{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T16:16:54Z","timestamp":1784737014652,"version":"3.55.0"},"reference-count":34,"publisher":"Elsevier BV","issue":"4","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/501100002865","name":"Chongqing Municipal Science and Technology Bureau","doi-asserted-by":"publisher","award":["CSTB2022TFII-OFX0042"],"award-info":[{"award-number":["CSTB2022TFII-OFX0042"]}],"id":[{"id":"10.13039\/501100002865","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["academicradiology.org","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Academic Radiology"],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1016\/j.acra.2024.09.052","type":"journal-article","created":{"date-parts":[[2024,10,28]],"date-time":"2024-10-28T13:00:41Z","timestamp":1730120441000},"page":"2141-2149","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":7,"title":["Deep Learning Using One-stop-shop CT Scan to Predict Hemorrhagic Transformation in Stroke Patients Undergoing Reperfusion Therapy: A Multicenter Study"],"prefix":"10.1016","volume":"32","author":[{"given":"Huanhuan","family":"Ren","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haojie","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaoguo","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meilin","family":"Gong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongmei","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.acra.2024.09.052_bib1","doi-asserted-by":"crossref","first-page":"e364","DOI":"10.1161\/STR.0000000000000375","article-title":"2021 Guideline for the Prevention of Stroke in Patients With Stroke and Transient Ischemic Attack: a guideline From the American Heart Association\/American Stroke Association","volume":"52","author":"Kleindorfer","year":"2021","journal-title":"Stroke"},{"key":"10.1016\/j.acra.2024.09.052_bib2","doi-asserted-by":"crossref","first-page":"S52","DOI":"10.1212\/WNL.0b013e3182697e70","article-title":"Blood-brain barrier, reperfusion injury, and hemorrhagic transformation in acute ischemic stroke","volume":"79","author":"Khatri","year":"2012","journal-title":"Neurology"},{"key":"10.1016\/j.acra.2024.09.052_bib3","doi-asserted-by":"crossref","DOI":"10.3389\/fneur.2021.797394","article-title":"High level of the fibrin degradation products at admission predicts parenchymal hematoma and unfavorable outcome of ischemic stroke after intravenous thrombolysis","volume":"12","author":"Liu","year":"2022","journal-title":"Front Neurol"},{"key":"10.1016\/j.acra.2024.09.052_bib4","doi-asserted-by":"crossref","first-page":"2498","DOI":"10.18632\/aging.102757","article-title":"The association between monocyte to high-density lipoprotein ratio and hemorrhagic transformation in patients with acute ischemic stroke","volume":"12","author":"Wang","year":"2020","journal-title":"Aging (Albany NY)"},{"key":"10.1016\/j.acra.2024.09.052_bib5","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1136\/svn-2018-000141","article-title":"Risk factors of haemorrhagic transformation for acute ischaemic stroke in Chinese patients receiving intravenous recombinant tissue plasminogen activator: a systematic review and meta-analysis","volume":"3","author":"Guo","year":"2018","journal-title":"Stroke Vasc Neurol"},{"key":"10.1016\/j.acra.2024.09.052_bib6","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1007\/s00415-022-11500-5","article-title":"Proximal hyperdense middle cerebral artery sign is associated with increased risk of asymptomatic hemorrhagic transformation after endovascular thrombectomy: a multicenter retrospective study","volume":"270","author":"Kang","year":"2023","journal-title":"J Neurol"},{"key":"10.1016\/j.acra.2024.09.052_bib7","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1136\/neurintsurg-2018-014141","article-title":"Hemorrhagic transformation is associated with poor functional outcome in patients with acute ischemic stroke due to a large vessel occlusion","volume":"11","author":"van Kranendonk","year":"2019","journal-title":"J Neurointerv Surg"},{"key":"10.1016\/j.acra.2024.09.052_bib8","doi-asserted-by":"crossref","first-page":"897","DOI":"10.3389\/fneur.2019.00897","article-title":"MRI-based predictors of hemorrhagic transformation in patients with stroke treated by intravenous thrombolysis","volume":"10","author":"El Nawar","year":"2019","journal-title":"Front Neurol"},{"key":"10.1016\/j.acra.2024.09.052_bib9","doi-asserted-by":"crossref","first-page":"1595","DOI":"10.1161\/STROKEAHA.113.000794","article-title":"External validation of the SEDAN score for prediction of intracerebral hemorrhage in stroke thrombolysis","volume":"44","author":"Mazya","year":"2013","journal-title":"Stroke"},{"key":"10.1016\/j.acra.2024.09.052_bib10","article-title":"Machine