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<meta name="DC.Title" content="Extensive White Matter Dysfunction in Cognitively Impaired Patients with Secondary-Progressive Multiple Sclerosis" />
<meta name="DC.Identifier" content="10.3174/ajnr.A3974" />
<meta name="DC.Date" content="2014-10-01" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Cognitive impairment is a common, disabling symptom of MS. We investigated the association between cognitive impairment and WM dysfunction in secondary-progressive multiple sclerosis using DTI.

MATERIALS AND METHODS: Cognitive performance was assessed with a standard neuropsychological battery, the Minimal Assessment of Cognitive Function in Multiple Sclerosis. Cognitive impairment was defined as scoring &gt;1.5 standard deviations below healthy controls on ≥2 subtests. Fractional anisotropy maps were compared against cognitive status using tract-based spatial statistics with threshold-free cluster enhancement.

RESULTS: Forty-five patients with secondary-progressive multiple sclerosis (median age: 55 years, female/male: 27/18, median Expanded Disability Status Scale Score: 6.5) were prospectively recruited. Cognitively impaired patients (25/45) displayed significantly less normalized global GM and WM volumes ( P = .001, P = .024), more normalized T2-weighted and T1-weighted WM lesion volumes ( P = .002, P = .006), and lower WM skeleton fractional anisotropy ( P &lt; .001) than non-impaired patients. Impaired patients also had significantly lower fractional anisotropy ( pcorr &lt; .05) in over 50% of voxels within every major WM tract. The most extensively impinged tracts were the left posterior thalamic radiation (100.0%), corpus callosum (97.8%), and right sagittal stratum (97.5%). No WM voxels had significantly higher fractional anisotropy in patients with cognitive impairment compared with their non-impaired counterparts ( pcorr &gt; .05). After the inclusion of confounders in a multivariate logistic regression, only fractional anisotropy remained a significant predictor of cognitive status.

CONCLUSIONS: Cognitively impaired patients with secondary-progressive multiple sclerosis exhibited extensive WM dysfunction, though preferential involvement of WM tracts associated with cognition, such as the corpus callosum, was apparent. Multivariate analysis revealed that only WM skeleton fractional anisotropy was a significant predictor of cognitive status.

CC
:   corpus callosum
EDSS
:   Expanded Disability Status Scale
FA
:   fractional anisotropy
MNI
:   Montreal Neurological Institute
RRMS
:   relapsing-remitting MS
SPMS
:   secondary-progressive MS
TBSS
:   tract-based spatial statistics
WML
:   white matter lesion" />
<meta name="DC.Contributor" content="P.L. Francis" />
<meta name="DC.Contributor" content="T.L. Chia" />
<meta name="DC.Contributor" content="R. Jakubovic" />
<meta name="DC.Contributor" content="P. O'Connor" />
<meta name="DC.Contributor" content="L. Lee" />
<meta name="DC.Contributor" content="A. Feinstein" />
<meta name="DC.Contributor" content="R.I. Aviv" />
<meta name="article:published_time" content="2014-10-01" />
<meta name="article:section" content="Brain" />
<meta name="citation_title" content="Extensive White Matter Dysfunction in Cognitively Impaired Patients with Secondary-Progressive Multiple Sclerosis" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;Cognitive impairment is a common, disabling symptom of MS. We investigated the association between cognitive impairment and WM dysfunction in secondary-progressive multiple sclerosis using DTI.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;Cognitive performance was assessed with a standard neuropsychological battery, the Minimal Assessment of Cognitive Function in Multiple Sclerosis. Cognitive impairment was defined as scoring &amp;gt;1.5 standard deviations below healthy controls on ≥2 subtests. Fractional anisotropy maps were compared against cognitive status using tract-based spatial statistics with threshold-free cluster enhancement.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;Forty-five patients with secondary-progressive multiple sclerosis (median age: 55 years, female/male: 27/18, median Expanded Disability Status Scale Score: 6.5) were prospectively recruited. Cognitively impaired patients (25/45) displayed significantly less normalized global GM and WM volumes (&lt;i&gt;P&lt;/i&gt; = .001, &lt;i&gt;P&lt;/i&gt; = .024), more normalized T2-weighted and T1-weighted WM lesion volumes (&lt;i&gt;P&lt;/i&gt; = .002, &lt;i&gt;P&lt;/i&gt; = .006), and lower WM skeleton fractional anisotropy (&lt;i&gt;P&lt;/i&gt; &amp;lt; .001) than non-impaired patients. Impaired patients also had significantly lower fractional anisotropy (&lt;i&gt;p&lt;sub&gt;corr&lt;/sub&gt;&lt;/i&gt; &amp;lt; .05) in over 50% of voxels within every major WM tract. The most extensively impinged tracts were the left posterior thalamic radiation (100.0%), corpus callosum (97.8%), and right sagittal stratum (97.5%). No WM voxels had significantly higher fractional anisotropy in patients with cognitive impairment compared with their non-impaired counterparts (&lt;i&gt;p&lt;sub&gt;corr&lt;/sub&gt;&lt;/i&gt; &amp;gt; .05). After the inclusion of confounders in a multivariate logistic regression, only fractional anisotropy remained a significant predictor of cognitive status.&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;Cognitively impaired patients with secondary-progressive multiple sclerosis exhibited extensive WM dysfunction, though preferential involvement of WM tracts associated with cognition, such as the corpus callosum, was apparent. Multivariate analysis revealed that only WM skeleton fractional anisotropy was a significant predictor of cognitive status.&lt;/p&gt;" />
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<meta name="twitter:title" content="Extensive White Matter Dysfunction in Cognitively Impaired Patients with Secondary-Progressive Multiple Sclerosis" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Cognitive impairment is a common, disabling symptom of MS. We investigated the association between cognitive impairment and WM dysfunction in secondary-progressive multiple sclerosis using DTI.

