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External Validation of e-ASPECTS Software for Interpreting Brain CT in Stroke.
Mair, Grant; White, Philip; Bath, Philip M; Muir, Keith W; Al-Shahi Salman, Rustam; Martin, Chloe; Dye, David; Chappell, Francesca M; Vacek, Adam; von Kummer, Rüdiger; Macleod, Malcolm; Sprigg, Nikola; Wardlaw, Joanna M.
Afiliación
  • Mair G; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
  • White P; Translational and Clinical Research Institute, Newcastle University and Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK.
  • Bath PM; Stroke Trials Unit, Mental Health & Clinical Neuroscience, University of Nottingham, Nottingham, UK.
  • Muir KW; School of Psychology & Neuroscience, University of Glasgow, Glasgow, UK.
  • Al-Shahi Salman R; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
  • Martin C; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
  • Dye D; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
  • Chappell FM; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
  • Vacek A; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
  • von Kummer R; Department of Neuroradiology, University Hospital, Technische Universität Dresden, Dresden, Germany.
  • Macleod M; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
  • Sprigg N; Translational and Clinical Research Institute, Newcastle University and Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK.
  • Wardlaw JM; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
Ann Neurol ; 92(6): 943-957, 2022 12.
Article en En | MEDLINE | ID: mdl-36053916
ABSTRACT

OBJECTIVE:

The purpose of this study was to test e-ASPECTS software in patients with stroke. Marketed as a decision-support tool, e-ASPECTS may detect features of ischemia or hemorrhage on computed tomography (CT) imaging and quantify ischemic extent using Alberta Stroke Program Early CT Score (ASPECTS).

METHODS:

Using CT from 9 stroke studies, we compared software with masked experts. As per indications for software use, we assessed e-ASPECTS results for patients with/without middle cerebral artery (MCA) ischemia but no other cause of stroke. In an analysis outside the intended use of the software, we enriched our dataset with non-MCA ischemia, hemorrhage, and mimics to simulate a representative "front door" hospital population. With final diagnosis as the reference standard, we tested the diagnostic accuracy of e-ASPECTS for identifying stroke features (ischemia, hyperattenuated arteries, and hemorrhage) in the representative population.

RESULTS:

We included 4,100 patients (51% women, median age = 78 years, National Institutes of Health Stroke Scale [NIHSS] = 10, onset to scan = 2.5 hours). Final diagnosis was ischemia (78%), hemorrhage (14%), or mimic (8%). From 3,035 CTs with expert-rated ASPECTS, most (2084/3035, 69%) e-ASPECTS results were within one point of experts. In the representative population, the diagnostic accuracy of e-ASPECTS was 71% (95% confidence interval [CI] = 70-72%) for detecting ischemic features, 85% (83-86%) for hemorrhage. Software identified more false positive ischemia (12% vs 2%) and hemorrhage (14% vs <1%) than experts.

INTERPRETATION:

On independent testing, e-ASPECTS provided moderate agreement with experts and overcalled stroke features. Therefore, future prospective trials testing impacts of artificial intelligence (AI) software on patient care and outcome are required before widespread implementation of stroke decision-support software. ANN NEUROL 2022;92943-957.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Isquemia Encefálica / Accidente Cerebrovascular Tipo de estudio: Observational_studies / Prognostic_studies Límite: Aged / Female / Humans / Male Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Isquemia Encefálica / Accidente Cerebrovascular Tipo de estudio: Observational_studies / Prognostic_studies Límite: Aged / Female / Humans / Male Idioma: En Año: 2022 Tipo del documento: Article