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<meta name="DC.Language" content="en" />
<meta name="DC.Title" content="Transcranial Sonography of the Substantia Nigra: Digital Image Analysis" />
<meta name="DC.Identifier" content="10.3174/ajnr.A4049" />
<meta name="DC.Date" content="2014-12-01" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
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Indicates open access to non-subscribers at www.ajnr.org" />
<meta name="DC.AccessRights" content="open-access" />
<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Increased echogenicity of the substantia nigra is a typical transcranial sonography finding in Parkinson disease. Experimental software for digital analysis of the echogenic substantia nigra area has been developed. The aim of this study was to compare the evaluation of substantia nigra echogenicity by using digital analysis with a manual measurement in patients with Parkinson disease and healthy volunteers.

MATERIALS AND METHODS: One hundred thirteen healthy volunteers were enrolled in the derivation cohort, and 50 healthy volunteers and 30 patients with Parkinson disease, in the validation cohort. The substantia nigra was imaged from the right and left temporal bone window by using transcranial sonography. All subjects were examined twice by using different sonographic machines by an experienced sonographer. DICOM images of the substantia nigra were encoded; then, digital analysis and manual measurement of the substantia nigra were performed. The 90th percentile of the derivation cohort values was used as a cut-point for the evaluation of the hyperechogenic substantia nigra in the validation cohort. The Spearman coefficient was used for assessment of the correlation between both measurements. The Cohen κ coefficient was used for the assessment of the correlation between both measurements and Parkinson disease diagnosis.

RESULTS: The Spearman coefficient between measurements by using different machines was 0.686 for digital analysis and 0.721 for manual measurement ( P &lt; .0001). Hyperechogenic substantia nigra was detected in the same 26 (86.7%) patients with Parkinson disease by using both measurements. Cohen κ coefficients for digital analysis and manual measurement were 0.787 and 0.762, respectively ( P &lt; .0001).

CONCLUSIONS: The present study showed comparable results when measuring the substantia nigra features conventionally and by using the developed software.

AC1
:   first-order agreement coefficient
I 
:   intensity
PD
:   Parkinson disease
SN
:   substantia nigra
TI
:   tissue index
TCS
:   transcranial sonography" />
<meta name="DC.Contributor" content="D. Školoudík" />
<meta name="DC.Contributor" content="M. Jelínková" />
<meta name="DC.Contributor" content="J. Blahuta" />
<meta name="DC.Contributor" content="P. Čermák" />
<meta name="DC.Contributor" content="T. Soukup" />
<meta name="DC.Contributor" content="P. Bártová" />
<meta name="DC.Contributor" content="K. Langová" />
<meta name="DC.Contributor" content="R. Herzig" />
<meta name="article:published_time" content="2014-12-01" />
<meta name="article:section" content="Brain" />
<meta name="citation_title" content="Transcranial Sonography of the Substantia Nigra: Digital Image Analysis" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;Increased echogenicity of the substantia nigra is a typical transcranial sonography finding in Parkinson disease. Experimental software for digital analysis of the echogenic substantia nigra area has been developed. The aim of this study was to compare the evaluation of substantia nigra echogenicity by using digital analysis with a manual measurement in patients with Parkinson disease and healthy volunteers.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;One hundred thirteen healthy volunteers were enrolled in the derivation cohort, and 50 healthy volunteers and 30 patients with Parkinson disease, in the validation cohort. The substantia nigra was imaged from the right and left temporal bone window by using transcranial sonography. All subjects were examined twice by using different sonographic machines by an experienced sonographer. DICOM images of the substantia nigra were encoded; then, digital analysis and manual measurement of the substantia nigra were performed. The 90th percentile of the derivation cohort values was used as a cut-point for the evaluation of the hyperechogenic substantia nigra in the validation cohort. The Spearman coefficient was used for assessment of the correlation between both measurements. The Cohen κ coefficient was used for the assessment of the correlation between both measurements and Parkinson disease diagnosis.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;The Spearman coefficient between measurements by using different machines was 0.686 for digital analysis and 0.721 for manual measurement (&lt;i&gt;P&lt;/i&gt; &amp;lt; .0001). Hyperechogenic substantia nigra was detected in the same 26 (86.7%) patients with Parkinson disease by using both measurements. Cohen κ coefficients for digital analysis and manual measurement were 0.787 and 0.762, respectively (&lt;i&gt;P&lt;/i&gt; &amp;lt; .0001).&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;The present study showed comparable results when measuring the substantia nigra features conventionally and by using the developed software.&lt;/p&gt;" />
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<meta name="twitter:title" content="Transcranial Sonography of the Substantia Nigra: Digital Image Analysis" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Increased echogenicity of the substantia nigra is a typical transcranial sonography finding in Parkinson disease. Experimental software for digital analysis of the echogenic substantia nigra area has been developed. The aim of this study was to compare the evaluation of substantia nigra echogenicity by using digital analysis with a manual measurement in patients with Parkinson disease and healthy volunteers.