MATERIALS AND METHODS: Cognitive performance was assessed with a standard neuropsychological battery, the Minimal Assessment of Cognitive Function in Multiple Sclerosis. Cognitive impairment was defined as scoring &gt;1.5 standard deviations below healthy controls on ≥2 subtests. Fractional anisotropy maps were compared against cognitive status using tract-based spatial statistics with threshold-free cluster enhancement.

RESULTS: Forty-five patients with secondary-progressive multiple sclerosis (median age: 55 years, female/male: 27/18, median Expanded Disability Status Scale Score: 6.5) were prospectively recruited. Cognitively impaired patients (25/45) displayed significantly less normalized global GM and WM volumes ( P = .001, P = .024), more normalized T2-weighted and T1-weighted WM lesion volumes ( P = .002, P = .006), and lower WM skeleton fractional anisotropy ( P &lt; .001) than non-impaired patients. Impaired patients also had significantly lower fractional anisotropy ( pcorr &lt; .05) in over 50% of voxels within every major WM tract. The most extensively impinged tracts were the left posterior thalamic radiation (100.0%), corpus callosum (97.8%), and right sagittal stratum (97.5%). No WM voxels had significantly higher fractional anisotropy in patients with cognitive impairment compared with their non-impaired counterparts ( pcorr &gt; .05). After the inclusion of confounders in a multivariate logistic regression, only fractional anisotropy remained a significant predictor of cognitive status.

CONCLUSIONS: Cognitively impaired patients with secondary-progressive multiple sclerosis exhibited extensive WM dysfunction, though preferential involvement of WM tracts associated with cognition, such as the corpus callosum, was apparent. Multivariate analysis revealed that only WM skeleton fractional anisotropy was a significant predictor of cognitive status.

CC
:   corpus callosum
EDSS
:   Expanded Disability Status Scale
FA
:   fractional anisotropy
MNI
:   Montreal Neurological Institute
RRMS
:   relapsing-remitting MS
SPMS
:   secondary-progressive MS
TBSS
:   tract-based spatial statistics
WML
:   white matter lesion" />
<meta name="og-title" property="og:title" content="Extensive White Matter Dysfunction in Cognitively Impaired Patients with Secondary-Progressive Multiple Sclerosis" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/35/10/1910" />
<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: Cognitive impairment is a common, disabling symptom of MS. We investigated the association between cognitive impairment and WM dysfunction in secondary-progressive multiple sclerosis using DTI.

MATERIALS AND METHODS: Cognitive performance was assessed with a standard neuropsychological battery, the Minimal Assessment of Cognitive Function in Multiple Sclerosis. Cognitive impairment was defined as scoring &gt;1.5 standard deviations below healthy controls on ≥2 subtests. Fractional anisotropy maps were compared against cognitive status using tract-based spatial statistics with threshold-free cluster enhancement.

