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<meta name="DC.Title" content="Differences in Cerebral Aneurysm Rupture Rate According to Arterial Anatomies Depend on the Hemodynamic Environment" />
<meta name="DC.Identifier" content="10.3174/ajnr.A6030" />
<meta name="DC.Date" content="2019-05-01" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Cerebral aneurysms have significantly different rupture rates depending on their size and location. The mechanisms underlying these differences are unclear. We examined whether anatomic rupture risks are dependent on the hemodynamic environment on the aneurysmal surface.

MATERIALS AND METHODS: Patient-specific geometries and flow rates of 84 cerebral aneurysms (42 anterior communicating artery and 42 MCA aneurysms) were acquired from our clinical study, the Computational Fluid Dynamics Analysis of Blood Flow in Cerebral Aneurysms: Prospective Observational Study. Pulsatile blood flow was simulated to calculate hemodynamic metrics with special attention to wall shear stress magnitude and temporal disturbance. Multivariate analyses were performed to identify associations between hemodynamic metrics and known rupture predictors (age, sex, hypertension, smoking history, location, and size).

RESULTS: All the wall shear stress magnitude–based metrics showed a significant negative association with size and location ( P &lt; .03), but not other risk factors. All the wall shear stress disturbance–based metrics were significantly related to size ( P &lt; .001). Only normalized transverse wall shear stress, a metric for multidirectional wall shear stress disturbance, was related to location ( P = .03). The normalized transverse wall shear stress had the highest odds ratio for location and size among hemodynamic metrics (odds ratios, 1.275 and 1.579; 95% confidence intervals, 1.020–1.693 and 1.238–2.219, respectively). Among the arterial geometric parameters, the aspect ratio had the second strongest association with all hemodynamic metrics, after our newly proposed aspect ratio–asphericity index.

CONCLUSIONS: The differences in aneurysm rupture rates according to size and location may reflect differences in hemodynamic environments in qualitatively different ways. An enhanced multidirectional wall shear stress disturbance may be especially associated with aneurysm rupture.

AAI
:   aspect ratio–asphericity index
AcomA
:   anterior communicating artery
β
:   regression coefficient
CFD
:   computational fluid dynamics
GON
:   gradient oscillatory number
NtransWSS
:   normalized transverse wall shear stress
NWSS
:   normalized wall shear stress
NWSSG
:   normalized wall shear stress gradient
OSI
:   oscillatory shear index
TAWSS
:   time-averaged wall shear stress
TAWSSG
:   time-averaged wall shear stress gradient
WSS
:   wall shear stress" />
<meta name="DC.Contributor" content="S. Fukuda" />
<meta name="DC.Contributor" content="Y. Shimogonya" />
<meta name="DC.Contributor" content="N. Yonemoto" />
<meta name="article:published_time" content="2019-05-01" />
<meta name="article:section" content="Interventional" />
<meta name="citation_title" content="Differences in Cerebral Aneurysm Rupture Rate According to Arterial Anatomies Depend on the Hemodynamic Environment" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;Cerebral aneurysms have significantly different rupture rates depending on their size and location. The mechanisms underlying these differences are unclear. We examined whether anatomic rupture risks are dependent on the hemodynamic environment on the aneurysmal surface.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;Patient-specific geometries and flow rates of 84 cerebral aneurysms (42 anterior communicating artery and 42 MCA aneurysms) were acquired from our clinical study, the Computational Fluid Dynamics Analysis of Blood Flow in Cerebral Aneurysms: Prospective Observational Study. Pulsatile blood flow was simulated to calculate hemodynamic metrics with special attention to wall shear stress magnitude and temporal disturbance. Multivariate analyses were performed to identify associations between hemodynamic metrics and known rupture predictors (age, sex, hypertension, smoking history, location, and size).&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;All the wall shear stress magnitude–based metrics showed a significant negative association with size and location (&lt;i&gt;P&lt;/i&gt; &amp;lt; .03), but not other risk factors. All the wall shear stress disturbance–based metrics were significantly related to size (&lt;i&gt;P&lt;/i&gt; &amp;lt; .001). Only normalized transverse wall shear stress, a metric for multidirectional wall shear stress disturbance, was related to location (&lt;i&gt;P&lt;/i&gt; = .03). The normalized transverse wall shear stress had the highest odds ratio for location and size among hemodynamic metrics (odds ratios, 1.275 and 1.579; 95% confidence intervals, 1.020–1.693 and 1.238–2.219, respectively). Among the arterial geometric parameters, the aspect ratio had the second strongest association with all hemodynamic metrics, after our newly proposed aspect ratio–asphericity index.&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;The differences in aneurysm rupture rates according to size and location may reflect differences in hemodynamic environments in qualitatively different ways. An enhanced multidirectional wall shear stress disturbance may be especially associated with aneurysm rupture.&lt;/p&gt;" />
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<meta name="twitter:title" content="Differences in Cerebral Aneurysm Rupture Rate According to Arterial Anatomies Depend on the Hemodynamic Environment" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:image" content="http://ajnr-stage2.stage.highwire.org/sites/default/files/highwire/ajnr/40/5.cover-source.jpg" />
<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Cerebral aneurysms have significantly different rupture rates depending on their size and location. The mechanisms underlying these differences are unclear. We examined whether anatomic rupture risks are dependent on the hemodynamic environment on the aneurysmal surface.