MATERIALS AND METHODS: One hundred thirteen healthy volunteers were enrolled in the derivation cohort, and 50 healthy volunteers and 30 patients with Parkinson disease, in the validation cohort. The substantia nigra was imaged from the right and left temporal bone window by using transcranial sonography. All subjects were examined twice by using different sonographic machines by an experienced sonographer. DICOM images of the substantia nigra were encoded; then, digital analysis and manual measurement of the substantia nigra were performed. The 90th percentile of the derivation cohort values was used as a cut-point for the evaluation of the hyperechogenic substantia nigra in the validation cohort. The Spearman coefficient was used for assessment of the correlation between both measurements. The Cohen κ coefficient was used for the assessment of the correlation between both measurements and Parkinson disease diagnosis.

RESULTS: The Spearman coefficient between measurements by using different machines was 0.686 for digital analysis and 0.721 for manual measurement ( P &lt; .0001). Hyperechogenic substantia nigra was detected in the same 26 (86.7%) patients with Parkinson disease by using both measurements. Cohen κ coefficients for digital analysis and manual measurement were 0.787 and 0.762, respectively ( P &lt; .0001).

CONCLUSIONS: The present study showed comparable results when measuring the substantia nigra features conventionally and by using the developed software.

AC1
:   first-order agreement coefficient
I 
:   intensity
PD
:   Parkinson disease
SN
:   substantia nigra
TI
:   tissue index
TCS
:   transcranial sonography" />
<meta name="og-title" property="og:title" content="Transcranial Sonography of the Substantia Nigra: Digital Image Analysis" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/35/12/2273" />
<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: Increased echogenicity of the substantia nigra is a typical transcranial sonography finding in Parkinson disease. Experimental software for digital analysis of the echogenic substantia nigra area has been developed. The aim of this study was to compare the evaluation of substantia nigra echogenicity by using digital analysis with a manual measurement in patients with Parkinson disease and healthy volunteers.

MATERIALS AND METHODS: One hundred thirteen healthy volunteers were enrolled in the derivation cohort, and 50 healthy volunteers and 30 patients with Parkinson disease, in the validation cohort. The substantia nigra was imaged from the right and left temporal bone window by using transcranial sonography. All subjects were examined twice by using different sonographic machines by an experienced sonographer. DICOM images of the substantia nigra were encoded; then, digital analysis and manual measurement of the substantia nigra were performed. The 90th percentile of the derivation cohort values was used as a cut-point for the evaluation of the hyperechogenic substantia nigra in the validation cohort. The Spearman coefficient was used for assessment of the correlation between both measurements. The Cohen κ coefficient was used for the assessment of the correlation between both measurements and Parkinson disease diagnosis.

RESULTS: The Spearman coefficient between measurements by using different machines was 0.686 for digital analysis and 0.721 for manual measurement ( P &lt; .0001). Hyperechogenic substantia nigra was detected in the same 26 (86.7%) patients with Parkinson disease by using both measurements. Cohen κ coefficients for digital analysis and manual measurement were 0.787 and 0.762, respectively ( P &lt; .0001).

