BALA, Fouzi, Wu QIU, Kairan ZHU, Manon KAPPELHOF, Petra CIMFLOVÁ, Beom Joon KIM, Rosalie MCDONOUGH, Nishita SINGH, Nima KASHANI, Jianhai ZHANG, Mohamed NAJM, Johanna M OSPEL, Ankur WADHWA, Raul G NOGUEIRA, Ryan A MCTAGGART, Andrew M DEMCHUK, Alexandre Y POPPE, Charlotte ZERNA, Manish JOSHI, Mohammed A ALMEKHLAFI, Mayank GOYAL, Michael D HILL and Bijoy K MENON. Ability of Radiomics Versus Humans in Predicting First-Pass Effect After Endovascular Treatment in the ESCAPE-NA1 Trial. Stroke: Vascular and Interventional Neurology. Hoboken: Wiley, 2023, vol. 3, No 3, p. 1-10. ISSN 2694-5746. Available from: https://dx.doi.org/10.1161/SVIN.122.000525.
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Basic information
Original name Ability of Radiomics Versus Humans in Predicting First-Pass Effect After Endovascular Treatment in the ESCAPE-NA1 Trial
Authors BALA, Fouzi, Wu QIU, Kairan ZHU, Manon KAPPELHOF, Petra CIMFLOVÁ (203 Czech Republic, belonging to the institution), Beom Joon KIM, Rosalie MCDONOUGH, Nishita SINGH, Nima KASHANI, Jianhai ZHANG, Mohamed NAJM, Johanna M OSPEL, Ankur WADHWA, Raul G NOGUEIRA, Ryan A MCTAGGART, Andrew M DEMCHUK, Alexandre Y POPPE, Charlotte ZERNA, Manish JOSHI, Mohammed A ALMEKHLAFI, Mayank GOYAL, Michael D HILL and Bijoy K MENON.
Edition Stroke: Vascular and Interventional Neurology, Hoboken, Wiley, 2023, 2694-5746.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 30210 Clinical neurology
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
RIV identification code RIV/00216224:14110/23:00133719
Organization unit Faculty of Medicine
Doi http://dx.doi.org/10.1161/SVIN.122.000525
UT WoS 001162312700004
Keywords in English deep learning; endovascular therapy; ischemia; machine learning; stroke; thrombus
Tags 14110119, rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Tereza Miškechová, učo 341652. Changed: 4/3/2024 07:50.
Abstract
BACKGROUND: First-pass effect (FPE), that is, achieving reperfusion with a single thrombectomy device pass, is associated with better clinical outcomes in patients with acute stroke. FPE is therefore increasingly used as a marker of device and procedural efficacy. We aimed to evaluate the ability of thrombus-based radiomics models to predict FPE in patients undergoing endovascular thrombectomy and compare performance with experts and nonradiomics thrombus characteristics.
PrintDisplayed: 17/7/2024 01:39