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<meta name="DC.Title" content="Automated Estimation of Quantitative Lesion Water Uptake as a Prognostic Biomarker for Patients with Ischemic Stroke and Large-Vessel Occlusion" />
<meta name="DC.Identifier" content="10.3174/ajnr.A7741" />
<meta name="DC.Date" content="2023-01-01" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
<meta name="DC.Rights" content="© 2023 by American Journal of Neuroradiology. Indicates open access to non-subscribers at www.ajnr.org" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Net water uptake is qualified as an imaging marker of brain edema. We aimed to investigate the ability of net water uptake to predict 90-day functional outcome in patients with acute ischemic stroke and large-vessel occlusion.

MATERIALS AND METHODS: A total of 295 consecutive patients were retrospectively enrolled. Automated ASPECTS–net water uptake was calculated on the admission CT. The relationship between ASPECTS–net water uptake and 90-day neurologic outcome was assessed. The independent predictors of favorable outcome (mRS score ≤2) were assessed using multivariate logistic regression analysis and receiver operating characteristic curves and stratified by the ASPECTS.

RESULTS: Favorable 90-day outcomes were observed in 156 (52.9%) patients. ASPECTS–net water uptake (OR, 0.79; 95% CI, 0.70–0.90), NIHSS scores (OR, 0.91; 95% CI, 0.87–0.96), age (OR, 0.96; 95% CI, 0.94–0.99), and vessel recanalization (OR, 7.78; 95% CI, 3.96–15.29) were independently associated with favorable outcomes at 90 days (all, P  &lt; .01). A lower ASPECTS–net water uptake independently predicted a good prognosis, even in the subgroup of patients with low ASPECTS (≤5) ( P  &lt; .05). An outcome-prediction model based on these variables yielded an area under the receiver operating characteristic curve of 0.856 (95% CI, 0.814–0.899; sensitivity, 76.3%; specificity, 81.3%).

CONCLUSIONS: ASPECTS–net water uptake could independently predict 90-day neurologic outcomes in patients with acute ischemic stroke and large-vessel occlusion. Integrating ASPECTS–net water uptake with clinical models could improve the efficiency of outcome stratification.

AIS
:   acute ischemic stroke
AUC
:   area under the curve
IQR
:   interquartile range
LVO
:   large-vessel occlusion
MT
:   mechanical thrombectomy
mTICI
:   modified TICI
NWU
:   net water uptake
ROC
:   receiver operating characteristic" />
<meta name="DC.Contributor" content="S.S. Lu" />
<meta name="DC.Contributor" content="R.R. Wu" />
<meta name="DC.Contributor" content="Y.Z. Cao" />
<meta name="DC.Contributor" content="X.Q. Xu" />
<meta name="DC.Contributor" content="Z.Y. Jia" />
<meta name="DC.Contributor" content="H.B. Shi" />
<meta name="DC.Contributor" content="S. Liu" />
<meta name="DC.Contributor" content="F.Y. Wu" />
<meta name="article:published_time" content="2023-01-01" />
<meta name="article:section" content="Adult Brain" />
<meta name="citation_title" content="Automated Estimation of Quantitative Lesion Water Uptake as a Prognostic Biomarker for Patients with Ischemic Stroke and Large-Vessel Occlusion" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;Net water uptake is qualified as an imaging marker of brain edema. We aimed to investigate the ability of net water uptake to predict 90-day functional outcome in patients with acute ischemic stroke and large-vessel occlusion.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;A total of 295 consecutive patients were retrospectively enrolled. Automated ASPECTS–net water uptake was calculated on the admission CT. The relationship between ASPECTS–net water uptake and 90-day neurologic outcome was assessed. The independent predictors of favorable outcome (mRS score ≤2) were assessed using multivariate logistic regression analysis and receiver operating characteristic curves and stratified by the ASPECTS.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;Favorable 90-day outcomes were observed in 156 (52.9%) patients. ASPECTS–net water uptake (OR, 0.79; 95% CI, 0.70–0.90), NIHSS scores (OR, 0.91; 95% CI, 0.87–0.96), age (OR, 0.96; 95% CI, 0.94–0.99), and vessel recanalization (OR, 7.78; 95% CI, 3.96–15.29) were independently associated with favorable outcomes at 90 days (all, &lt;i&gt;P &lt;/i&gt;&amp;lt; .01). A lower ASPECTS–net water uptake independently predicted a good prognosis, even in the subgroup of patients with low ASPECTS (≤5) (&lt;i&gt;P &lt;/i&gt;&amp;lt; .05). An outcome-prediction model based on these variables yielded an area under the receiver operating characteristic curve of 0.856 (95% CI, 0.814–0.899; sensitivity, 76.3%; specificity, 81.3%).&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;ASPECTS–net water uptake could independently predict 90-day neurologic outcomes in patients with acute ischemic stroke and large-vessel occlusion. Integrating ASPECTS–net water uptake with clinical models could improve the efficiency of outcome stratification.&lt;/p&gt;" />
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<meta name="twitter:title" content="Automated Estimation of Quantitative Lesion Water Uptake as a Prognostic Biomarker for Patients with Ischemic Stroke and Large-Vessel Occlusion" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Net water uptake is qualified as an imaging marker of brain edema. We aimed to investigate the ability of net water uptake to predict 90-day functional outcome in patients with acute ischemic stroke and large-vessel occlusion.

