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<meta name="DC.Title" content="Comparison of Hippocampal Subfield Segmentation Agreement between 2 Automated Protocols across the Adult Life Span" />
<meta name="DC.Identifier" content="10.3174/ajnr.A7244" />
<meta name="DC.Date" content="2021-10-01" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: The hippocampus is a frequent focus of quantitative neuroimaging research, and structural hippocampal alterations are related to multiple neurocognitive disorders. An increasing number of neuroimaging studies are focusing on hippocampal subfield regional involvement in these disorders using various automated segmentation approaches. Direct comparisons among these approaches are limited. The purpose of this study was to compare the agreement between two automated hippocampal segmentation algorithms in an adult population.

MATERIALS AND METHODS: We compared the results of 2 automated segmentation algorithms for hippocampal subfields (FreeSurfer v6.0 and volBrain) within a single imaging data set from adults ( n = 176, 89 women) across a wide age range (20–79 years). Brain MR imaging was acquired on a single 3T scanner as part of the IXI Brain Development Dataset and included T1- and T2-weighted MR images. We also examined subfield volumetric differences related to age and sex and the impact of different intracranial volume and total hippocampal volume normalization methods.

RESULTS: Estimated intracranial volume and total hippocampal volume of both protocols were strongly correlated ( r = 0.93 and 0.9, respectively; both P &lt; .001). Hippocampal subfield volumes were correlated (ranging from r = 0.42 for the subiculum to r = 0.78 for the cornu ammonis [CA]1, all P &lt; .001). However, absolute volumes were significantly different between protocols. volBrain produced larger CA1 and CA4-dentate gyrus and smaller CA2-CA3 and subiculum volumes compared with FreeSurfer v6.0. Regional age- and sex-related differences in subfield volumes were qualitatively and quantitatively different depending on segmentation protocol and intracranial volume/total hippocampal volume normalization method.

CONCLUSIONS: The hippocampal subfield volume relationship to demographic factors and disease states should undergo nuanced interpretation, especially when considering different segmentation protocols.

CA
:   cornu ammonis
DG
:   dentate gyrus
HPSF
:   hippocampal subfield
ICV
:   intracranial volume
SR-SL-SM
:   strata radiatum-lacunosum-moleculare
THV
:   total hippocampal volume" />
<meta name="DC.Contributor" content="A. Samara" />
<meta name="DC.Contributor" content="C.A. Raji" />
<meta name="DC.Contributor" content="Z. Li" />
<meta name="DC.Contributor" content="T. Hershey" />
<meta name="article:published_time" content="2021-10-01" />
<meta name="article:section" content="Adult Brain" />
<meta name="citation_title" content="Comparison of Hippocampal Subfield Segmentation Agreement between 2 Automated Protocols across the Adult Life Span" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;The hippocampus is a frequent focus of quantitative neuroimaging research, and structural hippocampal alterations are related to multiple neurocognitive disorders. An increasing number of neuroimaging studies are focusing on hippocampal subfield regional involvement in these disorders using various automated segmentation approaches. Direct comparisons among these approaches are limited. The purpose of this study was to compare the agreement between two automated hippocampal segmentation algorithms in an adult population.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;We compared the results of 2 automated segmentation algorithms for hippocampal subfields (FreeSurfer v6.0 and volBrain) within a single imaging data set from adults (&lt;i&gt;n&lt;/i&gt; = 176, 89 women) across a wide age range (20–79 years). Brain MR imaging was acquired on a single 3T scanner as part of the IXI Brain Development Dataset and included T1- and T2-weighted MR images. We also examined subfield volumetric differences related to age and sex and the impact of different intracranial volume and total hippocampal volume normalization methods.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;Estimated intracranial volume and total hippocampal volume of both protocols were strongly correlated (&lt;i&gt;r&lt;/i&gt; = 0.93 and 0.9, respectively; both &lt;i&gt;P&lt;/i&gt; &amp;lt; .001). Hippocampal subfield volumes were correlated (ranging from &lt;i&gt;r&lt;/i&gt; = 0.42 for the subiculum to &lt;i&gt;r&lt;/i&gt; = 0.78 for the cornu ammonis [CA]1, all &lt;i&gt;P&lt;/i&gt; &amp;lt; .001). However, absolute volumes were significantly different between protocols. volBrain produced larger CA1 and CA4-dentate gyrus and smaller CA2-CA3 and subiculum volumes compared with FreeSurfer v6.0. Regional age- and sex-related differences in subfield volumes were qualitatively and quantitatively different depending on segmentation protocol and intracranial volume/total hippocampal volume normalization method.&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;The hippocampal subfield volume relationship to demographic factors and disease states should undergo nuanced interpretation, especially when considering different segmentation protocols.&lt;/p&gt;" />
<meta name="citation_journal_title" content="American Journal of Neuroradiology" />
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<meta name="citation_author" content="A. Samara" />
<meta name="citation_author_institution" content="aFrom the Department of Psychiatry (A.S., Z.L., T.H.), Washington University School of Medicine, St. Louis, Missouri" />
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<meta name="citation_author" content="C.A. Raji" />
<meta name="citation_author_institution" content="aFrom the Department of Psychiatry (A.S., Z.L., T.H.), Washington University School of Medicine, St. Louis, Missouri" />
<meta name="citation_author_institution" content="bMallinckrodt Institute of Radiology (C.A.R., T.H.), Washington University School of Medicine, St. Louis, Missouri" />
<meta name="citation_author_institution" content="cDepartment of Neurology (C.A.R., T.H.), Washington University School of Medicine, St. Louis, Missouri" />
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<meta name="citation_author" content="Z. Li" />
<meta name="citation_author_institution" content="aFrom the Department of Psychiatry (A.S., Z.L., T.H.), Washington University School of Medicine, St. Louis, Missouri" />
<meta name="citation_author_institution" content="dDepartment of Psychological and Brain Sciences (Z.L.), Washington University School of Medicine, St. Louis, Missouri" />
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<meta name="twitter:title" content="Comparison of Hippocampal Subfield Segmentation Agreement between 2 Automated Protocols across the Adult Life Span" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: The hippocampus is a frequent focus of quantitative neuroimaging research, and structural hippocampal alterations are related to multiple neurocognitive disorders. An increasing number of neuroimaging studies are focusing on hippocampal subfield regional involvement in these disorders using various automated segmentation approaches. Direct comparisons among these approaches are limited. The purpose of this study was to compare the agreement between two automated hippocampal segmentation algorithms in an adult population.

