{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T05:24:43Z","timestamp":1787117083602,"version":"build-2736575974"},"reference-count":42,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T00:00:00Z","timestamp":1787097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurol."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To develop and validate CT-based radiomics models incorporating intrathrombus and perithrombus features for predicting complete recanalization [modified Thrombolysis in Cerebral Infarction (mTICI)2c\/3] after endovascular thrombectomy (EVT) in acute ischemic stroke (AIS), and to identify the optimal machine learning classifier.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>\n                      This retrospective study included 406 AIS patients with anterior circulation large-vessel occlusion from three centers (December 2018\u2013April 2024). Patients were allocated to training (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f178), internal testing (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f77), and external validation (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f151) cohorts. Complete recanalization was defined as mTICI 2c\/3. A total of 428 radiomics features were extracted from non-contrast CT and CT angiography (CTA). Least absolute shrinkage and selection operator (LASSO) regression and eleven classifiers were employed.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The combined intrathrombus-perithrombus model with logistic regression achieved area under the curve (AUC) values of 0.93 (training), 0.88 (testing), and 0.86 (validation), outperforming single-region models. Decision curve analysis confirmed superior clinical utility. The perithrombus region contributed dominantly (10 of 15 features) to the combined model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The combined CT-based radiomics model effectively predicts complete recanalization, providing an objective tool for patient selection and treatment optimization.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fneur.2026.1868821","type":"journal-article","created":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T04:35:08Z","timestamp":1787114108000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["CT-based intrathrombus and perithrombus radiomics for predicting complete recanalization after endovascular thrombectomy in acute ischemic stroke"],"prefix":"10.3389","volume":"17","author":[{"given":"Qianqian","family":"Zhao","sequence":"first","affiliation":[{"name":"Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuaishuai","family":"Feng","sequence":"additional","affiliation":[{"name":"Department of Radiology, The Eighth People's Hospital of Jinan","place":["Jinan, Shandong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huihui","family":"Jia","sequence":"additional","affiliation":[{"name":"Department of Radiology, Huadong Hospital, Fudan University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minda","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiology, Affiliated Hospital of Nantong University","place":["Nantong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Tian","sequence":"additional","affiliation":[{"name":"Department of Radiology, Affiliated Hospital of Nantong University","place":["Nantong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haibin","family":"Pan","sequence":"additional","affiliation":[{"name":"Department of Radiology, Shanghai Fengxian Central Hospital","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingxuan","family":"Jiang","sequence":"additional","affiliation":[{"name":"Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,19]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1723","DOI":"10.1016\/s0140-6736(16)00163-x","article-title":"Endovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials","volume":"387","author":"Goyal","year":"2016","journal-title":"Lancet"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"108110","DOI":"10.1016\/j.jstrokecerebrovasdis.2024.108110","article-title":"Temporal trends in endovascular therapy for acute stroke in the era of modern mechanical thrombectomy: the JR-NET4 study","volume":"34","author":"Hayakawa","year":"2025","journal-title":"J Stroke Cerebrovasc Dis"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"483","DOI":"10.2174\/0115672026356656241118065115","article-title":"Thrombectomy failure and associated factors for 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