MATERIALS AND METHODS: A total of 295 consecutive patients were retrospectively enrolled. Automated ASPECTS–net water uptake was calculated on the admission CT. The relationship between ASPECTS–net water uptake and 90-day neurologic outcome was assessed. The independent predictors of favorable outcome (mRS score ≤2) were assessed using multivariate logistic regression analysis and receiver operating characteristic curves and stratified by the ASPECTS.

RESULTS: Favorable 90-day outcomes were observed in 156 (52.9%) patients. ASPECTS–net water uptake (OR, 0.79; 95% CI, 0.70–0.90), NIHSS scores (OR, 0.91; 95% CI, 0.87–0.96), age (OR, 0.96; 95% CI, 0.94–0.99), and vessel recanalization (OR, 7.78; 95% CI, 3.96–15.29) were independently associated with favorable outcomes at 90 days (all, P  &lt; .01). A lower ASPECTS–net water uptake independently predicted a good prognosis, even in the subgroup of patients with low ASPECTS (≤5) ( P  &lt; .05). An outcome-prediction model based on these variables yielded an area under the receiver operating characteristic curve of 0.856 (95% CI, 0.814–0.899; sensitivity, 76.3%; specificity, 81.3%).

CONCLUSIONS: ASPECTS–net water uptake could independently predict 90-day neurologic outcomes in patients with acute ischemic stroke and large-vessel occlusion. Integrating ASPECTS–net water uptake with clinical models could improve the efficiency of outcome stratification.

AIS
:   acute ischemic stroke
AUC
:   area under the curve
IQR
:   interquartile range
LVO
:   large-vessel occlusion
MT
:   mechanical thrombectomy
mTICI
:   modified TICI
NWU
:   net water uptake
ROC
:   receiver operating characteristic" />
<meta name="og-title" property="og:title" content="Automated Estimation of Quantitative Lesion Water Uptake as a Prognostic Biomarker for Patients with Ischemic Stroke and Large-Vessel Occlusion" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/44/1/33" />
<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: Net water uptake is qualified as an imaging marker of brain edema. We aimed to investigate the ability of net water uptake to predict 90-day functional outcome in patients with acute ischemic stroke and large-vessel occlusion.

MATERIALS AND METHODS: A total of 295 consecutive patients were retrospectively enrolled. Automated ASPECTS–net water uptake was calculated on the admission CT. The relationship between ASPECTS–net water uptake and 90-day neurologic outcome was assessed. The independent predictors of favorable outcome (mRS score ≤2) were assessed using multivariate logistic regression analysis and receiver operating characteristic curves and stratified by the ASPECTS.

RESULTS: Favorable 90-day outcomes were observed in 156 (52.9%) patients. ASPECTS–net water uptake (OR, 0.79; 95% CI, 0.70–0.90), NIHSS scores (OR, 0.91; 95% CI, 0.87–0.96), age (OR, 0.96; 95% CI, 0.94–0.99), and vessel recanalization (OR, 7.78; 95% CI, 3.96–15.29) were independently associated with favorable outcomes at 90 days (all, P  &lt; .01). A lower ASPECTS–net water uptake independently predicted a good prognosis, even in the subgroup of patients with low ASPECTS (≤5) ( P  &lt; .05). An outcome-prediction model based on these variables yielded an area under the receiver operating characteristic curve of 0.856 (95% CI, 0.814–0.899; sensitivity, 76.3%; specificity, 81.3%).