MATERIALS AND METHODS: We compared the results of 2 automated segmentation algorithms for hippocampal subfields (FreeSurfer v6.0 and volBrain) within a single imaging data set from adults ( n = 176, 89 women) across a wide age range (20–79 years). Brain MR imaging was acquired on a single 3T scanner as part of the IXI Brain Development Dataset and included T1- and T2-weighted MR images. We also examined subfield volumetric differences related to age and sex and the impact of different intracranial volume and total hippocampal volume normalization methods.

RESULTS: Estimated intracranial volume and total hippocampal volume of both protocols were strongly correlated ( r = 0.93 and 0.9, respectively; both P &lt; .001). Hippocampal subfield volumes were correlated (ranging from r = 0.42 for the subiculum to r = 0.78 for the cornu ammonis [CA]1, all P &lt; .001). However, absolute volumes were significantly different between protocols. volBrain produced larger CA1 and CA4-dentate gyrus and smaller CA2-CA3 and subiculum volumes compared with FreeSurfer v6.0. Regional age- and sex-related differences in subfield volumes were qualitatively and quantitatively different depending on segmentation protocol and intracranial volume/total hippocampal volume normalization method.

CONCLUSIONS: The hippocampal subfield volume relationship to demographic factors and disease states should undergo nuanced interpretation, especially when considering different segmentation protocols.

CA
:   cornu ammonis
DG
:   dentate gyrus
HPSF
:   hippocampal subfield
ICV
:   intracranial volume
SR-SL-SM
:   strata radiatum-lacunosum-moleculare
THV
:   total hippocampal volume" />
<meta name="og-title" property="og:title" content="Comparison of Hippocampal Subfield Segmentation Agreement between 2 Automated Protocols across the Adult Life Span" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/42/10/1783" />
<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: The hippocampus is a frequent focus of quantitative neuroimaging research, and structural hippocampal alterations are related to multiple neurocognitive disorders. An increasing number of neuroimaging studies are focusing on hippocampal subfield regional involvement in these disorders using various automated segmentation approaches. Direct comparisons among these approaches are limited. The purpose of this study was to compare the agreement between two automated hippocampal segmentation algorithms in an adult population.

