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<meta name="DC.Title" content="Pretreatment ADC Histogram Analysis as a Prognostic Imaging Biomarker for Patients with Recurrent Glioblastoma Treated with Bevacizumab: A Systematic Review and Meta-analysis" />
<meta name="DC.Identifier" content="10.3174/ajnr.A7406" />
<meta name="DC.Date" content="2022-02-01" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
<meta name="DC.Rights" content="© 2022 by American Journal of Neuroradiology" />
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<meta name="DC.Description" content="BACKGROUND: The mean ADC value of the lower Gaussian curve (ADCL) derived from the bi-Gaussian curve-fitting histogram analysis has been reported as a predictive/prognostic imaging biomarker in patients with recurrent glioblastoma treated with bevacizumab; however, its systematic summary has been lacking.

PURPOSE: We applied a systematic review and meta-analysis to investigate the predictive/prognostic performance of ADCL in patients with recurrent glioblastoma treated with bevacizumab.

DATA SOURCES: We performed a literature search using PubMed, Scopus, and EMBASE.

STUDY SELECTION: A total of 1344 abstracts were screened, of which 83 articles were considered potentially relevant. Data were finally extracted from 6 studies including 578 patients.

DATA ANALYSIS: Forest plots were generated to illustrate the hazard ratios of overall survival and progression-free survival. The heterogeneity across the studies was assessed using the Cochrane Q test and I2 values.

DATA SYNTHESIS: The pooled hazard ratios for overall survival and progression-free survival in patients with an ADCL lower than the cutoff values were 1.89 (95% CI, 1.53–2.31) and 1.98 (95% CI, 1.54–2.55) with low heterogeneity among the studies. Subgroup analysis of the bevacizumab-free cohort showed a pooled hazard ratio for overall survival of 1.20 (95% CI, 1.08–1.34) with low heterogeneity.

LIMITATIONS: The conclusions are limited by the difference in the definition of recurrence among the included studies.

CONCLUSIONS: This systematic review with meta-analysis supports the prognostic value of ADCL in patients with recurrent glioblastoma treated with bevacizumab, with a low ADCL demonstrating decreased overall survival and progression-free survival. On the other hand, the predictive role of ADCL for bevacizumab treatment was not confirmed.