MATERIALS AND METHODS: Patient-specific geometries and flow rates of 84 cerebral aneurysms (42 anterior communicating artery and 42 MCA aneurysms) were acquired from our clinical study, the Computational Fluid Dynamics Analysis of Blood Flow in Cerebral Aneurysms: Prospective Observational Study. Pulsatile blood flow was simulated to calculate hemodynamic metrics with special attention to wall shear stress magnitude and temporal disturbance. Multivariate analyses were performed to identify associations between hemodynamic metrics and known rupture predictors (age, sex, hypertension, smoking history, location, and size).

RESULTS: All the wall shear stress magnitude–based metrics showed a significant negative association with size and location ( P &lt; .03), but not other risk factors. All the wall shear stress disturbance–based metrics were significantly related to size ( P &lt; .001). Only normalized transverse wall shear stress, a metric for multidirectional wall shear stress disturbance, was related to location ( P = .03). The normalized transverse wall shear stress had the highest odds ratio for location and size among hemodynamic metrics (odds ratios, 1.275 and 1.579; 95% confidence intervals, 1.020–1.693 and 1.238–2.219, respectively). Among the arterial geometric parameters, the aspect ratio had the second strongest association with all hemodynamic metrics, after our newly proposed aspect ratio–asphericity index.

CONCLUSIONS: The differences in aneurysm rupture rates according to size and location may reflect differences in hemodynamic environments in qualitatively different ways. An enhanced multidirectional wall shear stress disturbance may be especially associated with aneurysm rupture.

AAI
:   aspect ratio–asphericity index
AcomA
:   anterior communicating artery
β
:   regression coefficient
CFD
:   computational fluid dynamics
GON
:   gradient oscillatory number
NtransWSS
:   normalized transverse wall shear stress
NWSS
:   normalized wall shear stress
NWSSG
:   normalized wall shear stress gradient
OSI
:   oscillatory shear index
TAWSS
:   time-averaged wall shear stress
TAWSSG
:   time-averaged wall shear stress gradient
WSS
:   wall shear stress" />
<meta name="og-title" property="og:title" content="Differences in Cerebral Aneurysm Rupture Rate According to Arterial Anatomies Depend on the Hemodynamic Environment" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/40/5/834" />
<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: Cerebral aneurysms have significantly different rupture rates depending on their size and location. The mechanisms underlying these differences are unclear. We examined whether anatomic rupture risks are dependent on the hemodynamic environment on the aneurysmal surface.

MATERIALS AND METHODS: Patient-specific geometries and flow rates of 84 cerebral aneurysms (42 anterior communicating artery and 42 MCA aneurysms) were acquired from our clinical study, the Computational Fluid Dynamics Analysis of Blood Flow in Cerebral Aneurysms: Prospective Observational Study. Pulsatile blood flow was simulated to calculate hemodynamic metrics with special attention to wall shear stress magnitude and temporal disturbance. Multivariate analyses were performed to identify associations between hemodynamic metrics and known rupture predictors (age, sex, hypertension, smoking history, location, and size).

RESULTS: All the wall shear stress magnitude–based metrics showed a significant negative association with size and location ( P &lt; .03), but not other risk factors. All the wall shear stress disturbance–based metrics were significantly related to size ( P &lt; .001). Only normalized transverse wall shear stress, a metric for multidirectional wall shear stress disturbance, was related to location ( P = .03). The normalized transverse wall shear stress had the highest odds ratio for location and size among hemodynamic metrics (odds ratios, 1.275 and 1.579; 95% confidence intervals, 1.020–1.693 and 1.238–2.219, respectively). Among the arterial geometric parameters, the aspect ratio had the second strongest association with all hemodynamic metrics, after our newly proposed aspect ratio–asphericity index.

CONCLUSIONS: The differences in aneurysm rupture rates according to size and location may reflect differences in hemodynamic environments in qualitatively different ways. An enhanced multidirectional wall shear stress disturbance may be especially associated with aneurysm rupture.

AAI
:   aspect ratio–asphericity index
AcomA
:   anterior communicating artery
β
:   regression coefficient
CFD
:   computational fluid dynamics
GON
:   gradient oscillatory number
NtransWSS
:   normalized transverse wall shear stress
NWSS
:   normalized wall shear stress
NWSSG
:   normalized wall shear stress gradient
OSI
:   oscillatory shear index
TAWSS
:   time-averaged wall shear stress
TAWSSG
:   time-averaged wall shear stress gradient
WSS
:   wall shear stress" />
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    <div class="highwire-article-citation highwire-citation-type-highwire-article node67536--5" data-node-nid="67536" id="top-node-67536--6488923026" data-pisa="ajnr;40/5/834" data-pisa-master="ajnr;ajnr.A6030" data-apath="/ajnr/40/5/834.atom" data-hw-author-tooltip-instance="highwire_author_tooltip"><div class="highwire-cite highwire-cite-highwire-article highwire-citation-jcore-article-title-complete clearfix has-author-tooltip highwire-citation-highwire-article-top-a">
  