RESULTS: Forty-five patients with secondary-progressive multiple sclerosis (median age: 55 years, female/male: 27/18, median Expanded Disability Status Scale Score: 6.5) were prospectively recruited. Cognitively impaired patients (25/45) displayed significantly less normalized global GM and WM volumes ( P = .001, P = .024), more normalized T2-weighted and T1-weighted WM lesion volumes ( P = .002, P = .006), and lower WM skeleton fractional anisotropy ( P &lt; .001) than non-impaired patients. Impaired patients also had significantly lower fractional anisotropy ( pcorr &lt; .05) in over 50% of voxels within every major WM tract. The most extensively impinged tracts were the left posterior thalamic radiation (100.0%), corpus callosum (97.8%), and right sagittal stratum (97.5%). No WM voxels had significantly higher fractional anisotropy in patients with cognitive impairment compared with their non-impaired counterparts ( pcorr &gt; .05). After the inclusion of confounders in a multivariate logistic regression, only fractional anisotropy remained a significant predictor of cognitive status.

CONCLUSIONS: Cognitively impaired patients with secondary-progressive multiple sclerosis exhibited extensive WM dysfunction, though preferential involvement of WM tracts associated with cognition, such as the corpus callosum, was apparent. Multivariate analysis revealed that only WM skeleton fractional anisotropy was a significant predictor of cognitive status.

CC
:   corpus callosum
EDSS
:   Expanded Disability Status Scale
FA
:   fractional anisotropy
MNI
:   Montreal Neurological Institute
RRMS
:   relapsing-remitting MS
SPMS
:   secondary-progressive MS
TBSS
:   tract-based spatial statistics
WML
:   white matter lesion" />
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    <div class="highwire-article-citation highwire-citation-type-highwire-article node13764--5" data-node-nid="13764" id="top-node-13764--61725917895" data-pisa="ajnr;35/10/1910" data-pisa-master="ajnr;ajnr.A3974" data-apath="/ajnr/35/10/1910.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">Extensive White Matter Dysfunction in Cognitively Impaired Patients with Secondary-Progressive Multiple Sclerosis</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">P.L. Francis</span>, <span class="highwire-citation-author" data-delta="1">T.L. Chia</span>, <span class="highwire-citation-author" data-delta="2">R. Jakubovic</span>, <span class="highwire-citation-author" data-delta="3">P. O'Connor</span>, <span class="highwire-citation-author" data-delta="4">L. Lee</span>, <span class="highwire-citation-author" data-delta="5">A. Feinstein</span> and <span class="highwire-citation-author" data-delta="6">R.I. Aviv</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 2014,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">35 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(10) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1910-1915; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A3974 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-13764--61725917895" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">P.L. Francis </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>c</span>Medical Imaging (P.L.F., T.L.C., R.J., R.I.A.), Sunnybrook Health Sciences Centre</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.L.%2BFrancis%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=Francis%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 last"><a href="/search/author1%3AP.L.%2BFrancis%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">T.L. Chia </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>c</span>Medical Imaging (P.L.F., T.L.C., R.J., R.I.A.), Sunnybrook Health Sciences Centre</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=T.L.%2BChia%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=Chia%20T&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%3AT.L.%2BChia%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">R. Jakubovic </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>c</span>Medical Imaging (P.L.F., T.L.C., R.J., R.I.A.), Sunnybrook Health Sciences Centre</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=R.%2BJakubovic%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=Jakubovic%20R&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%3AR.%2BJakubovic%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">P. O'Connor </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>d</span>Department of Neurology (P.O.C.), St. Michael's Hospital</div><div class='author-affiliation'><span class='nlm-sup'>e</span>University of Toronto (P.O.C., L.L., A.F., R.I.A.), Toronto, Ontario, Canada.</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.%2BO%27Connor%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=O%27Connor%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 last"><a href="/search/author1%3AP.%2BO%2527Connor%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">L. Lee </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Neurology (L.L.)</div><div class='author-affiliation'><span class='nlm-sup'>e</span>University of Toronto (P.O.C., L.L., A.F., R.I.A.), Toronto, Ontario, Canada.</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=L.%2BLee%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=Lee%20L&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%3AL.%2BLee%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">A. Feinstein </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Psychiatry (A.F.)</div><div class='author-affiliation'><span class='nlm-sup'>e</span>University of Toronto (P.O.C., L.L., A.F., R.I.A.), Toronto, Ontario, Canada.</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=A.%2BFeinstein%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=Feinstein%20A&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%3AA.%2BFeinstein%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">R.I. 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<p id="p-1"><strong>BACKGROUND AND PURPOSE:</strong> Cognitive impairment is a common, disabling symptom of MS. We investigated the association between cognitive impairment and WM dysfunction in secondary-progressive multiple sclerosis using DTI.</p>
