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<meta name="category" content="research-article" />
<meta name="HW.identifier" content="/ajnr/early/2024/12/05/ajnr.A8434.atom" />
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<meta name="DC.Title" content="Combinations of Clinical Factors, CT Signs, and Radiomics for Differentiating High-Density Areas after Mechanical Thrombectomy in Patients with Acute Ischemic Stroke" />
<meta name="DC.Identifier" content="10.3174/ajnr.A8434" />
<meta name="DC.Date" content="2024-12-05" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
<meta name="DC.Rights" content="© 2024 by American Journal of Neuroradiology" />
<meta name="DC.AccessRights" content="restricted" />
<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Clinically, hemorrhagic transformation (HT) after mechanical thrombectomy (MT) is a common complication. This study aimed to investigate the value of clinical factors, CT signs, and radiomics in the differential diagnosis of high-density areas (HDAs) in the brain after MT in patients with acute ischemic stroke with large-vessel occlusion (AIS-LVO).

MATERIALS AND METHODS: A total of 156 eligible patients with AIS-LVO in Center I from December 2015 to June 2023 were retrospectively enrolled and randomly divided into training ( n = 109) and internal validation ( n = 47) sets at a ratio of 7:3. The data of 63 patients in Center II were collected as an external validation set. According to the diagnostic criteria, the patients in the 3 data sets were divided into an HT group and a non-HT group. The clinical and imaging data from Centers I and II were used to construct a clinical factor and CT-sign model, a radiomics model, and a combined model by logistic regression. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy of each model in the 3 data sets.

RESULTS: Clinical blood glucose and the maximum cross-sectional area on CT were associated with the HT or non-HT of the HDA according to multivariate logistic regression analyses ( P &lt; .05). Among the 3 models, the combined model had the highest diagnostic efficiency, with area under the curve values of 0.895, 0.882, and 0.820 in the 3 data sets, which were significantly greater than the area under the curve values of the radiomics model (0.887, 0.898, 0.798) and clinical factor and CT-sign model (0.831, 0.744, 0.684).

CONCLUSIONS: The combined model based on radiomics had the best performance, indicating that radiomics features can be used as imaging biomarkers to aid in the clinical judgment of the nature of HDA after MT.

