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<meta name="DC.Title" content="Iron and Volume in the Deep Gray Matter: Association with Cognitive Impairment in Multiple Sclerosis" />
<meta name="DC.Identifier" content="10.3174/ajnr.A3998" />
<meta name="DC.Date" content="2015-01-01" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
<meta name="DC.Rights" content="© 2015 by American Journal of Neuroradiology" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: There is a well-established correlation between deep gray matter atrophy and cognitive dysfunction in MS. However, the cause of these signs of neurodegeneration is poorly understood. Iron accumulation in the deep gray matter is higher in patients with MS compared with age- and sex-matched healthy controls, and could contribute to disease progression. Our objective was to evaluate the relationship between iron and cognition in several deep gray matter structures while accounting for the influence of volume loss.

MATERIALS AND METHODS: Eighty-five patients with MS and 27 healthy volunteers underwent 3T MR imaging and neuropsychological examination. We used SWI filtered phase to analyze the mean phase of low-phase voxels, indicative of abnormal iron accumulation.

RESULTS: Correlations between mean phase of low-phase voxels and cognitive tests were found in the caudate nucleus ( r = 0.240 and 0.232), putamen ( r = 0.368, 0.252, and 0.238), globus pallidus ( r = 0.235), and pulvinar nucleus of thalamus ( r = 0.244, 0.255, and 0.251) ( P &lt; .05). However, correlations between structure volume and cognition were more robust. Furthermore, the introduction of structure volume into hierarchical regression analyses after iron metrics significantly improved most models, and mean phase of low-phase voxels did not account for significant variance after volume.

CONCLUSIONS: These findings suggest that iron accumulation plays a significant, if minor, role in MS cognitive decline.

BVMT-R
:   the total learning portion of the Brief Visuospatial Memory Test-Revised
CVLT2
:   total learning portion of the California Verbal Learning Test
DGM
:   deep gray matter
DKEFS-CS
:   Delis-Kaplan Executive Function System Sorting Test
LPV
:   low-phase voxel
MP-LPV
:   mean phase of the low-phase voxels
NP
:   neuropsychological
PASAT
:   3-second Paced Auditory Serial Addition Test
SDMT
:   Symbol Digit Modalities Test" />
<meta name="DC.Contributor" content="C.M. Modica" />
<meta name="DC.Contributor" content="R. Zivadinov" />
<meta name="DC.Contributor" content="M.G. Dwyer" />
<meta name="DC.Contributor" content="N. Bergsland" />
<meta name="DC.Contributor" content="A.R. Weeks" />
<meta name="DC.Contributor" content="R.H.B. Benedict" />
<meta name="article:published_time" content="2015-01-01" />
<meta name="article:section" content="Brain" />
<meta name="citation_title" content="Iron and Volume in the Deep Gray Matter: Association with Cognitive Impairment in Multiple Sclerosis" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;There is a well-established correlation between deep gray matter atrophy and cognitive dysfunction in MS. However, the cause of these signs of neurodegeneration is poorly understood. Iron accumulation in the deep gray matter is higher in patients with MS compared with age- and sex-matched healthy controls, and could contribute to disease progression. Our objective was to evaluate the relationship between iron and cognition in several deep gray matter structures while accounting for the influence of volume loss.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;Eighty-five patients with MS and 27 healthy volunteers underwent 3T MR imaging and neuropsychological examination. We used SWI filtered phase to analyze the mean phase of low-phase voxels, indicative of abnormal iron accumulation.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;Correlations between mean phase of low-phase voxels and cognitive tests were found in the caudate nucleus (&lt;i&gt;r&lt;/i&gt; = 0.240 and 0.232), putamen (&lt;i&gt;r&lt;/i&gt; = 0.368, 0.252, and 0.238), globus pallidus (&lt;i&gt;r&lt;/i&gt; = 0.235), and pulvinar nucleus of thalamus (&lt;i&gt;r&lt;/i&gt; = 0.244, 0.255, and 0.251) (&lt;i&gt;P&lt;/i&gt; &amp;lt; .05). However, correlations between structure volume and cognition were more robust. Furthermore, the introduction of structure volume into hierarchical regression analyses after iron metrics significantly improved most models, and mean phase of low-phase voxels did not account for significant variance after volume.&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;These findings suggest that iron accumulation plays a significant, if minor, role in MS cognitive decline.&lt;/p&gt;" />
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<meta name="twitter:title" content="Iron and Volume in the Deep Gray Matter: Association with Cognitive Impairment in Multiple Sclerosis" />
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<meta name="twitter:image" content="http://ajnr-stage2.stage.highwire.org/sites/default/files/highwire/ajnr/36/1.cover-source.jpg" />
<meta name="twitter:description" content="BACKGROUND AND PURPOSE: There is a well-established correlation between deep gray matter atrophy and cognitive dysfunction in MS. However, the cause of these signs of neurodegeneration is poorly understood. Iron accumulation in the deep gray matter is higher in patients with MS compared with age- and sex-matched healthy controls, and could contribute to disease progression. Our objective was to evaluate the relationship between iron and cognition in several deep gray matter structures while accounting for the influence of volume loss.