CONCLUSIONS: ASPECTS–net water uptake could independently predict 90-day neurologic outcomes in patients with acute ischemic stroke and large-vessel occlusion. Integrating ASPECTS–net water uptake with clinical models could improve the efficiency of outcome stratification.

AIS
:   acute ischemic stroke
AUC
:   area under the curve
IQR
:   interquartile range
LVO
:   large-vessel occlusion
MT
:   mechanical thrombectomy
mTICI
:   modified TICI
NWU
:   net water uptake
ROC
:   receiver operating characteristic" />
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    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">S.S. Lu</span>, <span class="highwire-citation-author" data-delta="1">R.R. Wu</span>, <span class="highwire-citation-author" data-delta="2">Y.Z. Cao</span>, <span class="highwire-citation-author" data-delta="3">X.Q. Xu</span>, <span class="highwire-citation-author" data-delta="4">Z.Y. Jia</span>, <span class="highwire-citation-author" data-delta="5">H.B. Shi</span>, <span class="highwire-citation-author" data-delta="6">S. Liu</span> and <span class="highwire-citation-author" data-delta="7">F.Y. Wu</span></span></div>
  
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<div id="hw-article-author-popups-top-node-100595--6269931672" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">S.S. Lu </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Radiology (S.S.L., R.R.W., X.Q.X., F.Y.W.)</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.S.%2BLu%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=Lu%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.S.%2BLu%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/0000-0002-5438-8050" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for S.S. Lu</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">R.R. Wu </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Radiology (S.S.L., R.R.W., X.Q.X., F.Y.W.)</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.R.%2BWu%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=Wu%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.R.%2BWu%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/0000-0003-4140-4637" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for R.R. Wu</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">Y.Z. Cao </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Interventional Radiology (Y.Z.C., Z.Y.J., H.B.S., S.L.), The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China</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.Z.%2BCao%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=Cao%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.Z.%2BCao%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/0000-0002-2449-7379" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Y.Z. Cao</a></li></ul></div><div class="author-tooltip-3"><div class="author-tooltip-name">X.Q. Xu </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Radiology (S.S.L., R.R.W., X.Q.X., F.Y.W.)</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=X.Q.%2BXu%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=Xu%20X&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%3AX.Q.%2BXu%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/0000-0001-5493-5256" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for X.Q. Xu</a></li></ul></div><div class="author-tooltip-4"><div class="author-tooltip-name">Z.Y. Jia </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Interventional Radiology (Y.Z.C., Z.Y.J., H.B.S., S.L.), The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China</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.Y.%2BJia%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=Jia%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.Y.%2BJia%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/0000-0002-5134-9339" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Z.Y. Jia</a></li></ul></div><div class="author-tooltip-5"><div class="author-tooltip-name">H.B. Shi </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Interventional Radiology (Y.Z.C., Z.Y.J., H.B.S., S.L.), The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China</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=H.B.%2BShi%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=Shi%20H&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%3AH.B.%2BShi%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/0000-0003-1293-5789" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for H.B. Shi</a></li></ul></div><div class="author-tooltip-6"><div class="author-tooltip-name">S. Liu </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Interventional Radiology (Y.Z.C., Z.Y.J., H.B.S., S.L.), The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China</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.%2BLiu%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=Liu%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.%2BLiu%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/0000-0002-4058-4413" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for S. Liu</a></li></ul></div><div class="author-tooltip-7"><div class="author-tooltip-name">F.Y. Wu </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Radiology (S.S.L., R.R.W., X.Q.X., F.Y.W.)</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.Y.%2BWu%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=Wu%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.Y.%2BWu%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/0000-0002-0343-0458" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for F.Y. 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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-44.1.33.1" data-doi="10.1056/NEJMoa1713973"><div class="cit-metadata"><ol class="cit-auth-list"><li><span class="cit-auth"><span class="cit-name-surname">Albers</span>  <span class="cit-name-given-names">GW</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Marks</span>  <span class="cit-name-given-names">MP</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Kemp</span>  <span class="cit-name-given-names">S</span></span>, <span class="cit-etal">et al</span></li></ol><cite>; <span class="cit-auth cit-collab">DEFUSE 3 Investigators</span>. 