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<p id="p-2"><strong>MATERIALS AND METHODS:</strong> Cognitive performance was assessed with a standard neuropsychological battery, the Minimal Assessment of Cognitive Function in Multiple Sclerosis. Cognitive impairment was defined as scoring &gt;1.5 standard deviations below healthy controls on ≥2 subtests. Fractional anisotropy maps were compared against cognitive status using tract-based spatial statistics with threshold-free cluster enhancement.</p>
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<p id="p-3"><strong>RESULTS:</strong> Forty-five patients with secondary-progressive multiple sclerosis (median age: 55 years, female/male: 27/18, median Expanded Disability Status Scale Score: 6.5) were prospectively recruited. Cognitively impaired patients (25/45) displayed significantly less normalized global GM and WM volumes (<em>P</em> = .001, <em>P</em> = .024), more normalized T2-weighted and T1-weighted WM lesion volumes (<em>P</em> = .002, <em>P</em> = .006), and lower WM skeleton fractional anisotropy (<em>P</em> &lt; .001) than non-impaired patients. Impaired patients also had significantly lower fractional anisotropy (<em>p<sub>corr</sub></em> &lt; .05) in over 50% of voxels within every major WM tract. The most extensively impinged tracts were the left posterior thalamic radiation (100.0%), corpus callosum (97.8%), and right sagittal stratum (97.5%). No WM voxels had significantly higher fractional anisotropy in patients with cognitive impairment compared with their non-impaired counterparts (<em>p<sub>corr</sub></em> &gt; .05). After the inclusion of confounders in a multivariate logistic regression, only fractional anisotropy remained a significant predictor of cognitive status.</p>
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<p id="p-4"><strong>CONCLUSIONS:</strong> Cognitively impaired patients with secondary-progressive multiple sclerosis exhibited extensive WM dysfunction, though preferential involvement of WM tracts associated with cognition, such as the corpus callosum, was apparent. Multivariate analysis revealed that only WM skeleton fractional anisotropy was a significant predictor of cognitive status.</p>
</div></div><div class="section glossary" id="glossary-1">
<h2>ABBREVIATIONS:</h2>
<dl id="def-list-1"><dt id="def-item-1">CC<span class="def-item-dt-sep"></span></dt><dd>corpus callosum<span class="def-item-dd-sep"></span></dd><dt id="def-item-2">EDSS<span class="def-item-dt-sep"></span></dt><dd>Expanded Disability Status Scale<span class="def-item-dd-sep"></span></dd><dt id="def-item-3">FA<span class="def-item-dt-sep"></span></dt><dd>fractional anisotropy<span class="def-item-dd-sep"></span></dd><dt id="def-item-4">MNI<span class="def-item-dt-sep"></span></dt><dd>Montreal Neurological Institute<span class="def-item-dd-sep"></span></dd><dt id="def-item-5">RRMS<span class="def-item-dt-sep"></span></dt><dd>relapsing-remitting MS<span class="def-item-dd-sep"></span></dd><dt id="def-item-6">SPMS<span class="def-item-dt-sep"></span></dt><dd>secondary-progressive MS<span class="def-item-dd-sep"></span></dd><dt id="def-item-7">TBSS<span class="def-item-dt-sep"></span></dt><dd>tract-based spatial statistics<span class="def-item-dd-sep"></span></dd><dt id="def-item-8">WML<span class="def-item-dt-sep"></span></dt><dd>white matter lesion</dd></dl></div><ul class="copyright-statement"><li class="fn" id="copyright-statement-1">© 2014 by American Journal of Neuroradiology</li></ul><span class="highwire-journal-article-marker-end"></span></div><span class="related-urls"></span></div><a href="http://ajnr-stage2.stage.highwire.org/content/35/10/1910.full" class="hw-link hw-link-article-full-text" data-icon-position="" data-hide-link-title="0">View Full Text</a></div>  </div>

  
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        	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-volume highwire-cite-metadata">Vol. 35</span>, <span  class="highwire-cite-metadata-issue highwire-cite-metadata">Issue 10 </span><div  class="highwire-cite-metadata-pubdate highwire-cite-metadata">1 Oct 2014 </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 2014, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">35 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(10) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1910-1915; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A3974 </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">P.L.</span> <span class="nlm-surname">Francis</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">T.L.</span> <span class="nlm-surname">Chia</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">R.</span> <span class="nlm-surname">Jakubovic</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">P.</span> <span class="nlm-surname">O'Connor</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">L.</span> <span class="nlm-surname">Lee</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">A.</span> <span class="nlm-surname">Feinstein</span></span>, <span class="highwire-citation-author" data-delta="6"><span class="nlm-given-names">R.I.</span> <span class="nlm-surname">Aviv</span></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">Oct 2014, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">35 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(10) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1910-1915; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A3974 </span></div>
  
  
  
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