CONCLUSIONS: The present study showed comparable results when measuring the substantia nigra features conventionally and by using the developed software.

AC1
:   first-order agreement coefficient
I 
:   intensity
PD
:   Parkinson disease
SN
:   substantia nigra
TI
:   tissue index
TCS
:   transcranial sonography" />
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    <div class="highwire-article-citation highwire-citation-type-highwire-article node13810--5" data-node-nid="13810" id="top-node-13810--61164827732" data-pisa="ajnr;35/12/2273" data-pisa-master="ajnr;ajnr.A4049" data-apath="/ajnr/35/12/2273.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">
  
  
      <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">Brain</span></span></div>
  
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      <h1 class="highwire-cite-title" id="page-title">Transcranial Sonography of the Substantia Nigra: Digital Image Analysis</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">D. Školoudík</span>, <span class="highwire-citation-author" data-delta="1">M. Jelínková</span>, <span class="highwire-citation-author" data-delta="2">J. Blahuta</span>, <span class="highwire-citation-author" data-delta="3">P. Čermák</span>, <span class="highwire-citation-author" data-delta="4">T. Soukup</span>, <span class="highwire-citation-author" data-delta="5">P. Bártová</span>, <span class="highwire-citation-author" data-delta="6">K. Langová</span> and <span class="highwire-citation-author" data-delta="7">R. Herzig</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">December 2014,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">35 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(12) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">2273-2278; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A4049 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-13810--61164827732" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">D. Školoudík </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Faculty of Health Science (D.Š.), Palacký University Olomouc, Olomouc, Czech Republic</div><div class='author-affiliation'><span class='nlm-sup'>b</span>Department of Neurology (D.Š., M.J., P.B.), University Hospital Ostrava, Ostrava, Czech Republic</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=D.%2B%C5%A0koloud%C3%ADk%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=%C5%A0koloud%C3%ADk%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.%2B%25C5%25A0koloud%25C3%25ADk%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">M. Jelínková </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Department of Neurology (D.Š., M.J., P.B.), University Hospital Ostrava, Ostrava, Czech Republic</div><div class='author-affiliation'><span class='nlm-sup'>c</span>Department of Neurology (M.J.), Hospital, Karviná-Ráj, Karviná, Czech Republic</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.%2BJel%C3%ADnkov%C3%A1%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=Jel%C3%ADnkov%C3%A1%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.%2BJel%25C3%25ADnkov%25C3%25A1%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. Blahuta </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>d</span>Institute of Computer Science (J.B., P.Č., T.S.), Faculty of Philosophy and Science, Silesian University in Opava, Opava, Czech Republic</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.%2BBlahuta%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=Blahuta%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.%2BBlahuta%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. Čermák </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>d</span>Institute of Computer Science (J.B., P.Č., T.S.), Faculty of Philosophy and Science, Silesian University in Opava, Opava, Czech Republic</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.%2B%C4%8Cerm%C3%A1k%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=%C4%8Cerm%C3%A1k%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.%2B%25C4%258Cerm%25C3%25A1k%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">T. Soukup </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>d</span>Institute of Computer Science (J.B., P.Č., T.S.), Faculty of Philosophy and Science, Silesian University in Opava, Opava, Czech Republic</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.%2BSoukup%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=Soukup%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.%2BSoukup%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">P. Bártová </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Department of Neurology (D.Š., M.J., P.B.), University Hospital Ostrava, Ostrava, Czech Republic</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.%2BB%C3%A1rtov%C3%A1%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=B%C3%A1rtov%C3%A1%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.