External Validation of e‐ASPECTS Software for Interpreting Brain CT in Stroke

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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;92:943–957
Original languageEnglish
Pages (from-to)943-957
JournalAnnals of Neurology
Volume92
Issue number6
Early online date31 Aug 2022
DOIs
Publication statusPublished - Dec 2022

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