MATERIALS AND METHODS: Eighty-five patients with MS and 27 healthy volunteers underwent 3T MR imaging and neuropsychological examination. We used SWI filtered phase to analyze the mean phase of low-phase voxels, indicative of abnormal iron accumulation.

RESULTS: Correlations between mean phase of low-phase voxels and cognitive tests were found in the caudate nucleus ( r = 0.240 and 0.232), putamen ( r = 0.368, 0.252, and 0.238), globus pallidus ( r = 0.235), and pulvinar nucleus of thalamus ( r = 0.244, 0.255, and 0.251) ( P &lt; .05). However, correlations between structure volume and cognition were more robust. Furthermore, the introduction of structure volume into hierarchical regression analyses after iron metrics significantly improved most models, and mean phase of low-phase voxels did not account for significant variance after volume.

CONCLUSIONS: These findings suggest that iron accumulation plays a significant, if minor, role in MS cognitive decline.

BVMT-R
:   the total learning portion of the Brief Visuospatial Memory Test-Revised
CVLT2
:   total learning portion of the California Verbal Learning Test
DGM
:   deep gray matter
DKEFS-CS
:   Delis-Kaplan Executive Function System Sorting Test
LPV
:   low-phase voxel
MP-LPV
:   mean phase of the low-phase voxels
NP
:   neuropsychological
PASAT
:   3-second Paced Auditory Serial Addition Test
SDMT
:   Symbol Digit Modalities Test" />
<meta name="og-title" property="og:title" content="Iron and Volume in the Deep Gray Matter: Association with Cognitive Impairment in Multiple Sclerosis" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/36/1/57" />
<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: There is a well-established correlation between deep gray matter atrophy and cognitive dysfunction in MS. However, the cause of these signs of neurodegeneration is poorly understood. Iron accumulation in the deep gray matter is higher in patients with MS compared with age- and sex-matched healthy controls, and could contribute to disease progression. Our objective was to evaluate the relationship between iron and cognition in several deep gray matter structures while accounting for the influence of volume loss.

MATERIALS AND METHODS: Eighty-five patients with MS and 27 healthy volunteers underwent 3T MR imaging and neuropsychological examination. We used SWI filtered phase to analyze the mean phase of low-phase voxels, indicative of abnormal iron accumulation.

RESULTS: Correlations between mean phase of low-phase voxels and cognitive tests were found in the caudate nucleus ( r = 0.240 and 0.232), putamen ( r = 0.368, 0.252, and 0.238), globus pallidus ( r = 0.235), and pulvinar nucleus of thalamus ( r = 0.244, 0.255, and 0.251) ( P &lt; .05). However, correlations between structure volume and cognition were more robust. Furthermore, the introduction of structure volume into hierarchical regression analyses after iron metrics significantly improved most models, and mean phase of low-phase voxels did not account for significant variance after volume.

CONCLUSIONS: These findings suggest that iron accumulation plays a significant, if minor, role in MS cognitive decline.