  
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      <h1 class="highwire-cite-title" id="page-title">Differences in Cerebral Aneurysm Rupture Rate According to Arterial Anatomies Depend on the Hemodynamic Environment</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">S. Fukuda</span>, <span class="highwire-citation-author" data-delta="1">Y. Shimogonya</span> and <span class="highwire-citation-author" data-delta="2">N. Yonemoto</span> <span  class="highwire-citation-author last"><span class="nlm-on-behalf-of"><span class="span" data-class="nlm-on-behalf-of">on behalf of the CFD ABO Study Group</span></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">May 2019,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">40 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(5) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">834-839; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A6030 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-67536--6488923026" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">S. Fukuda </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 Neurosurgery (S.F.), National Hospital Organization Kyoto Medical Center, Kyoto, Japan</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=S.%2BFukuda%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=Fukuda%20S&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%3AS.%2BFukuda%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/0000-0001-8876-4889" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for S. Fukuda</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">Y. Shimogonya </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>College of Engineering (Y.S.), Nihon University, Koriyama, Japan</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=Y.%2BShimogonya%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=Shimogonya%20Y&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%3AY.%2BShimogonya%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/0000-0002-9122-6253" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Y. Shimogonya</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">N. Yonemoto </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>c</span>Department of Biostatistics (N.Y.), Kyoto University, Kyoto, Japan</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.%2BYonemoto%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=Yonemoto%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"><a href="/search/author1%3AN.%2BYonemoto%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/0000-0003-3637-2095" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for N. Yonemoto</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><div class="cit ref-cit ref-journal" id="cit-40.5.834.1" data-doi="10.1038/nrneurol.2016.150"><div class="cit-metadata"><ol class="cit-auth-list"><li>
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</li><li><span class="cit-auth"><span class="cit-name-surname">Sugiyama</span>  <span class="cit-name-given-names">S</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Niizuma</span>  <span class="cit-name-given-names">K</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Sato</span>  <span class="cit-name-given-names">K</span></span>, <span class="cit-etal">et al</span></li></ol><cite>. <span class="cit-article-title">Blood flow into basilar tip aneurysms: a predictor for recanalization after coil embolization</span>. <abbr class="cit-jnl-abbrev">Stroke</abbr> <span class="cit-pub-date">2016</span>;<span class="cit-vol">47</span>:<span class="cit-fpage">2541</span>–<span class="cit-lpage">47</span><span class="cit-pub-id-sep cit-pub-id-doi-sep"> </span><span class="cit-pub-id cit-pub-id-doi"><span class="cit-pub-id-scheme-doi">doi:</span>10.1161/STROKEAHA.116.013555</span><span class="cit-pub-id-sep cit-pub-id-pmid-sep"> </span><span class="cit-pub-id cit-pub-id-pmid"><span class="cit-pub-id-scheme-pmid">pmid:</span>27625377</span></cite></div><div class="cit-extra"><a href="/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6OToic3Ryb2tlYWhhIjtzOjU6InJlc2lkIjtzOjEwOiI0Ny8xMC8yNTQxIjtzOjQ6ImF0b20iO3M6MTk6Ii9ham5yLzQwLzUvODM0LmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ==" class="cit-ref-sprinkles cit-ref-sprinkles-ijlink"><span><span class="cit-reflinks-abstract">Abstract</span><span class="cit-sep cit-reflinks-variant-name-sep">/</span><span class="cit-reflinks-full-text"><span class="free-full-text">FREE </span>Full Text</span></span></a></div></div></li></ol></div></div>  </div>

  
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        	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-volume highwire-cite-metadata">Vol. 40</span>, <span  class="highwire-cite-metadata-issue highwire-cite-metadata">Issue 5 </span><div  class="highwire-cite-metadata-pubdate highwire-cite-metadata">1 May 2019 </div></div>
      
      
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      <div class="highwire-cite-title">Differences in Cerebral Aneurysm Rupture Rate According to Arterial Anatomies Depend on the Hemodynamic Environment</div>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0"><span class="nlm-given-names">S.</span> <span class="nlm-surname">Fukuda</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">Y.</span> <span class="nlm-surname">Shimogonya</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">N.</span> <span class="nlm-surname">Yonemoto</span></span></span></div>
  
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      <div class="highwire-cite-title">Differences in Cerebral Aneurysm Rupture Rate According to Arterial Anatomies Depend on the Hemodynamic Environment</div>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0"><span class="nlm-given-names">S.</span> <span class="nlm-surname">Fukuda</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">Y.</span> <span class="nlm-surname">Shimogonya</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">N.</span> <span class="nlm-surname">Yonemoto</span></span></span></div>
  
    	<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">May 2019, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">40 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(5) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">834-839; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A6030 </span></div>
  
  
  
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