learning-based model for prediction of hemorrhage transformation in acute ischemic stroke after alteplase","volume":"13","author":"Xu","year":"2022","journal-title":"Front Neurol"},{"key":"10.1016\/j.acra.2024.09.052_bib11","doi-asserted-by":"crossref","first-page":"3039","DOI":"10.1161\/STROKEAHA.113.002396","article-title":"Prediction of poststroke hemorrhagic transformation using computed tomography perfusion","volume":"44","author":"Yassi","year":"2013","journal-title":"Stroke"},{"key":"10.1016\/j.acra.2024.09.052_bib12","doi-asserted-by":"crossref","first-page":"156","DOI":"10.3390\/brainsci13010156","article-title":"Predictive value of CT perfusion in hemorrhagic transformation after acute ischemic stroke: a systematic review and meta-analysis","volume":"13","author":"Xu","year":"2023","journal-title":"Brain Sci"},{"key":"10.1016\/j.acra.2024.09.052_bib13","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.1111\/ene.13117","article-title":"Cerebral collateral circulation and acute ischaemic stroke","volume":"23","author":"Gill","year":"2016","journal-title":"Eur J Neurol"},{"key":"10.1016\/j.acra.2024.09.052_bib14","doi-asserted-by":"crossref","first-page":"882","DOI":"10.3390\/brainsci10110882","article-title":"ColorViz, a new and rapid tool for assessing collateral circulation during stroke","volume":"10","author":"Verdolotti","year":"2020","journal-title":"Brain Sci"},{"key":"10.1016\/j.acra.2024.09.052_bib15","doi-asserted-by":"crossref","first-page":"60","DOI":"10.3389\/fneur.2020.00060","article-title":"Collateral vessels on 4D CTA as a predictor of hemorrhage transformation after endovascular treatments in patients with acute ischemic stroke: a single-center study","volume":"11","author":"Cao","year":"2020","journal-title":"Front Neurol"},{"key":"10.1016\/j.acra.2024.09.052_bib16","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1148\/radiol.2503080257","article-title":"Hemorrhagic transformation of ischemic stroke: prediction with CT perfusion","volume":"250","author":"Aviv","year":"2009","journal-title":"Radiology"},{"key":"10.1016\/j.acra.2024.09.052_bib17","doi-asserted-by":"crossref","first-page":"630","DOI":"10.1038\/jcbfm.2014.238","article-title":"Postischemic hyperperfusion on arterial spin labeled perfusion MRI is linked to hemorrhagic transformation in stroke","volume":"35","author":"Yu","year":"2015","journal-title":"J Cereb Blood Flow Metab"},{"key":"10.1016\/j.acra.2024.09.052_bib18","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2020.101693","article-title":"Embracing imperfect datasets: a review of deep learning solutions for medical image segmentation","volume":"63","author":"Tajbakhsh","year":"2020","journal-title":"Med Image Anal"},{"key":"10.1016\/j.acra.2024.09.052_bib19","doi-asserted-by":"crossref","first-page":"20TR01","DOI":"10.1088\/1361-6560\/ab843e","article-title":"Deep learning in medical image registration: a review","volume":"65","author":"Fu","year":"2020","journal-title":"Phys Med Biol"},{"key":"10.1016\/j.acra.2024.09.052_bib20","doi-asserted-by":"crossref","first-page":"713","DOI":"10.21037\/atm.2020.02.44","article-title":"A review of the application of deep learning in medical image classification and segmentation","volume":"8","author":"Cai","year":"2020","journal-title":"Ann Transl Med"},{"key":"10.1016\/j.acra.2024.09.052_bib21","doi-asserted-by":"crossref","DOI":"10.1007\/s00330-024-10618-6","article-title":"Radiomics using non-contrast CT to predict hemorrhagic transformation risk in stroke patients undergoing revascularization","author":"Heo","year":"2024","journal-title":"Eur Radiol"},{"key":"10.1016\/j.acra.2024.09.052_bib22","doi-asserted-by":"crossref","first-page":"1823","DOI":"10.1001\/jama.292.15.1823","article-title":"Comparison of MRI and CT for detection of acute intracerebral hemorrhage","volume":"292","author":"Kidwell","year":"2004","journal-title":"JAMA"},{"key":"10.1016\/j.acra.2024.09.052_bib23","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1001\/jama.1995.03530130023023","article-title":"Intravenous thrombolysis with recombinant tissue plasminogen activator for acute hemispheric stroke. The European Cooperative Acute Stroke Study (ECASS)","volume":"274","author":"Hacke","year":"1995","journal-title":"JAMA"},{"key":"10.1016\/j.acra.2024.09.052_bib24","doi-asserted-by":"crossref","first-page":"4077","DOI":"10.1007\/s00330-018-5936-7","article-title":"Perfusion CT for prediction of hemorrhagic transformation in acute ischemic stroke: a systematic review and meta-analysis","volume":"29","author":"Suh","year":"2019","journal-title":"Eur