AIS-LVO
:   acute ischemic stroke with large-vessel occlusion
Areamax
:   maximum cross-sectional area
AUC
:   area under the curve
DCA
:   decision curve analysis
D-D
:   D-dimer
DECT
:   dual-energy CT
DPT
:   door-to-puncture time
HDA
:   high-density area
HT
:   hemorrhagic transformation
ICE
:   iodine contrast extravasation
IOM
:   iodine overlay map
LASSO
:   least absolute shrinkage and selection operator
LR
:   logistic regression
MT
:   mechanical thrombectomy
PLT
:   platelet
ROC
:   receiver operating characteristic
TG
:   total cholesterol triglyceride
VNC
:   virtual noncontrast" />
<meta name="DC.Contributor" content="Duchang Zhai" />
<meta name="DC.Contributor" content="Yuanyuan Wu" />
<meta name="DC.Contributor" content="Manman Cui" />
<meta name="DC.Contributor" content="Yan Liu" />
<meta name="DC.Contributor" content="Xiuzhi Zhou" />
<meta name="DC.Contributor" content="Dongliang Hu" />
<meta name="DC.Contributor" content="Yuancheng Wang" />
<meta name="DC.Contributor" content="Shenghong Ju" />
<meta name="DC.Contributor" content="Guohua Fan" />
<meta name="DC.Contributor" content="Wu Cai" />
<meta name="article:published_time" content="2024-12-05" />
<meta name="article:section" content="NEUROVASCULAR/STROKE IMAGING" />
<meta name="citation_title" content="Combinations of Clinical Factors, CT Signs, and Radiomics for Differentiating High-Density Areas after Mechanical Thrombectomy in Patients with Acute Ischemic Stroke" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;Clinically, hemorrhagic transformation (HT) after mechanical thrombectomy (MT) is a common complication. This study aimed to investigate the value of clinical factors, CT signs, and radiomics in the differential diagnosis of high-density areas (HDAs) in the brain after MT in patients with acute ischemic stroke with large-vessel occlusion (AIS-LVO).&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;A total of 156 eligible patients with AIS-LVO in Center I from December 2015 to June 2023 were retrospectively enrolled and randomly divided into training (&lt;i&gt;n&lt;/i&gt; = 109) and internal validation (&lt;i&gt;n&lt;/i&gt; = 47) sets at a ratio of 7:3. The data of 63 patients in Center II were collected as an external validation set. According to the diagnostic criteria, the patients in the 3 data sets were divided into an HT group and a non-HT group. The clinical and imaging data from Centers I and II were used to construct a clinical factor and CT-sign model, a radiomics model, and a combined model by logistic regression. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy of each model in the 3 data sets.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;Clinical blood glucose and the maximum cross-sectional area on CT were associated with the HT or non-HT of the HDA according to multivariate logistic regression analyses (&lt;i&gt;P&lt;/i&gt; &amp;lt; .05). Among the 3 models, the combined model had the highest diagnostic efficiency, with area under the curve values of 0.895, 0.882, and 0.820 in the 3 data sets, which were significantly greater than the area under the curve values of the radiomics model (0.887, 0.898, 0.798) and clinical factor and CT-sign model (0.831, 0.744, 0.684).&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;The combined model based on radiomics had the best performance, indicating that radiomics features can be used as imaging biomarkers to aid in the clinical judgment of the nature of HDA after MT.&lt;/p&gt;" />
<meta name="citation_journal_title" content="American Journal of Neuroradiology" />
<meta name="citation_publisher" content="American Journal of Neuroradiology" />
<meta name="citation_publication_date" content="2024/12/05" />
<meta name="citation_mjid" content="ajnr;ajnr.A8434v2" />
<meta name="citation_id" content="ajnr.A8434v2" />
<meta name="citation_public_url" content="http://ajnr-stage2.stage.highwire.org/content/early/2024/12/05/ajnr.A8434" />
<meta name="citation_abstract_html_url" content="http://ajnr-stage2.stage.highwire.org/content/early/2024/12/05/ajnr.A8434.abstract" />
<meta name="citation_full_html_url" content="http://ajnr-stage2.stage.highwire.org/content/early/2024/12/05/ajnr.A8434.full" />
<meta name="citation_pdf_url" content="http://ajnr-stage2.stage.highwire.org/content/ajnr/early/2024/12/05/ajnr.A8434.full.pdf" />
<meta name="citation_issn" content="0195-6108" />
<meta name="citation_issn" content="1936-959X" />
<meta name="citation_doi" content="10.3174/ajnr.A8434" />
<meta name="citation_pmid" content="39122469" />
<meta name="citation_article_type" content="Research Article" />
<meta name="citation_section" content="NEUROVASCULAR/STROKE IMAGING" />
<meta name="citation_author" content="Duchang Zhai" />
<meta name="citation_author_institution" content="aFrom the Department of Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China" />
<meta name="citation_author_orcid" content="https://orcid.org/0000-0002-3435-5892" />
<meta name="citation_author" content="Yuanyuan Wu" />
<meta name="citation_author_institution" content="aFrom the Department of Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China" />
<meta name="citation_author" content="Manman Cui" />
<meta name="citation_author_institution" content="aFrom the Department of Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China" />
<meta name="citation_author_orcid" content="https://orcid.org/0009-0009-0431-2283" />
<meta name="citation_author" content="Yan Liu" />
<meta name="citation_author_institution" content="aFrom the Department of Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China" />
<meta name="citation_author_orcid" content="https://orcid.org/0009-0006-3543-1136" />
<meta name="citation_author" content="Xiuzhi Zhou" />
<meta name="citation_author_institution" content="aFrom the Department of Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China" />
<meta name="citation_author_orcid" content="https://orcid.org/0009-0002-2647-0994" />
<meta name="citation_author" content="Dongliang Hu" />
<meta name="citation_author_institution" content="aFrom the Department of Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China" />
<meta name="citation_author" content="Yuancheng Wang" />
<meta name="citation_author_institution" content="bDepartment of Radiology (Y. Wang, S.J.), Zhongda Hospital, Medical School of Southeast University, Nanjing, Jiangsu, China." />
<meta name="citation_author" content="Shenghong Ju" />
<meta name="citation_author_institution" content="bDepartment of Radiology (Y. Wang, S.J.), Zhongda Hospital, Medical School of Southeast University, Nanjing, Jiangsu, China." />
<meta name="citation_author_orcid" content="https://orcid.org/0000-0001-5041-7865" />
<meta name="citation_author" content="Guohua Fan" />
<meta name="citation_author_institution" content="aFrom the Department of Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China" />
<meta name="citation_author_orcid" content="https://orcid.org/0009-0001-6278-0773" />
<meta name="citation_author" content="Wu Cai" />
<meta name="citation_author_institution" content="aFrom the Department of Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China" />
<meta name="citation_author_orcid" content="https://orcid.org/0000-0002-6800-4177" />
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<meta name="twitter:title" content="Combinations of Clinical Factors, CT Signs, and Radiomics for Differentiating High-Density Areas after Mechanical Thrombectomy in Patients with Acute Ischemic Stroke" />
<meta name="twitter:card" content="summary" />
<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Clinically, hemorrhagic transformation (HT) after mechanical thrombectomy (MT) is a common complication. This study aimed to investigate the value of clinical factors, CT signs, and radiomics in the differential diagnosis of high-density areas (HDAs) in the brain after MT in patients with acute ischemic stroke with large-vessel occlusion (AIS-LVO).

