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<meta name="DC.Title" content="Understanding Angiography-Based Aneurysm Flow Fields through Comparison with Computational Fluid Dynamics" />
<meta name="DC.Identifier" content="10.3174/ajnr.A5158" />
<meta name="DC.Date" content="2017-04-06" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Hemodynamics is thought to be an important factor for aneurysm progression and rupture. Our aim was to evaluate whether flow fields reconstructed from dynamic angiography data can be used to realistically represent the main flow structures in intracranial aneurysms.

MATERIALS AND METHODS: DSA-based flow reconstructions, obtained during interventional treatment, were compared qualitatively with flow fields obtained from patient-specific computational fluid dynamics models and quantitatively with projections of the computational fluid dynamics fields (by computing a directional similarity of the vector fields) in 15 cerebral aneurysms.

RESULTS: The average similarity between the DSA and the projected computational fluid dynamics flow fields was 78% in the parent artery, while it was only 30% in the aneurysm region. Qualitatively, both the DSA and projected computational fluid dynamics flow fields captured the location of the inflow jet, the main vortex structure, the intrasaccular flow split, and the main rotation direction in approximately 60% of the cases.

CONCLUSIONS: Several factors affect the reconstruction of 2D flow fields from dynamic angiography sequences. The most important factors are the 3-dimensionality of the intrasaccular flow patterns and inflow jets, the alignment of the main vortex structure with the line of sight, the overlapping of surrounding vessels, and possibly frame rate undersampling. Flow visualization with DSA from &gt;1 projection is required for understanding of the 3D intrasaccular flow patterns. Although these DSA-based flow quantification techniques do not capture swirling or secondary flows in the parent artery, they still provide a good representation of the mean axial flow and the corresponding flow rate.

### Abbreviations

CFD
:   computational fluid dynamics
MAFA
:   mean aneurysm flow amplitude (determined from DSA)
MEAN
:   projection average
VEL
:   mean aneurysm velocity (determined from CFD)" />
<meta name="DC.Contributor" content="J.R. Cebral" />
<meta name="DC.Contributor" content="F. Mut" />
<meta name="DC.Contributor" content="B.J. Chung" />
<meta name="DC.Contributor" content="L. Spelle" />
<meta name="DC.Contributor" content="J. Moret" />
<meta name="DC.Contributor" content="F. van Nijnatten" />
<meta name="DC.Contributor" content="D. Ruijters" />
<meta name="article:published_time" content="2017-04-06" />
<meta name="article:section" content="INTERVENTIONAL" />
<meta name="citation_title" content="Understanding Angiography-Based Aneurysm Flow Fields through Comparison with Computational Fluid Dynamics" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;Hemodynamics is thought to be an important factor for aneurysm progression and rupture. Our aim was to evaluate whether flow fields reconstructed from dynamic angiography data can be used to realistically represent the main flow structures in intracranial aneurysms.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;DSA-based flow reconstructions, obtained during interventional treatment, were compared qualitatively with flow fields obtained from patient-specific computational fluid dynamics models and quantitatively with projections of the computational fluid dynamics fields (by computing a directional similarity of the vector fields) in 15 cerebral aneurysms.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;The average similarity between the DSA and the projected computational fluid dynamics flow fields was 78% in the parent artery, while it was only 30% in the aneurysm region. Qualitatively, both the DSA and projected computational fluid dynamics flow fields captured the location of the inflow jet, the main vortex structure, the intrasaccular flow split, and the main rotation direction in approximately 60% of the cases.&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;Several factors affect the reconstruction of 2D flow fields from dynamic angiography sequences. The most important factors are the 3-dimensionality of the intrasaccular flow patterns and inflow jets, the alignment of the main vortex structure with the line of sight, the overlapping of surrounding vessels, and possibly frame rate undersampling. Flow visualization with DSA from &amp;gt;1 projection is required for understanding of the 3D intrasaccular flow patterns. Although these DSA-based flow quantification techniques do not capture swirling or secondary flows in the parent artery, they still provide a good representation of the mean axial flow and the corresponding flow rate.&lt;/p&gt;" />
<meta name="citation_journal_title" content="American Journal of Neuroradiology" />
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<meta name="citation_publication_date" content="2017/04/06" />
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<meta name="citation_author" content="J.R. Cebral" />
<meta name="citation_author_institution" content="From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands." />
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<meta name="citation_author" content="F. Mut" />
<meta name="citation_author_institution" content="From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands." />
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<meta name="citation_author" content="B.J. Chung" />
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<meta name="citation_author_orcid" content="http://orcid.org/0000-0002-5846-7944" />
<meta name="citation_author" content="L. Spelle" />
<meta name="citation_author_institution" content="From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands." />
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<meta name="citation_author" content="J. Moret" />
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<meta name="citation_author" content="F. van Nijnatten" />
<meta name="citation_author_institution" content="From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands." />
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<meta name="citation_author" content="D. Ruijters" />
<meta name="citation_author_institution" content="From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands." />
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<meta name="twitter:title" content="Understanding Angiography-Based Aneurysm Flow Fields through Comparison with Computational Fluid Dynamics" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Hemodynamics is thought to be an important factor for aneurysm progression and rupture. Our aim was to evaluate whether flow fields reconstructed from dynamic angiography data can be used to realistically represent the main flow structures in intracranial aneurysms.

MATERIALS AND METHODS: DSA-based flow reconstructions, obtained during interventional treatment, were compared qualitatively with flow fields obtained from patient-specific computational fluid dynamics models and quantitatively with projections of the computational fluid dynamics fields (by computing a directional similarity of the vector fields) in 15 cerebral aneurysms.