Radiol"},{"key":"10.1016\/j.acra.2024.09.052_bib25","doi-asserted-by":"crossref","first-page":"221","DOI":"10.3174\/ajnr.A6889","article-title":"Multiphase CT angiography: a useful technique in acute stroke imaging-collaterals and beyond","volume":"42","author":"Dundamadappa","year":"2021","journal-title":"AJNR Am J Neuroradiol"},{"key":"10.1016\/j.acra.2024.09.052_bib26","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1177\/1971400919900275","article-title":"Radiological predictors of hemorrhagic transformation after acute ischemic stroke: an evidence-based analysis","volume":"33","author":"Elsaid","year":"2020","journal-title":"Neuroradiol J"},{"key":"10.1016\/j.acra.2024.09.052_bib27","doi-asserted-by":"crossref","first-page":"1562","DOI":"10.3390\/diagnostics12071562","article-title":"Merging multiphase CTA images and training them simultaneously with a deep learning algorithm could improve the efficacy of AI models for lateral circulation assessment in ischemic stroke","volume":"12","author":"Wang","year":"2022","journal-title":"Diagnostics (Basel)"},{"key":"10.1016\/j.acra.2024.09.052_bib28","doi-asserted-by":"crossref","first-page":"1024","DOI":"10.1016\/j.acra.2023.06.034","article-title":"The predictive value of cerebral veins on hemorrhagic transformation after endovascular treatment in acute ischemic stroke patients: enhanced insights from venous collateral circulation analysis using four-dimensional CTA","volume":"31","author":"Cao","year":"2024","journal-title":"Acad Radiol"},{"key":"10.1016\/j.acra.2024.09.052_bib29","doi-asserted-by":"crossref","DOI":"10.1111\/bpa.13023","article-title":"A deep learning-based model for prediction of hemorrhagic transformation after stroke","volume":"33","author":"Jiang","year":"2023","journal-title":"Brain Pathol"},{"key":"10.1016\/j.acra.2024.09.052_bib30","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1002\/ana.24953","article-title":"Computed tomographic perfusion to predict response to recanalization in ischemic stroke","volume":"81","author":"Lansberg","year":"2017","journal-title":"Ann Neurol"},{"key":"10.1016\/j.acra.2024.09.052_bib31","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.1007\/s13760-023-02239-5","article-title":"Proposal of multimodal computed tomography-based scoring system in prediction of hemorrhagic transformation in acute ischemic stroke","volume":"123","author":"Elsaid","year":"2023","journal-title":"Acta Neurol Belg"},{"key":"10.1016\/j.acra.2024.09.052_bib32","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1007\/s00330-023-10007-5","article-title":"Quantitative assessment of hyperperfusion using arterial spin labeling to predict hemorrhagic transformation in acute ischemic stroke patients with mechanical endovascular therapy","volume":"34","author":"Huang","year":"2024","journal-title":"Eur Radiol"},{"key":"10.1016\/j.acra.2024.09.052_bib33","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1186\/s13244-023-01399-5","article-title":"A clinical-radiomics model based on noncontrast computed tomography to predict hemorrhagic transformation after stroke by machine learning: a multicenter study","volume":"14","author":"Ren","year":"2023","journal-title":"Insights Imaging"},{"key":"10.1016\/j.acra.2024.09.052_bib34","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1161\/01.STR.32.2.438","article-title":"Risk factors for severe hemorrhagic transformation in ischemic stroke patients treated with recombinant tissue plasminogen activator: a secondary analysis of the European-Australasian Acute Stroke Study (ECASS II)","volume":"32","author":"Larrue","year":"2001","journal-title":"Stroke"}],"container-title":["Academic Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633224007025?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633224007025?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T17:28:24Z","timestamp":1762363704000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1076633224007025"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4]]},"references-count":34,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["S1076633224007025"],"URL":"https:\/\/doi.org\/10.1016\/j.acra.2024.09.052","relation":{},"ISSN":["1076-6332"],"issn-type":[{"value":"1076-6332","type":"print"}],"subject":[],"published":{"date-parts":[[2025,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deep Learning Using One-stop-shop CT Scan to Predict Hemorrhagic Transformation in Stroke Patients Undergoing Reperfusion Therapy: A Multicenter Study","name":"articletitle","label":"Article Title"},{"value":"Academic Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.acra.2024.09.052","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Association of Academic Radiology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}