MATERIALS AND METHODS: A total of 156 eligible patients with AIS-LVO in Center I from December 2015 to June 2023 were retrospectively enrolled and randomly divided into training ( n = 109) and internal validation ( n = 47) sets at a ratio of 7:3. The data of 63 patients in Center II were collected as an external validation set. According to the diagnostic criteria, the patients in the 3 data sets were divided into an HT group and a non-HT group. The clinical and imaging data from Centers I and II were used to construct a clinical factor and CT-sign model, a radiomics model, and a combined model by logistic regression. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy of each model in the 3 data sets.

RESULTS: Clinical blood glucose and the maximum cross-sectional area on CT were associated with the HT or non-HT of the HDA according to multivariate logistic regression analyses ( P &lt; .05). Among the 3 models, the combined model had the highest diagnostic efficiency, with area under the curve values of 0.895, 0.882, and 0.820 in the 3 data sets, which were significantly greater than the area under the curve values of the radiomics model (0.887, 0.898, 0.798) and clinical factor and CT-sign model (0.831, 0.744, 0.684).

CONCLUSIONS: The combined model based on radiomics had the best performance, indicating that radiomics features can be used as imaging biomarkers to aid in the clinical judgment of the nature of HDA after MT.

AIS-LVO
:   acute ischemic stroke with large-vessel occlusion
Areamax
:   maximum cross-sectional area
AUC
:   area under the curve
DCA
:   decision curve analysis
D-D
:   D-dimer
DECT
:   dual-energy CT
DPT
:   door-to-puncture time
HDA
:   high-density area
HT
:   hemorrhagic transformation
ICE
:   iodine contrast extravasation
IOM
:   iodine overlay map
LASSO
:   least absolute shrinkage and selection operator
LR
:   logistic regression
MT
:   mechanical thrombectomy
PLT
:   platelet
ROC
:   receiver operating characteristic
TG
:   total cholesterol triglyceride
VNC
:   virtual noncontrast" />
<meta name="og-title" property="og:title" content="Combinations of Clinical Factors, CT Signs, and Radiomics for Differentiating High-Density Areas after Mechanical Thrombectomy in Patients with Acute Ischemic Stroke" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/early/2024/12/05/ajnr.A8434" />
<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: Clinically, hemorrhagic transformation (HT) after mechanical thrombectomy (MT) is a common complication. This study aimed to investigate the value of clinical factors, CT signs, and radiomics in the differential diagnosis of high-density areas (HDAs) in the brain after MT in patients with acute ischemic stroke with large-vessel occlusion (AIS-LVO).