RESULTS: The average similarity between the DSA and the projected computational fluid dynamics flow fields was 78% in the parent artery, while it was only 30% in the aneurysm region. Qualitatively, both the DSA and projected computational fluid dynamics flow fields captured the location of the inflow jet, the main vortex structure, the intrasaccular flow split, and the main rotation direction in approximately 60% of the cases.

CONCLUSIONS: Several factors affect the reconstruction of 2D flow fields from dynamic angiography sequences. The most important factors are the 3-dimensionality of the intrasaccular flow patterns and inflow jets, the alignment of the main vortex structure with the line of sight, the overlapping of surrounding vessels, and possibly frame rate undersampling. Flow visualization with DSA from &gt;1 projection is required for understanding of the 3D intrasaccular flow patterns. Although these DSA-based flow quantification techniques do not capture swirling or secondary flows in the parent artery, they still provide a good representation of the mean axial flow and the corresponding flow rate.

### Abbreviations

CFD
:   computational fluid dynamics
MAFA
:   mean aneurysm flow amplitude (determined from DSA)
MEAN
:   projection average
VEL
:   mean aneurysm velocity (determined from CFD)" />
<meta name="og-title" property="og:title" content="Understanding Angiography-Based Aneurysm Flow Fields through Comparison with Computational Fluid Dynamics" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/early/2017/04/06/ajnr.A5158" />
<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: Hemodynamics is thought to be an important factor for aneurysm progression and rupture. Our aim was to evaluate whether flow fields reconstructed from dynamic angiography data can be used to realistically represent the main flow structures in intracranial aneurysms.

MATERIALS AND METHODS: DSA-based flow reconstructions, obtained during interventional treatment, were compared qualitatively with flow fields obtained from patient-specific computational fluid dynamics models and quantitatively with projections of the computational fluid dynamics fields (by computing a directional similarity of the vector fields) in 15 cerebral aneurysms.

RESULTS: The average similarity between the DSA and the projected computational fluid dynamics flow fields was 78% in the parent artery, while it was only 30% in the aneurysm region. Qualitatively, both the DSA and projected computational fluid dynamics flow fields captured the location of the inflow jet, the main vortex structure, the intrasaccular flow split, and the main rotation direction in approximately 60% of the cases.

CONCLUSIONS: Several factors affect the reconstruction of 2D flow fields from dynamic angiography sequences. The most important factors are the 3-dimensionality of the intrasaccular flow patterns and inflow jets, the alignment of the main vortex structure with the line of sight, the overlapping of surrounding vessels, and possibly frame rate undersampling. Flow visualization with DSA from &gt;1 projection is required for understanding of the 3D intrasaccular flow patterns. Although these DSA-based flow quantification techniques do not capture swirling or secondary flows in the parent artery, they still provide a good representation of the mean axial flow and the corresponding flow rate.

### Abbreviations

CFD
:   computational fluid dynamics
MAFA
:   mean aneurysm flow amplitude (determined from DSA)
MEAN
:   projection average
VEL
:   mean aneurysm velocity (determined from CFD)" />
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      <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">INTERVENTIONAL</span></span></div>
  
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      <h1 class="highwire-cite-title" id="page-title">Understanding Angiography-Based Aneurysm Flow Fields through Comparison with Computational Fluid Dynamics</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">J.R. Cebral</span>, <span class="highwire-citation-author" data-delta="1">F. Mut</span>, <span class="highwire-citation-author" data-delta="2">B.J. Chung</span>, <span class="highwire-citation-author" data-delta="3">L. Spelle</span>, <span class="highwire-citation-author" data-delta="4">J. Moret</span>, <span class="highwire-citation-author" data-delta="5">F. van Nijnatten</span> and <span class="highwire-citation-author" data-delta="6">D. Ruijters</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">April 2017,  </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A5158 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-54269--62018712770" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">J.R. Cebral </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'>From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands.</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.R.%2BCebral%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=Cebral%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"><a href="/search/author1%3AJ.R.%2BCebral%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="http://orcid.org/0000-0002-3216-0856" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for J.R. Cebral</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">F. Mut </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'>From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands.</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=F.%2BMut%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=Mut%20F&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%3AF.%2BMut%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="http://orcid.org/0000-0003-1907-3739" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for F. Mut</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">B.J. Chung </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'>From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands.</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=B.J.%2BChung%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=Chung%20B&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%3AB.J.%2BChung%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="http://orcid.org/0000-0002-5846-7944" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for B.J. Chung</a></li></ul></div><div class="author-tooltip-3"><div class="author-tooltip-name">L. Spelle </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'>From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands.</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=L.%2BSpelle%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=Spelle%20L&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%3AL.%2BSpelle%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="http://orcid.org/0000-0002-6748-8528" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for L. Spelle</a></li></ul></div><div class="author-tooltip-4"><div class="author-tooltip-name">J. Moret </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'>From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands.</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.%2BMoret%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=Moret%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"><a href="/search/author1%3AJ.%2BMoret%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="http://orcid.org/0000-0002-2086-2973" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for J. Moret</a></li></ul></div><div class="author-tooltip-5"><div class="author-tooltip-name">F. van Nijnatten </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'>From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands.</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=F.%2Bvan%2BNijnatten%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=van%20Nijnatten%20F&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%3AF.%2Bvan%2BNijnatten%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="http://orcid.org/0000-0001-6108-2255" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for F. van Nijnatten</a></li></ul></div><div class="author-tooltip-6"><div class="author-tooltip-name">D. Ruijters </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'>From the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia; Faculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France; Interventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France; and Image Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands.</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.%2BRuijters%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=Ruijters%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"><a href="/search/author1%3AD.%2BRuijters%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="http://orcid.org/0000-0002-9931-4047" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for D. 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