ADCL
:   mean ADC value of the lower Gaussian curve
HR
:   hazard ratio
OS
:   overall survival
PFS
:   progression-free survival
QUADAS-2
:   Quality Assessment of Diagnostic Accuracy Studies 2
VEGF
:   vascular endothelial growth factor" />
<meta name="DC.Contributor" content="R. Kurokawa" />
<meta name="DC.Contributor" content="A. Baba" />
<meta name="DC.Contributor" content="M. Kurokawa" />
<meta name="DC.Contributor" content="A. Capizzano" />
<meta name="DC.Contributor" content="O. Hassan" />
<meta name="DC.Contributor" content="T. Johnson" />
<meta name="DC.Contributor" content="Y. Ota" />
<meta name="DC.Contributor" content="J. Kim" />
<meta name="DC.Contributor" content="A. Hagiwara" />
<meta name="DC.Contributor" content="T. Moritani" />
<meta name="DC.Contributor" content="A. Srinivasan" />
<meta name="article:published_time" content="2022-02-01" />
<meta name="article:section" content="Adult Brain" />
<meta name="citation_title" content="Pretreatment ADC Histogram Analysis as a Prognostic Imaging Biomarker for Patients with Recurrent Glioblastoma Treated with Bevacizumab: A Systematic Review and Meta-analysis" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND:&lt;/h3&gt;
&lt;p&gt;The mean ADC value of the lower Gaussian curve (ADC&lt;sub&gt;L&lt;/sub&gt;) derived from the bi-Gaussian curve-fitting histogram analysis has been reported as a predictive/prognostic imaging biomarker in patients with recurrent glioblastoma treated with bevacizumab; however, its systematic summary has been lacking.&lt;/p&gt;&lt;h3&gt;PURPOSE:&lt;/h3&gt;
&lt;p&gt;We applied a systematic review and meta-analysis to investigate the predictive/prognostic performance of ADC&lt;sub&gt;L&lt;/sub&gt; in patients with recurrent glioblastoma treated with bevacizumab.&lt;/p&gt;&lt;h3&gt;DATA SOURCES:&lt;/h3&gt;
&lt;p&gt;We performed a literature search using PubMed, Scopus, and EMBASE.&lt;/p&gt;&lt;h3&gt;STUDY SELECTION:&lt;/h3&gt;
&lt;p&gt;A total of 1344 abstracts were screened, of which 83 articles were considered potentially relevant. Data were finally extracted from 6 studies including 578 patients.&lt;/p&gt;&lt;h3&gt;DATA ANALYSIS:&lt;/h3&gt;
&lt;p&gt;Forest plots were generated to illustrate the hazard ratios of overall survival and progression-free survival. The heterogeneity across the studies was assessed using the Cochrane &lt;i&gt;Q&lt;/i&gt; test and I&lt;sup&gt;2&lt;/sup&gt; values.&lt;/p&gt;&lt;h3&gt;DATA SYNTHESIS:&lt;/h3&gt;
&lt;p&gt;The pooled hazard ratios for overall survival and progression-free survival in patients with an ADC&lt;sub&gt;L&lt;/sub&gt; lower than the cutoff values were 1.89 (95% CI, 1.53–2.31) and 1.98 (95% CI, 1.54–2.55) with low heterogeneity among the studies. Subgroup analysis of the bevacizumab-free cohort showed a pooled hazard ratio for overall survival of 1.20 (95% CI, 1.08–1.34) with low heterogeneity.&lt;/p&gt;&lt;h3&gt;LIMITATIONS:&lt;/h3&gt;
&lt;p&gt;The conclusions are limited by the difference in the definition of recurrence among the included studies.&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;This systematic review with meta-analysis supports the prognostic value of ADC&lt;sub&gt;L&lt;/sub&gt; in patients with recurrent glioblastoma treated with bevacizumab, with a low ADC&lt;sub&gt;L&lt;/sub&gt; demonstrating decreased overall survival and progression-free survival. On the other hand, the predictive role of ADC&lt;sub&gt;L&lt;/sub&gt; for bevacizumab treatment was not confirmed.&lt;/p&gt;" />
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<meta name="twitter:title" content="Pretreatment ADC Histogram Analysis as a Prognostic Imaging Biomarker for Patients with Recurrent Glioblastoma Treated with Bevacizumab: A Systematic Review and Meta-analysis" />
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<meta name="twitter:description" content="BACKGROUND: The mean ADC value of the lower Gaussian curve (ADCL) derived from the bi-Gaussian curve-fitting histogram analysis has been reported as a predictive/prognostic imaging biomarker in patients with recurrent glioblastoma treated with bevacizumab; however, its systematic summary has been lacking.

PURPOSE: We applied a systematic review and meta-analysis to investigate the predictive/prognostic performance of ADCL in patients with recurrent glioblastoma treated with bevacizumab.

DATA SOURCES: We performed a literature search using PubMed, Scopus, and EMBASE.

STUDY SELECTION: A total of 1344 abstracts were screened, of which 83 articles were considered potentially relevant. Data were finally extracted from 6 studies including 578 patients.

DATA ANALYSIS: Forest plots were generated to illustrate the hazard ratios of overall survival and progression-free survival. The heterogeneity across the studies was assessed using the Cochrane Q test and I2 values.

DATA SYNTHESIS: The pooled hazard ratios for overall survival and progression-free survival in patients with an ADCL lower than the cutoff values were 1.89 (95% CI, 1.53–2.31) and 1.98 (95% CI, 1.54–2.55) with low heterogeneity among the studies. Subgroup analysis of the bevacizumab-free cohort showed a pooled hazard ratio for overall survival of 1.20 (95% CI, 1.08–1.34) with low heterogeneity.

LIMITATIONS: The conclusions are limited by the difference in the definition of recurrence among the included studies.

CONCLUSIONS: This systematic review with meta-analysis supports the prognostic value of ADCL in patients with recurrent glioblastoma treated with bevacizumab, with a low ADCL demonstrating decreased overall survival and progression-free survival. On the other hand, the predictive role of ADCL for bevacizumab treatment was not confirmed.