MATERIALS AND METHODS: A total of 156 eligible patients with AIS-LVO in Center I from December 2015 to June 2023 were retrospectively enrolled and randomly divided into training ( n = 109) and internal validation ( n = 47) sets at a ratio of 7:3. The data of 63 patients in Center II were collected as an external validation set. According to the diagnostic criteria, the patients in the 3 data sets were divided into an HT group and a non-HT group. The clinical and imaging data from Centers I and II were used to construct a clinical factor and CT-sign model, a radiomics model, and a combined model by logistic regression. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy of each model in the 3 data sets.

RESULTS: Clinical blood glucose and the maximum cross-sectional area on CT were associated with the HT or non-HT of the HDA according to multivariate logistic regression analyses ( P &lt; .05). Among the 3 models, the combined model had the highest diagnostic efficiency, with area under the curve values of 0.895, 0.882, and 0.820 in the 3 data sets, which were significantly greater than the area under the curve values of the radiomics model (0.887, 0.898, 0.798) and clinical factor and CT-sign model (0.831, 0.744, 0.684).

CONCLUSIONS: The combined model based on radiomics had the best performance, indicating that radiomics features can be used as imaging biomarkers to aid in the clinical judgment of the nature of HDA after MT.

AIS-LVO
:   acute ischemic stroke with large-vessel occlusion
Areamax
:   maximum cross-sectional area
AUC
:   area under the curve
DCA
:   decision curve analysis
D-D
:   D-dimer
DECT
:   dual-energy CT
DPT
:   door-to-puncture time
HDA
:   high-density area
HT
:   hemorrhagic transformation
ICE
:   iodine contrast extravasation
IOM
:   iodine overlay map
LASSO
:   least absolute shrinkage and selection operator
LR
:   logistic regression
MT
:   mechanical thrombectomy
PLT
:   platelet
ROC
:   receiver operating characteristic
TG
:   total cholesterol triglyceride
VNC
:   virtual noncontrast" />
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    <div class="highwire-article-citation highwire-citation-type-highwire-article node112186--5" data-node-nid="112186" id="top-node-112186--6822279358" data-pisa="ajnr;ajnr.A8434v2" data-pisa-master="ajnr;ajnr.A8434" data-apath="/ajnr/early/2024/12/05/ajnr.A8434.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">
  
  
      <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">NEUROVASCULAR/STROKE IMAGING</span></span></div>
  
