{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T00:29:31Z","timestamp":1793233771519,"version":"4.5.0"},"reference-count":25,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"12","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Stroke"],"published-print":{"date-parts":[[2019,12]]},"abstract":"<jats:sec>\n            <jats:title>Background and Purpose\u2014<\/jats:title>\n            <jats:p>Accurate and rapid detection of anterior circulation large vessel occlusion (LVO) is of paramount importance in patients with acute stroke due to the potentially rapid infarction of at-risk tissue and the limited therapeutic window for endovascular clot retrieval. Hence, the optimal threshold of a new, fully automated software-based approach for LVO detection was determined, and its diagnostic performance evaluated in a large cohort study.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Methods\u2014<\/jats:title>\n            <jats:p>For this retrospective study, data were pooled from: 2 stroke trials, DEFUSE 2 (n=62; 07\/08\u201309\/11) and DEFUSE 3 (n=213; 05\/17\u201305\/18); a cohort of endovascular clot retrieval candidates (n=82; August 2, 2014\u2013August 30, 2015) and normals (n=111; June 6, 2017\u2013January 28, 2019) from a single quaternary center; and code stroke patients (n=501; January 1, 2017\u2013December 31, 2018) from a single regional hospital. All CTAs were assessed by the automated algorithm. Consensus reads by 2 neuroradiologists served as the reference standard. ROC analysis was used to assess diagnostic performance of the algorithm for detection of (1) anterior circulation LVOs involving the intracranial internal carotid artery or M1 segment middle cerebral artery (M1-MCA); (2) anterior circulation LVOs and proximal M2 segment MCA (M2-MCA) occlusions; and (3) individual segment occlusions.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results\u2014<\/jats:title>\n            <jats:p>CTAs from 926 patients (median age 70 years, interquartile range: 58-80; 422 females) were analyzed. Three hundred ninety-five patients had an anterior circulation LVO or M2-MCA occlusion (National Institutes of Health Stroke Scale 14 [median], interquartile range: 9\u201319). Sensitivity and specificity were 97% and 74%, respectively, for LVO detection, and 95% and 79%, respectively, when M2 occlusions were included. On analysis by occlusion site, sensitivities were 90% (M2-MCA), 97% (M1-MCA), and 97% (intracranial internal carotid artery) with corresponding area-under-the-ROC-curves of 0.874 (M2), 0.962 (M1), and 0.997 (intracranial internal carotid artery).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions\u2014<\/jats:title>\n            <jats:p>Intracranial anterior circulation LVOs and proximal M2 occlusions can be rapidly and reliably detected by an automated detection tool, which may facilitate intra- and inter-instutional workflows and emergent imaging triage in the care of patients with stroke.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/strokeaha.119.027076","type":"journal-article","created":{"date-parts":[[2019,11,4]],"date-time":"2019-11-04T10:00:34Z","timestamp":1572861634000},"page":"3431-3438","update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":76,"title":["Fast Automatic Detection of Large Vessel Occlusions on CT Angiography"],"prefix":"10.1161","volume":"50","author":[{"given":"Shalini A.","family":"Amukotuwa","sequence":"first","affiliation":[{"name":"From the Diagnostic Imaging, Monash Medical Centre, Clayton, VIC, Australia (S.A.A.)"},{"name":"Department of Radiology, University Hospital Geelong, VIC, Australia (S.A.A.)"},{"name":"Department of Radiology and Medicine, Royal Melbourne Hospital, Parkville, VIC, Australia (S.A.A., R.B.)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matus","family":"Straka","sequence":"additional","affiliation":[{"name":"Department of Neurology, Stanford Stroke Center, Stanford University, CA (M.S.)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seena","family":"Dehkharghani","sequence":"additional","affiliation":[{"name":"Department of Radiology, NYU Langone Medical Center, NY (S.D.)"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roland","family":"Bammer","sequence":"additional","affiliation":[{"name":"Department of Radiology and Medicine, Royal Melbourne Hospital, Parkville, VIC, Australia (S.A.A., R.B.)"},{"name":"Florey Institute of Neurosciences, Parkville, VIC Australia (R.B.)"},{"name":"Department of Radiology, 3DQ Lab, Stanford University, CA (R.B)."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2017.00651"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1415061"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1414792"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1414905"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1411587"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1706442"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1713973"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1161\/STR.0000000000000158"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neurad.2018.03.003"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1017\/s0317167100004480"},{"key":"e_1_3_3_12_2","unstructured":"CMS. 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Automated large artery occlusion detection in stroke imaging - ALADIN study. Stroke. 2018;49(suppl 1):wp61. Abstract.","journal-title":"Stroke"},{"key":"e_1_3_3_25_2","first-page":"A101","article-title":"E-108 ALADIN study: Automated large artery occlusion detection in stroke imaging study \u2013 a multicenter analysis.","volume":"10","author":"Barreira CM","year":"2018","unstructured":"Barreira, CM, Bouslama, M, Lim, J, Al-Bayati, A, Saleem, Y, Devlin, T, et al. E-108 ALADIN study: Automated large artery occlusion detection in stroke imaging study \u2013 a multicenter analysis. J Neurointerv Surg. 2018;10:A101\u2013A102","journal-title":"J Neurointerv Surg"},{"key":"e_1_3_3_26_2","first-page":"As10-047","article-title":"ALADIN study: automated large artery occlusion detection in stroke imaging study - a multi-center experience.","volume":"3","author":"Barreira CM","year":"2018","unstructured":"Barreira, CM, Bouslama, M, Lim, J, Al-Bayati, A, Haussen, DC, Grossberg, JA, et al. 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