ADCL
:   mean ADC value of the lower Gaussian curve
HR
:   hazard ratio
OS
:   overall survival
PFS
:   progression-free survival
QUADAS-2
:   Quality Assessment of Diagnostic Accuracy Studies 2
VEGF
:   vascular endothelial growth factor" />
<meta name="og-title" property="og:title" content="Pretreatment ADC Histogram Analysis as a Prognostic Imaging Biomarker for Patients with Recurrent Glioblastoma Treated with Bevacizumab: A Systematic Review and Meta-analysis" />
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<meta name="og-site-name" property="og:site_name" content="American Journal of Neuroradiology" />
<meta name="og-description" property="og:description" content="BACKGROUND: The mean ADC value of the lower Gaussian curve (ADCL) derived from the bi-Gaussian curve-fitting histogram analysis has been reported as a predictive/prognostic imaging biomarker in patients with recurrent glioblastoma treated with bevacizumab; however, its systematic summary has been lacking.

PURPOSE: We applied a systematic review and meta-analysis to investigate the predictive/prognostic performance of ADCL in patients with recurrent glioblastoma treated with bevacizumab.

DATA SOURCES: We performed a literature search using PubMed, Scopus, and EMBASE.

STUDY SELECTION: A total of 1344 abstracts were screened, of which 83 articles were considered potentially relevant. Data were finally extracted from 6 studies including 578 patients.

DATA ANALYSIS: Forest plots were generated to illustrate the hazard ratios of overall survival and progression-free survival. The heterogeneity across the studies was assessed using the Cochrane Q test and I2 values.

DATA SYNTHESIS: The pooled hazard ratios for overall survival and progression-free survival in patients with an ADCL lower than the cutoff values were 1.89 (95% CI, 1.53–2.31) and 1.98 (95% CI, 1.54–2.55) with low heterogeneity among the studies. Subgroup analysis of the bevacizumab-free cohort showed a pooled hazard ratio for overall survival of 1.20 (95% CI, 1.08–1.34) with low heterogeneity.

LIMITATIONS: The conclusions are limited by the difference in the definition of recurrence among the included studies.

CONCLUSIONS: This systematic review with meta-analysis supports the prognostic value of ADCL in patients with recurrent glioblastoma treated with bevacizumab, with a low ADCL demonstrating decreased overall survival and progression-free survival. On the other hand, the predictive role of ADCL for bevacizumab treatment was not confirmed.