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      <h1 class="highwire-cite-title" id="page-title">Combinations of Clinical Factors, CT Signs, and Radiomics for Differentiating High-Density Areas after Mechanical Thrombectomy in Patients with Acute Ischemic Stroke</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">Duchang Zhai</span>, <span class="highwire-citation-author" data-delta="1">Yuanyuan Wu</span>, <span class="highwire-citation-author" data-delta="2">Manman Cui</span>, <span class="highwire-citation-author" data-delta="3">Yan Liu</span>, <span class="highwire-citation-author" data-delta="4">Xiuzhi Zhou</span>, <span class="highwire-citation-author" data-delta="5">Dongliang Hu</span>, <span class="highwire-citation-author" data-delta="6">Yuancheng Wang</span>, <span class="highwire-citation-author" data-delta="7">Shenghong Ju</span>, <span class="highwire-citation-author" data-delta="8">Guohua Fan</span> and <span class="highwire-citation-author" data-delta="9">Wu Cai</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">December 2024,  </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A8434 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-112186--6822279358" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">Duchang Zhai </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 Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 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=Duchang%2BZhai%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=Zhai%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%3ADuchang%2BZhai%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/0000-0002-3435-5892" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Duchang Zhai</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">Yuanyuan Wu </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 Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 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=Yuanyuan%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%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 last"><a href="/search/author1%3AYuanyuan%2BWu%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">Manman Cui </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 Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 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=Manman%2BCui%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=Cui%20M&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AManman%2BCui%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/0009-0009-0431-2283" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Manman Cui</a></li></ul></div><div class="author-tooltip-3"><div class="author-tooltip-name">Yan Liu </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 Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 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=Yan%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%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%3AYan%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/0009-0006-3543-1136" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Yan Liu</a></li></ul></div><div class="author-tooltip-4"><div class="author-tooltip-name">Xiuzhi Zhou </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 Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 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=Xiuzhi%2BZhou%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=Zhou%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%3AXiuzhi%2BZhou%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/0009-0002-2647-0994" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Xiuzhi Zhou</a></li></ul></div><div class="author-tooltip-5"><div class="author-tooltip-name">Dongliang Hu </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 Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 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=Dongliang%2BHu%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=Hu%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 last"><a href="/search/author1%3ADongliang%2BHu%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-6"><div class="author-tooltip-name">Yuancheng Wang </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Department of Radiology (Y. Wang, S.J.), Zhongda Hospital, Medical School of Southeast University, Nanjing, Jiangsu, 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=Yuancheng%2BWang%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=Wang%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 last"><a href="/search/author1%3AYuancheng%2BWang%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-7"><div class="author-tooltip-name">Shenghong Ju </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Department of Radiology (Y. Wang, S.J.), Zhongda Hospital, Medical School of Southeast University, Nanjing, Jiangsu, 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=Shenghong%2BJu%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=Ju%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%3AShenghong%2BJu%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/0000-0001-5041-7865" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Shenghong Ju</a></li></ul></div><div class="author-tooltip-8"><div class="author-tooltip-name">Guohua Fan </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 Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 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=Guohua%2BFan%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=Fan%20G&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%3AGuohua%2BFan%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/0009-0001-6278-0773" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Guohua Fan</a></li></ul></div><div class="author-tooltip-9"><div class="author-tooltip-name">Wu Cai </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 Radiology (D.Z., Y. Wu., M.C., Y.L., X.Z., D.H., G.F., W.C.), The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 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=Wu%2BCai%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=Cai%20W&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%3AWu%2BCai%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/0000-0002-6800-4177" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Wu Cai</a></li></ul></div></div></div>  </div>