%2BB%25C3%25A1rtov%25C3%25A1%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. Langová </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>e</span>Department of Biophysics (K.L.), Faculty of Medicine and Dentistry, Institute of Molecular and Translational Medicine, Palacký University, Olomouc, Czech Republic</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.%2BLangov%C3%A1%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=Langov%C3%A1%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.%2BLangov%25C3%25A1%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">R. Herzig </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>f</span>Department of Neurology (R.H.), Charles University Faculty of Medicine and University Hospital Hradec Králové, Hradec Králové, Czech Republic.</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.%2BHerzig%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=Herzig%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.%2BHerzig%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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<p id="p-2"><strong>BACKGROUND AND PURPOSE:</strong> Increased echogenicity of the substantia nigra is a typical transcranial sonography finding in Parkinson disease. Experimental software for digital analysis of the echogenic substantia nigra area has been developed. The aim of this study was to compare the evaluation of substantia nigra echogenicity by using digital analysis with a manual measurement in patients with Parkinson disease and healthy volunteers.</p>
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<p id="p-3"><strong>MATERIALS AND METHODS:</strong> One hundred thirteen healthy volunteers were enrolled in the derivation cohort, and 50 healthy volunteers and 30 patients with Parkinson disease, in the validation cohort. The substantia nigra was imaged from the right and left temporal bone window by using transcranial sonography. All subjects were examined twice by using different sonographic machines by an experienced sonographer. DICOM images of the substantia nigra were encoded; then, digital analysis and manual measurement of the substantia nigra were performed. The 90th percentile of the derivation cohort values was used as a cut-point for the evaluation of the hyperechogenic substantia nigra in the validation cohort. The Spearman coefficient was used for assessment of the correlation between both measurements. The Cohen κ coefficient was used for the assessment of the correlation between both measurements and Parkinson disease diagnosis.</p>
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<p id="p-4"><strong>RESULTS:</strong> The Spearman coefficient between measurements by using different machines was 0.686 for digital analysis and 0.721 for manual measurement (<em>P</em> &lt; .0001). Hyperechogenic substantia nigra was detected in the same 26 (86.7%) patients with Parkinson disease by using both measurements. Cohen κ coefficients for digital analysis and manual measurement were 0.787 and 0.762, respectively (<em>P</em> &lt; .0001).</p>
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<p id="p-5"><strong>CONCLUSIONS:</strong> The present study showed comparable results when measuring the substantia nigra features conventionally and by using the developed software.</p>
</div></div><div class="section glossary" id="glossary-1">
<h2 class="">ABBREVIATIONS:</h2>
<dl id="def-list-1"><dt id="def-item-1">AC1<span class="def-item-dt-sep"></span></dt><dd>first-order agreement coefficient<span class="def-item-dd-sep"></span></dd><dt id="def-item-2"><em>I</em><span class="def-item-dt-sep"></span></dt><dd>intensity<span class="def-item-dd-sep"></span></dd><dt id="def-item-3">PD<span class="def-item-dt-sep"></span></dt><dd>Parkinson disease<span class="def-item-dd-sep"></span></dd><dt id="def-item-4">SN<span class="def-item-dt-sep"></span></dt><dd>substantia nigra<span class="def-item-dd-sep"></span></dd><dt id="def-item-5">TI<span class="def-item-dt-sep"></span></dt><dd>tissue index<span class="def-item-dd-sep"></span></dd><dt id="def-item-6">TCS<span class="def-item-dt-sep"></span></dt><dd>transcranial sonography</dd></dl></div><ul class="copyright-statement"><li class="fn" id="copyright-statement-1">© 2014 by American Journal of Neuroradiology</li></ul><div class="license" id="license-1"><p id="p-1">Indicates open access to non-subscribers at <a href="http://www.ajnr.org">www.ajnr.org</a></p></div><span class="highwire-journal-article-marker-end"></span></div><span class="related-urls"></span></div><a href="http://ajnr-stage2.stage.highwire.org/content/35/12/2273.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 12 </span><div  class="highwire-cite-metadata-pubdate highwire-cite-metadata">1 Dec 2014 </div></div>
      
      
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    	<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">Dec 2014, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">35 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(12) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">2273-2278; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A4049 </span></div>
  
  
  
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