ADCL
:   mean ADC value of the lower Gaussian curve
HR
:   hazard ratio
OS
:   overall survival
PFS
:   progression-free survival
QUADAS-2
:   Quality Assessment of Diagnostic Accuracy Studies 2
VEGF
:   vascular endothelial growth factor" />
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      <h1 class="highwire-cite-title" id="page-title">Pretreatment ADC Histogram Analysis as a Prognostic Imaging Biomarker for Patients with Recurrent Glioblastoma Treated with Bevacizumab: A Systematic Review and Meta-analysis</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">R. Kurokawa</span>, <span class="highwire-citation-author" data-delta="1">A. Baba</span>, <span class="highwire-citation-author" data-delta="2">M. Kurokawa</span>, <span class="highwire-citation-author" data-delta="3">A. Capizzano</span>, <span class="highwire-citation-author" data-delta="4">O. Hassan</span>, <span class="highwire-citation-author" data-delta="5">T. Johnson</span>, <span class="highwire-citation-author" data-delta="6">Y. Ota</span>, <span class="highwire-citation-author" data-delta="7">J. Kim</span>, <span class="highwire-citation-author" data-delta="8">A. Hagiwara</span>, <span class="highwire-citation-author" data-delta="9">T. Moritani</span> and <span class="highwire-citation-author" data-delta="10">A. Srinivasan</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">February 2022,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">43 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(2) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">202-206; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A7406 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-95495--61676300146" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">R. Kurokawa </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Division of Neuroradiology (R.K., A.B., M.K., A.C., O.H., Y.O., J.K., T.M., A.S.), Department of Radiology, University of Michigan, Ann Arbor, Michigan</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.%2BKurokawa%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=Kurokawa%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"><a href="/search/author1%3AR.%2BKurokawa%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/0000-0002-1186-8900" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for R. Kurokawa</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">A. Baba </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Division of Neuroradiology (R.K., A.B., M.K., A.C., O.H., Y.O., J.K., T.M., A.S.), Department of Radiology, University of Michigan, Ann Arbor, Michigan</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.%2BBaba%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=Baba%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"><a href="/search/author1%3AA.%2BBaba%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/0000-0001-6913-5307" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for A. 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Kurokawa </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Division of Neuroradiology (R.K., A.B., M.K., A.C., O.H., Y.O., J.K., T.M., A.S.), Department of Radiology, University of Michigan, Ann Arbor, Michigan</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.%2BKurokawa%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=Kurokawa%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"><a href="/search/author1%3AM.%2BKurokawa%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/0000-0002-3907-9188" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for M. Kurokawa</a></li></ul></div><div class="author-tooltip-3"><div class="author-tooltip-name">A. Capizzano </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Division of Neuroradiology (R.K., A.B., M.K., A.C., O.H., Y.O., J.K., T.M., A.S.), Department of Radiology, University of Michigan, Ann Arbor, Michigan</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.%2BCapizzano%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=Capizzano%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"><a href="/search/author1%3AA.%2BCapizzano%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/0000-0003-1950-8499" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for A. Capizzano</a></li></ul></div><div class="author-tooltip-4"><div class="author-tooltip-name">O. Hassan </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Division of Neuroradiology (R.K., A.B., M.K., A.C., O.H., Y.O., J.K., T.M., A.S.), Department of Radiology, University of Michigan, Ann Arbor, Michigan</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=O.%2BHassan%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=Hassan%20O&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%3AO.%2BHassan%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/0000-0002-7927-5378" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for O. 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Johnson </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Department of Biostatistics (T.J.), University of Michigan School of Public Health, Ann Arbor, Michigan</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.%2BJohnson%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=Johnson%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"><a href="/search/author1%3AT.%2BJohnson%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/0000-0002-7676-5347" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for T. 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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><div class="cit ref-cit ref-journal" id="cit-43.2.202.1" data-doi="10.1093/neuonc/noaa200"><div class="cit-metadata"><ol class="cit-auth-list"><li><span class="cit-auth"><span class="cit-name-surname">Ostrom</span>  <span class="cit-name-given-names">QT</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Patil</span>  <span class="cit-name-given-names">N</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Cioffi</span>  <span class="cit-name-given-names">G</span></span>, <span class="cit-etal">et al</span></li></ol><cite>. <span class="cit-article-title">CBTRUS Statistical Report: 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        	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-volume highwire-cite-metadata">Vol. 43</span>, <span  class="highwire-cite-metadata-issue highwire-cite-metadata">Issue 2 </span><div  class="highwire-cite-metadata-pubdate highwire-cite-metadata">1 Feb 2022 </div></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">R.</span> <span class="nlm-surname">Kurokawa</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">A.</span> <span class="nlm-surname">Baba</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">M.</span> <span class="nlm-surname">Kurokawa</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">A.</span> <span class="nlm-surname">Capizzano</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">O.</span> <span class="nlm-surname">Hassan</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">T.</span> <span class="nlm-surname">Johnson</span></span>, <span class="highwire-citation-author" data-delta="6"><span class="nlm-given-names">Y.</span> <span class="nlm-surname">Ota</span></span>, <span class="highwire-citation-author" data-delta="7"><span class="nlm-given-names">J.</span> <span class="nlm-surname">Kim</span></span>, <span class="highwire-citation-author" data-delta="8"><span class="nlm-given-names">A.</span> <span class="nlm-surname">Hagiwara</span></span>, <span class="highwire-citation-author" data-delta="9"><span class="nlm-given-names">T.</span> <span class="nlm-surname">Moritani</span></span>, <span class="highwire-citation-author" data-delta="10"><span class="nlm-given-names">A.</span> <span class="nlm-surname">Srinivasan</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">Feb 2022, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">43 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(2) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">202-206; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A7406 </span></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">Feb 2022, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">43 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(2) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">202-206; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A7406 </span></div>
  
  
  
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