  
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    <div class="highwire-markup"><div xmlns="http://www.w3.org/1999/xhtml" data-highwire-cite-ref-tooltip-instance="highwire_reflinks_tooltip" class="content-block-markup" xmlns:xhtml="http://www.w3.org/1999/xhtml"><div class="article abstract-view "><span class="highwire-journal-article-marker-start"></span><div class="section abstract" id="abstract-1"><h2>Abstract</h2><div id="sec-1" class="subsection"><p id="p-1"><strong>BACKGROUND AND PURPOSE:</strong> Clinically, hemorrhagic transformation (HT) after mechanical thrombectomy (MT) is a common complication. This study aimed to investigate the value of clinical factors, CT signs, and radiomics in the differential diagnosis of high-density areas (HDAs) in the brain after MT in patients with acute ischemic stroke with large-vessel occlusion (AIS-LVO).</p></div><div id="sec-2" class="subsection"><p id="p-2"><strong>MATERIALS AND METHODS:</strong> A total of 156 eligible patients with AIS-LVO in Center I from December 2015 to June 2023 were retrospectively enrolled and randomly divided into training (<em>n</em> = 109) and internal validation (<em>n</em> = 47) sets at a ratio of 7:3. The data of 63 patients in Center II were collected as an external validation set. According to the diagnostic criteria, the patients in the 3 data sets were divided into an HT group and a non-HT group. The clinical and imaging data from Centers I and II were used to construct a clinical factor and CT-sign model, a radiomics model, and a combined model by logistic regression. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy of each model in the 3 data sets.</p></div><div id="sec-3" class="subsection"><p id="p-3"><strong>RESULTS:</strong> Clinical blood glucose and the maximum cross-sectional area on CT were associated with the HT or non-HT of the HDA according to multivariate logistic regression analyses (<em>P</em> &lt; .05). Among the 3 models, the combined model had the highest diagnostic efficiency, with area under the curve values of 0.895, 0.882, and 0.820 in the 3 data sets, which were significantly greater than the area under the curve values of the radiomics model (0.887, 0.898, 0.798) and clinical factor and CT-sign model (0.831, 0.744, 0.684).</p></div><div id="sec-4" class="subsection"><p id="p-4"><strong>CONCLUSIONS:</strong> The combined model based on radiomics had the best performance, indicating that radiomics features can be used as imaging biomarkers to aid in the clinical judgment of the nature of HDA after MT.</p></div></div><div class="section glossary" id="glossary-1"><h2 class="">ABBREVIATIONS:</h2><dl id="def-list-1"><dt id="def-item-1">AIS-LVO<span class="def-item-dt-sep"></span></dt><dd>acute ischemic stroke with large-vessel occlusion<span class="def-item-dd-sep"></span></dd><dt id="def-item-2">Area<sub>max</sub><span class="def-item-dt-sep"></span></dt><dd>maximum cross-sectional area<span class="def-item-dd-sep"></span></dd><dt id="def-item-3">AUC<span class="def-item-dt-sep"></span></dt><dd>area under the curve<span class="def-item-dd-sep"></span></dd><dt id="def-item-4">DCA<span class="def-item-dt-sep"></span></dt><dd>decision curve analysis<span class="def-item-dd-sep"></span></dd><dt id="def-item-5">D-D<span class="def-item-dt-sep"></span></dt><dd>D-dimer<span class="def-item-dd-sep"></span></dd><dt id="def-item-6">DECT<span class="def-item-dt-sep"></span></dt><dd>dual-energy CT<span class="def-item-dd-sep"></span></dd><dt id="def-item-7">DPT<span class="def-item-dt-sep"></span></dt><dd>door-to-puncture time<span class="def-item-dd-sep"></span></dd><dt id="def-item-8">HDA<span class="def-item-dt-sep"></span></dt><dd>high-density area<span class="def-item-dd-sep"></span></dd><dt id="def-item-9">HT<span class="def-item-dt-sep"></span></dt><dd>hemorrhagic transformation<span class="def-item-dd-sep"></span></dd><dt id="def-item-10">ICE<span class="def-item-dt-sep"></span></dt><dd>iodine contrast extravasation<span class="def-item-dd-sep"></span></dd><dt id="def-item-11">IOM<span class="def-item-dt-sep"></span></dt><dd>iodine overlay map<span class="def-item-dd-sep"></span></dd><dt id="def-item-12">LASSO<span class="def-item-dt-sep"></span></dt><dd>least absolute shrinkage and selection operator<span class="def-item-dd-sep"></span></dd><dt id="def-item-13">LR<span class="def-item-dt-sep"></span></dt><dd>logistic regression<span class="def-item-dd-sep"></span></dd><dt id="def-item-14">MT<span class="def-item-dt-sep"></span></dt><dd>mechanical thrombectomy<span class="def-item-dd-sep"></span></dd><dt id="def-item-15">PLT<span class="def-item-dt-sep"></span></dt><dd>platelet<span class="def-item-dd-sep"></span></dd><dt id="def-item-16">ROC<span class="def-item-dt-sep"></span></dt><dd>receiver operating characteristic<span class="def-item-dd-sep"></span></dd><dt id="def-item-17">TG<span class="def-item-dt-sep"></span></dt><dd>total cholesterol triglyceride<span class="def-item-dd-sep"></span></dd><dt id="def-item-18">VNC<span class="def-item-dt-sep"></span></dt><dd>virtual noncontrast</dd></dl></div><div class="section fn-group" id="fn-group-1"><h2>Footnotes</h2><ul><li class="fn-equal" id="fn-4"><p id="p-58">D. Zhai and Y. Wu contributed equally to this work.</p></li><li class="fn-supported-by" id="fn-5"><p id="p-59">This study was supported by the Project of State Key Laboratory of Radiation Medicine and Protection, Soochow University (GZK12024025, 12024013, 1202136), Suzhou Clinical Key Disease Diagnosis and Treatment Technology Special Project (LCZX202309), “National Tutor System” Training Program for Health Youth Key Talents in Suzhou (Qngg2021006), Gusu Talent Program (GSWS2021025), Suzhou Municipal Science and Technology Development Project (SKY2022049, SKY2022011), “Technological Innovation” Project of CNNC Medical Industry Co. Ltd (ZHYLYB2021006, ZHYLYB2021001), “Image Medical Star” Project of Suzhou Medical Association (2022YX-M05), Project of Nuclear Technology Medical Application Supported by Discipline Construction of Second Affiliated Hospital of Soochow University (XKTJ-HRC20210010) and The Second Affiliated Hospital of Soochow University Pre-Research Fund Project (SDFEYLC2342).</p></li><li class="fn-financial-disclosure" id="fn-6"><p id="p-60"><a href="https://www.ajnr.org/sites/default/files/additional-assets/Disclosures/January%202025/0349.pdf">Disclosure forms</a> provided by the authors are available with the full text and PDF of this article at <a href="http://www.ajnr.org">www.ajnr.org</a>.</p></li></ul></div><ul class="copyright-statement"><li class="fn" id="copyright-statement-1">© 2024 by American Journal of Neuroradiology</li></ul><span class="highwire-journal-article-marker-end"></span></div><span class="related-urls"></span></div><a href="http://ajnr-stage2.stage.highwire.org/content/early/2024/12/05/ajnr.A8434.full" class="hw-link hw-link-article-full-text" data-icon-position="" data-hide-link-title="0">View Full Text</a></div>  </div>

