External validation of e-ASPECTS software for interpreting brain CT in stroke

Mair, Grant; White, Philip; Bath, Philip M.; Muir, Keith W.; Salman, Rustam Al-Shahi; Martin, Chloe; Dye, David; Chappell, Francesca M.; Vacek, Adam; Von Kummer, Rüdiger; Macleod, Malcolm; Sprigg, Nikola; Wardlaw, Joanna M.

Abstract

Objective
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 ASPECTS (Alberta Stroke Program Early CT Score).
Methods
Using CT from nine 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 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, hemorrhage) in the representative population.
Results
We included 4100 patients (51% female, median age 78 years, NIHSS 10, onset to scan 2·5 hours). Final diagnosis was ischemia (78%), hemorrhage (14%), or mimic (8%). From 3035 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, 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 AI software on patient care and outcome are required before widespread implementation of stroke decision-support software.

Citation

Mair, G., White, P., Bath, P. M., Muir, K. W., Salman, R. A.-S., Martin, C., …Wardlaw, J. M. (2022). External validation of e-ASPECTS software for interpreting brain CT in stroke. Annals of Neurology, 92(6), 943-957. https://doi.org/10.1002/ana.26495

• Journal Article Type: Article
• Acceptance Date: Aug 30, 2022
• Online Publication Date: Sep 23, 2022
• Publication Date: 2022-12
• Deposit Date: Sep 14, 2022
• Publicly Available Date: Sep 24, 2023
• Journal: Annals of Neurology
• Print ISSN: 0364-5134
• Electronic ISSN: 1531-8249
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 92
• Issue: 6
• Pages: 943-957
• DOI: https://doi.org/10.1002/ana.26495
• Public URL: https://nottingham-repository.worktribe.com/output/11196012
• Publisher URL: https://onlinelibrary.wiley.com/doi/10.1002/ana.26495