MATERIALS AND METHODS: We compared the results of 2 automated segmentation algorithms for hippocampal subfields (FreeSurfer v6.0 and volBrain) within a single imaging data set from adults ( n = 176, 89 women) across a wide age range (20–79 years). Brain MR imaging was acquired on a single 3T scanner as part of the IXI Brain Development Dataset and included T1- and T2-weighted MR images. We also examined subfield volumetric differences related to age and sex and the impact of different intracranial volume and total hippocampal volume normalization methods.

RESULTS: Estimated intracranial volume and total hippocampal volume of both protocols were strongly correlated ( r = 0.93 and 0.9, respectively; both P &lt; .001). Hippocampal subfield volumes were correlated (ranging from r = 0.42 for the subiculum to r = 0.78 for the cornu ammonis [CA]1, all P &lt; .001). However, absolute volumes were significantly different between protocols. volBrain produced larger CA1 and CA4-dentate gyrus and smaller CA2-CA3 and subiculum volumes compared with FreeSurfer v6.0. Regional age- and sex-related differences in subfield volumes were qualitatively and quantitatively different depending on segmentation protocol and intracranial volume/total hippocampal volume normalization method.

CONCLUSIONS: The hippocampal subfield volume relationship to demographic factors and disease states should undergo nuanced interpretation, especially when considering different segmentation protocols.

CA
:   cornu ammonis
DG
:   dentate gyrus
HPSF
:   hippocampal subfield
ICV
:   intracranial volume
SR-SL-SM
:   strata radiatum-lacunosum-moleculare
THV
:   total hippocampal volume" />
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      <h1 class="highwire-cite-title" id="page-title">Comparison of Hippocampal Subfield Segmentation Agreement between 2 Automated Protocols across the Adult Life Span</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">A. Samara</span>, <span class="highwire-citation-author" data-delta="1">C.A. Raji</span>, <span class="highwire-citation-author" data-delta="2">Z. Li</span> and <span class="highwire-citation-author" data-delta="3">T. Hershey</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 2021,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">42 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(10) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1783-1789; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A7244 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-93301--6233672790" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">A. Samara </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Department of Psychiatry (A.S., Z.L., T.H.), Washington University School of Medicine, St. Louis, Missouri</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.%2BSamara%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=Samara%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.%2BSamara%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/0000-0002-6001-7395" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for A. Samara</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">C.A. Raji </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Department of Psychiatry (A.S., Z.L., T.H.), Washington University School of Medicine, St. Louis, Missouri</div><div class='author-affiliation'><span class='nlm-sup'>b</span>Mallinckrodt Institute of Radiology (C.A.R., T.H.), Washington University School of Medicine, St. Louis, Missouri</div><div class='author-affiliation'><span class='nlm-sup'>c</span>Department of Neurology (C.A.R., T.H.), Washington University School of Medicine, St. Louis, Missouri</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.A.%2BRaji%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=Raji%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"><a href="/search/author1%3AC.A.%2BRaji%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/0000-0002-9086-0105" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for C.A. Raji</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">Z. Li </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Department of Psychiatry (A.S., Z.L., T.H.), Washington University School of Medicine, St. Louis, Missouri</div><div class='author-affiliation'><span class='nlm-sup'>d</span>Department of Psychological and Brain Sciences (Z.L.), Washington University School of Medicine, St. Louis, Missouri</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=Z.%2BLi%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Li%20Z&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%3AZ.%2BLi%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0000-0003-2246-4116" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Z. 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Hershey </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Department of Psychiatry (A.S., Z.L., T.H.), Washington University School of Medicine, St. Louis, Missouri</div><div class='author-affiliation'><span class='nlm-sup'>b</span>Mallinckrodt Institute of Radiology (C.A.R., T.H.), Washington University School of Medicine, St. Louis, Missouri</div><div class='author-affiliation'><span class='nlm-sup'>c</span>Department of Neurology (C.A.R., T.H.), Washington University School of Medicine, St. Louis, Missouri</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.%2BHershey%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=Hershey%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.%2BHershey%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/0000-0001-7549-0698" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for T. 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      <div class="highwire-cite-title">Comparison of Hippocampal Subfield Segmentation Agreement between 2 Automated Protocols across the Adult Life Span</div>  
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