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href="#xref-ref-5-1" title="View reference 5. in text" id="ref-5">↵</a><div class="cit ref-cit ref-journal" id="cit-44.1.33.5" data-doi="10.1212/WNL.0000000000008481"><div class="cit-metadata"><ol class="cit-auth-list"><li><span class="cit-auth"><span class="cit-name-surname">Vagal</span>  <span class="cit-name-given-names">A</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Wintermark</span>  <span class="cit-name-given-names">M</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Nael</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">Automated CT perfusion imaging for acute ischemic stroke: Pearls and pitfalls for real-world use</span>. <abbr class="cit-jnl-abbrev">Neurology</abbr> <span class="cit-pub-date">2019</span>;<span class="cit-vol">93</span>:<span class="cit-fpage">888</span>–<span class="cit-lpage">98</span><span 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class="ref-label">6.</span><a class="rev-xref-ref" href="#xref-ref-6-1" title="View reference 6. in text" id="ref-6">↵</a><div class="cit ref-cit ref-journal" id="cit-44.1.33.6" data-doi="10.1159/000490117"><div class="cit-metadata"><ol class="cit-auth-list"><li><span class="cit-auth"><span class="cit-name-surname">Martins</span>  <span class="cit-name-given-names">N</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Aires</span>  <span class="cit-name-given-names">A</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Mendez</span>  <span class="cit-name-given-names">B</span></span>, <span class="cit-etal">et al</span></li></ol><cite>. <span class="cit-article-title">Ghost infarct core and admission computed tomography perfusion: redefining the role of neuroimaging in acute ischemic stroke</span>. <abbr class="cit-jnl-abbrev">Interv Neurol</abbr> <span class="cit-pub-date">2018</span>;<span class="cit-vol">7</span>:<span 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data-doi="10.1111/jon.12692"><div class="cit-metadata"><ol class="cit-auth-list"><li><span class="cit-auth"><span class="cit-name-surname">Rotem</span>  <span class="cit-name-given-names">SH</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Mor</span>  <span class="cit-name-given-names">S</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Chen</span>  <span class="cit-name-given-names">B</span></span>, <span class="cit-etal">et al</span></li></ol><cite>. <span class="cit-article-title">Infarct core reliability by CT perfusion is a time-dependent phenomenon</span>. <abbr class="cit-jnl-abbrev">J Neuroimaging</abbr> <span class="cit-pub-date">2020</span>;<span class="cit-vol">30</span>:<span class="cit-fpage">240</span>–<span class="cit-lpage">45</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>10.1111/jon.12692</span><span 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class="cit-auth"><span class="cit-name-surname">Broocks</span>  <span class="cit-name-given-names">G</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Kniep</span>  <span class="cit-name-given-names">H</span></span>, </li><li><span class="cit-auth"><span class="cit-name-surname">Schramm</span>  <span class="cit-name-given-names">P</span></span>, <span class="cit-etal">et al</span></li></ol><cite>. <span class="cit-article-title">Patients with low Alberta Stroke Program Early CT Score (ASPECTS) but good collaterals benefit from endovascular recanalization</span>. <abbr class="cit-jnl-abbrev">J Neurointerv Surg</abbr> <span class="cit-pub-date">2020</span>;<span class="cit-vol">12</span>:<span class="cit-fpage">747</span>–<span class="cit-lpage">52</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>10.1136/neurintsurg-2019-015308</span><span class="cit-pub-id-sep 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        	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-volume highwire-cite-metadata">Vol. 44</span>, <span  class="highwire-cite-metadata-issue highwire-cite-metadata">Issue 1 </span><div  class="highwire-cite-metadata-pubdate highwire-cite-metadata">1 Jan 2023 </div></div>
      
      
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    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-oa-ind highwire-cite-metadata"><i class="highwire-oa-indicator"></i> </span><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">Jan 2023, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">44 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(1) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">33-39; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A7741 </span></div>
  
  
  
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      <div class="highwire-cite-title">Automated Estimation of Quantitative Lesion Water Uptake as a Prognostic Biomarker for Patients with Ischemic Stroke and Large-Vessel Occlusion</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.S.</span> <span class="nlm-surname">Lu</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">R.R.</span> <span class="nlm-surname">Wu</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">Y.Z.</span> <span class="nlm-surname">Cao</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">X.Q.</span> <span class="nlm-surname">Xu</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">Z.Y.</span> <span class="nlm-surname">Jia</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">H.B.</span> <span class="nlm-surname">Shi</span></span>, <span class="highwire-citation-author" data-delta="6"><span class="nlm-given-names">S.</span> <span class="nlm-surname">Liu</span></span>, <span class="highwire-citation-author" data-delta="7"><span class="nlm-given-names">F.Y.</span> <span class="nlm-surname">Wu</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">Jan 2023, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">44 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(1) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">33-39; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A7741 </span></div>
  
  
  
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