  
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      <div class="highwire-cite-title">Combinations of Clinical Factors, CT Signs, and Radiomics for Differentiating High-Density Areas after Mechanical Thrombectomy in Patients with Acute Ischemic Stroke</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">Duchang</span> <span class="nlm-surname">Zhai</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">Yuanyuan</span> <span class="nlm-surname">Wu</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">Manman</span> <span class="nlm-surname">Cui</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">Yan</span> <span class="nlm-surname">Liu</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">Xiuzhi</span> <span class="nlm-surname">Zhou</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">Dongliang</span> <span class="nlm-surname">Hu</span></span>, <span class="highwire-citation-author" data-delta="6"><span class="nlm-given-names">Yuancheng</span> <span class="nlm-surname">Wang</span></span>, <span class="highwire-citation-author" data-delta="7"><span class="nlm-given-names">Shenghong</span> <span class="nlm-surname">Ju</span></span>, <span class="highwire-citation-author" data-delta="8"><span class="nlm-given-names">Guohua</span> <span class="nlm-surname">Fan</span></span>, <span class="highwire-citation-author" data-delta="9"><span class="nlm-given-names">Wu</span> <span class="nlm-surname">Cai</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">Dec 2024, </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A8434 </span></div>
  
  
  
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      <div class="highwire-cite-title">Combinations of Clinical Factors, CT Signs, and Radiomics for Differentiating High-Density Areas after Mechanical Thrombectomy in Patients with Acute Ischemic Stroke</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">Duchang</span> <span class="nlm-surname">Zhai</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">Yuanyuan</span> <span class="nlm-surname">Wu</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">Manman</span> <span class="nlm-surname">Cui</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">Yan</span> <span class="nlm-surname">Liu</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">Xiuzhi</span> <span class="nlm-surname">Zhou</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">Dongliang</span> <span class="nlm-surname">Hu</span></span>, <span class="highwire-citation-author" data-delta="6"><span class="nlm-given-names">Yuancheng</span> <span class="nlm-surname">Wang</span></span>, <span class="highwire-citation-author" data-delta="7"><span class="nlm-given-names">Shenghong</span> <span class="nlm-surname">Ju</span></span>, <span class="highwire-citation-author" data-delta="8"><span class="nlm-given-names">Guohua</span> <span class="nlm-surname">Fan</span></span>, <span class="highwire-citation-author" data-delta="9"><span class="nlm-given-names">Wu</span> <span class="nlm-surname">Cai</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">Dec 2024, </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A8434 </span></div>
  
  
  
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