. Compared with TOF-MRA, black-blood luminal angiography showed significantly higher sensitivity for the detection of severe stenosis (89.3% versus 64.3%, P = .039) and higher specificity for the detection of occlusion (95.4% versus 84.6%, P = .039). Lesion length estimated on source images of vessel wall imaging was significantly greater than that measured by CTA and black-blood luminal angiography ( P &lt; .001 and P = .010).

CONCLUSIONS: Black-blood luminal angiography is better than TOF-MRA in detecting severe stenosis and occlusion of the MCA. Compared with source images of vessel wall imaging, it is more accurate in evaluating stenosis length. Black-blood luminal angiography can be produced as a derivative from vessel wall imaging and implemented as an adjunct to vessel wall imaging and TOF-MRA without extra acquisition time.

BBLA
:   black-blood luminal angiography
VWI
:   vessel wall imaging" />
<meta name="DC.Contributor" content="X. Bai" />
<meta name="DC.Contributor" content="P. Lv" />
<meta name="DC.Contributor" content="K. Liu" />
<meta name="DC.Contributor" content="Q. Li" />
<meta name="DC.Contributor" content="J. Ding" />
<meta name="DC.Contributor" content="J. Qu" />
<meta name="DC.Contributor" content="J. Lin" />
<meta name="article:published_time" content="2018-10-01" />
<meta name="article:section" content="Adult Brain" />
<meta name="citation_title" content="3D Black-Blood Luminal Angiography Derived from High-Resolution MR Vessel Wall Imaging in Detecting MCA Stenosis: A Preliminary Study" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;3D high-resolution vessel wall imaging is increasingly used for intracranial arterial diseases. This study compared the diagnostic performance of black-blood luminal angiography derived from 3D vessel wall imaging with source images of vessel wall imaging and TOF-MRA in detecting middle cerebral artery stenosis.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;Sixty-two patients with suspected MCA atherosclerosis underwent TOF-MRA, vessel wall imaging, and CTA. Intracranial black-blood luminal angiography was created from source images of vessel wall imaging using minimum intensity projection. The degree and length of MCA stenosis were measured on source images of vessel wall imaging, TOF-MRA, and black-blood luminal angiography and compared using CTA as a reference standard.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;The image quality of black-blood luminal angiography was diagnostic in most patients. The intra- and interobserver agreement for both stenosis degree and length measurements was excellent for black-blood luminal angiography. It was comparable with that of source images of vessel wall imaging in grading stenosis. Compared with TOF-MRA, black-blood luminal angiography showed significantly higher sensitivity for the detection of severe stenosis (89.3% versus 64.3%, &lt;i&gt;P&lt;/i&gt; = .039) and higher specificity for the detection of occlusion (95.4% versus 84.6%, &lt;i&gt;P&lt;/i&gt; = .039). Lesion length estimated on source images of vessel wall imaging was significantly greater than that measured by CTA and black-blood luminal angiography (&lt;i&gt;P&lt;/i&gt; &amp;lt; .001 and &lt;i&gt;P&lt;/i&gt; = .010).&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;Black-blood luminal angiography is better than TOF-MRA in detecting severe stenosis and occlusion of the MCA. Compared with source images of vessel wall imaging, it is more accurate in evaluating stenosis length. Black-blood luminal angiography can be produced as a derivative from vessel wall imaging and implemented as an adjunct to vessel wall imaging and TOF-MRA without extra acquisition time.&lt;/p&gt;" />
<meta name="citation_journal_title" content="American Journal of Neuroradiology" />
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<meta name="twitter:title" content="3D Black-Blood Luminal Angiography Derived from High-Resolution MR Vessel Wall Imaging in Detecting MCA Stenosis: A Preliminary Study" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: 3D high-resolution vessel wall imaging is increasingly used for intracranial arterial diseases. This study compared the diagnostic performance of black-blood luminal angiography derived from 3D vessel wall imaging with source images of vessel wall imaging and TOF-MRA in detecting middle cerebral artery stenosis.

MATERIALS AND METHODS: Sixty-two patients with suspected MCA atherosclerosis underwent TOF-MRA, vessel wall imaging, and CTA. Intracranial black-blood luminal angiography was created from source images of vessel wall imaging using minimum intensity projection. The degree and length of MCA stenosis were measured on source images of vessel wall imaging, TOF-MRA, and black-blood luminal angiography and compared using CTA as a reference standard.

RESULTS: The image quality of black-blood luminal angiography was diagnostic in most patients. The intra- and interobserver agreement for both stenosis degree and length measurements was excellent for black-blood luminal angiography. It was comparable with that of source images of vessel wall imaging in grading stenosis. Compared with TOF-MRA, black-blood luminal angiography showed significantly higher sensitivity for the detection of severe stenosis (89.3% versus 64.3%, P = .039) and higher specificity for the detection of occlusion (95.4% versus 84.6%, P = .039). Lesion length estimated on source images of vessel wall imaging was significantly greater than that measured by CTA and black-blood luminal angiography ( P &lt; .001 and P = .010).

CONCLUSIONS: Black-blood luminal angiography is better than TOF-MRA in detecting severe stenosis and occlusion of the MCA. Compared with source images of vessel wall imaging, it is more accurate in evaluating stenosis length. Black-blood luminal angiography can be produced as a derivative from vessel wall imaging and implemented as an adjunct to vessel wall imaging and TOF-MRA without extra acquisition time.

