Background and purpose The Alberta Stroke Program Early CT Score (ASPECTS) is a widely used measure of ischemic change on non-contrast CT. Although predictive of long-term outcome, ASPECTS is limited by its modest interobserver agreement. One potential solution to this is the use of machine learning strategies, such as e-ASPECTS, to detect ischemia. Here, we compared e-ASPECTS with manual scoring by experienced neuroradiologists for all 10 individual ASPECTS regions.
Materials and methods We retrospectively reviewed 178 baseline non-contrast CT scans from patients with acute ischemic stroke undergoing endovascular thrombectomy. All scans were reviewed by two independent neuroradiologists with a third reader arbitrating disagreements for a consensus read. Each ASPECTS region was scored individually. All scans were then evaluated using a machine learning-based software package (e-ASPECTS, Brainomix). Interobserver agreement between readers and the software for each region was calculated with a kappa statistic.
Results The median ASPECTS was 9 for manual scoring and 8.5 for e-ASPECTS, with an overall agreement of κ=0.248. Regional agreement varied from κ=0.094 (M1) to κ=0.555 (lentiform), with better performance in subcortical regions. When corrected for the low number of infarcts in any given region, prevalence-adjusted bias-adjusted kappa ranged from 0.483 (insula) to 0.888 (M3), with greater agreement for cortical areas. Intraclass correlation coefficients were between 0.09 (M1) and 0.556 (lentiform).
Conclusion Manual scoring and e-ASPECTS had fair agreement in our dataset on a per-region basis. This warrants further investigation using follow-up scans or MRI as the gold standard measure of true ASPECTS.
Data availability statement
Data are available upon reasonable request.
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Correction notice Since this paper was first published, the middle initial C has been added to the author name John Benson.
Contributors AN and SMS analysed the data and drafted the manuscript. DM, JB, IM, DFK, and WB collected the data. DFK and WB supervised the project. All authors contributed to revising the manuscript, approved the final version, and agree to be accountable for all aspects of the work.
Funding AN was supported by an award from the Oxford University Clinical Academic Graduate School. This work was done during the term of an Award from the American Heart Association (19POST34381067) to SMS.
Competing interests The manuscript was reviewed by Brainomix, the developers of e-ASPECTS, but the authors retained full control over analysis, presentation, and discussion of results.
Provenance and peer review Not commissioned; externally peer reviewed.
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