BVMT-R
:   the total learning portion of the Brief Visuospatial Memory Test-Revised
CVLT2
:   total learning portion of the California Verbal Learning Test
DGM
:   deep gray matter
DKEFS-CS
:   Delis-Kaplan Executive Function System Sorting Test
LPV
:   low-phase voxel
MP-LPV
:   mean phase of the low-phase voxels
NP
:   neuropsychological
PASAT
:   3-second Paced Auditory Serial Addition Test
SDMT
:   Symbol Digit Modalities Test" />
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      <h1 class="highwire-cite-title" id="page-title">Iron and Volume in the Deep Gray Matter: Association with Cognitive Impairment in Multiple Sclerosis</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">C.M. Modica</span>, <span class="highwire-citation-author" data-delta="1">R. Zivadinov</span>, <span class="highwire-citation-author" data-delta="2">M.G. Dwyer</span>, <span class="highwire-citation-author" data-delta="3">N. Bergsland</span>, <span class="highwire-citation-author" data-delta="4">A.R. Weeks</span> and <span class="highwire-citation-author" data-delta="5">R.H.B. Benedict</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">January 2015,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">36 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(1) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">57-62; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A3998 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-13952--61002299655" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">C.M. Modica </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Neuroscience Program (C.M.M.)</div><div class='author-affiliation'><span class='nlm-sup'>b</span>Buffalo Neuroimaging Analysis Center (C.M.M., R.Z., M.G.D., N.B., R.H.B.B.)</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=C.M.%2BModica%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=Modica%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.M.%2BModica%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">R. Zivadinov </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Buffalo Neuroimaging Analysis Center (C.M.M., R.Z., M.G.D., N.B., R.H.B.B.)</div><div class='author-affiliation'><span class='nlm-sup'>c</span>MR Imaging Clinical Translational Research Center (R.Z.)</div><div class='author-affiliation'><span class='nlm-sup'>d</span>Department of Neurology (R.Z., R.H.B.B.), School of Medicine and Biomedical Sciences</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.%2BZivadinov%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=Zivadinov%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.%2BZivadinov%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">M.G. Dwyer </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Buffalo Neuroimaging Analysis Center (C.M.M., R.Z., M.G.D., N.B., R.H.B.B.)</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=M.G.%2BDwyer%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=Dwyer%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.G.%2BDwyer%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">N. Bergsland </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Buffalo Neuroimaging Analysis Center (C.M.M., R.Z., M.G.D., N.B., R.H.B.B.)</div><div class='author-affiliation'><span class='nlm-sup'>f</span>IRCCS (N.B.), “S. Maria Nascente,” Don Gnocchi Foundation, Milan, Italy.</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=N.%2BBergsland%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=Bergsland%20N&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%3AN.%2BBergsland%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">A.R. Weeks </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>e</span>School of Public Health and Health Professions (A.R.W.), University at Buffalo, State University of New York, Buffalo, New York</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.R.%2BWeeks%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=Weeks%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.R.%2BWeeks%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">R.H.B. Benedict </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Buffalo Neuroimaging Analysis Center (C.M.M., R.Z., M.G.D., N.B., R.H.B.B.)</div><div class='author-affiliation'><span class='nlm-sup'>d</span>Department of Neurology (R.Z., R.H.B.B.), School of Medicine and Biomedical Sciences</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.H.B.%2BBenedict%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=Benedict%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.H.B.%2BBenedict%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div></div></div>  </div>

  
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    <div class="highwire-markup"><div xmlns="http://www.w3.org/1999/xhtml" xmlns:xhtml="http://www.w3.org/1999/xhtml" class="section ref-list" id="ref-list-1"><h2 class="">References</h2><ol class="cit-list ref-use-labels"><li><span class="ref-label">1.</span><a class="rev-xref-ref" href="#xref-ref-1-1" title="View reference 1. in text" id="ref-1">↵</a>

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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">Jan 2015, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">36 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(1) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">57-62; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A3998 </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">C.M.</span> <span class="nlm-surname">Modica</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">R.</span> <span class="nlm-surname">Zivadinov</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">M.G.</span> <span class="nlm-surname">Dwyer</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">N.</span> <span class="nlm-surname">Bergsland</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">A.R.</span> <span class="nlm-surname">Weeks</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">R.H.B.</span> <span class="nlm-surname">Benedict</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">Jan 2015, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">36 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(1) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">57-62; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A3998 </span></div>
  
  
  
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