BBLA
:   black-blood luminal angiography
VWI
:   vessel wall imaging" />
<meta name="og-title" property="og:title" content="3D Black-Blood Luminal Angiography Derived from High-Resolution MR Vessel Wall Imaging in Detecting MCA Stenosis: A Preliminary Study" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/39/10/1827" />
<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: 3D high-resolution vessel wall imaging is increasingly used for intracranial arterial diseases. This study compared the diagnostic performance of black-blood luminal angiography derived from 3D vessel wall imaging with source images of vessel wall imaging and TOF-MRA in detecting middle cerebral artery stenosis.

MATERIALS AND METHODS: Sixty-two patients with suspected MCA atherosclerosis underwent TOF-MRA, vessel wall imaging, and CTA. Intracranial black-blood luminal angiography was created from source images of vessel wall imaging using minimum intensity projection. The degree and length of MCA stenosis were measured on source images of vessel wall imaging, TOF-MRA, and black-blood luminal angiography and compared using CTA as a reference standard.

RESULTS: The image quality of black-blood luminal angiography was diagnostic in most patients. The intra- and interobserver agreement for both stenosis degree and length measurements was excellent for black-blood luminal angiography. It was comparable with that of source images of vessel wall imaging in grading stenosis. Compared with TOF-MRA, black-blood luminal angiography showed significantly higher sensitivity for the detection of severe stenosis (89.3% versus 64.3%, P = .039) and higher specificity for the detection of occlusion (95.4% versus 84.6%, P = .039). Lesion length estimated on source images of vessel wall imaging was significantly greater than that measured by CTA and black-blood luminal angiography ( P &lt; .001 and P = .010).

CONCLUSIONS: Black-blood luminal angiography is better than TOF-MRA in detecting severe stenosis and occlusion of the MCA. Compared with source images of vessel wall imaging, it is more accurate in evaluating stenosis length. Black-blood luminal angiography can be produced as a derivative from vessel wall imaging and implemented as an adjunct to vessel wall imaging and TOF-MRA without extra acquisition time.

BBLA
:   black-blood luminal angiography
VWI
:   vessel wall imaging" />
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      <div class="highwire-cite-overline"><span  class="highwire-cite-metadata-article-type highwire-cite-metadata">Research Article</span><span class="separator-pipe"></span><span  class="highwire-cite-metadata-art-cat highwire-cite-metadata"><span class="wrapper">Adult Brain</span></span></div>
  
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      <h1 class="highwire-cite-title" id="page-title">3D Black-Blood Luminal Angiography Derived from High-Resolution MR Vessel Wall Imaging in Detecting MCA Stenosis: A Preliminary Study</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">X. Bai</span>, <span class="highwire-citation-author" data-delta="1">P. Lv</span>, <span class="highwire-citation-author" data-delta="2">K. Liu</span>, <span class="highwire-citation-author" data-delta="3">Q. Li</span>, <span class="highwire-citation-author" data-delta="4">J. Ding</span>, <span class="highwire-citation-author" data-delta="5">J. Qu</span> and <span class="highwire-citation-author" data-delta="6">J. Lin</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">October 2018,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">39 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(10) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1827-1832; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A5770 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-63301--63095407" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">X. Bai </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Department of Radiology (X.B., P.L., K.L., J.L.), Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China</div></span></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=X.%2BBai%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=Bai%20X&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"><a href="/search/author1%3AX.%2BBai%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-9092-7824" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for X. Bai</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">P. Lv </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Department of Radiology (X.B., P.L., K.L., J.L.), Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China</div></span></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=P.%2BLv%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=Lv%20P&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"><a href="/search/author1%3AP.%2BLv%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-5163-3604" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for P. Lv</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">K. Liu </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Department of Radiology (X.B., P.L., K.L., J.L.), Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China</div></span></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.%2BLiu%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=Liu%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"><a href="/search/author1%3AK.%2BLiu%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0001-9300-7989" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for K. Liu</a></li></ul></div><div class="author-tooltip-3"><div class="author-tooltip-name">Q. Li </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Departments of Neurosurgery (Q.L.)</div></span></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=Q.%2BLi%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=Li%20Q&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"><a href="/search/author1%3AQ.%2BLi%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0003-2831-3183" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Q. Li</a></li></ul></div><div class="author-tooltip-4"><div class="author-tooltip-name">J. Ding </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>c</span>Neurology (J.D.), Zhongshan Hospital, Fudan University, Shanghai, China</div></span></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.%2BDing%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=Ding%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"><a href="/search/author1%3AJ.%2BDing%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0001-5135-4210" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for J. Ding</a></li></ul></div><div class="author-tooltip-5"><div class="author-tooltip-name">J. Qu </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>d</span>GE Healthcare (J.Q.),Shanghai, China.</div></span></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.%2BQu%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=Qu%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"><a href="/search/author1%3AJ.%2BQu%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0003-2006-1997" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for J. Qu</a></li></ul></div><div class="author-tooltip-6"><div class="author-tooltip-name">J. Lin </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Department of Radiology (X.B., P.L., K.L., J.L.), Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, China</div></span></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.%2BLin%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=Lin%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"><a href="/search/author1%3AJ.%2BLin%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0002-6593-9700" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for J. 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        	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-volume highwire-cite-metadata">Vol. 39</span>, <span  class="highwire-cite-metadata-issue highwire-cite-metadata">Issue 10 </span><div  class="highwire-cite-metadata-pubdate highwire-cite-metadata">1 Oct 2018 </div></div>
      
      
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    	<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">Oct 2018, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">39 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(10) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1827-1832; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A5770 </span></div>
  
  
  
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