Background The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is an established 10-point quantitative topographic computed tomography scan score to assess early ischemic changes. We performed a non-inferiority trial between the e-ASPECTS software and neuroradiologists in scoring ASPECTS on non-contrast enhanced computed tomography images of acute ischemic stroke patients. Methods In this multicenter study, e-ASPECTS and three independent neuroradiologists retrospectively and blindly assessed baseline non-contrast enhanced computed tomography images of 132 patients with acute anterior circulation ischemic stroke. Follow-up scans served as ground truth to determine the definite area of infarction. Sensitivity, specificity, and accuracy for region- and score-based analysis, receiver-operating characteristic curves, Bland-Altman plots and Matthews correlation coefficients relative to the ground truth were calculated and comparisons were made between neuroradiologists and different pre-specified e-ASPECTS operating points. The non-inferiority margin was set to 10% for both sensitivity and specificity on region-based analysis. Results In total 2640 (132 patients × 20 regions per patient) ASPECTS regions were scored. Mean time from onset to baseline computed tomography was 146 ± 124 min and median NIH Stroke Scale (NIHSS) was 11 (6-17, interquartile range). Median ASPECTS for ground truth on follow-up imaging was 8 (6.5-9, interquartile range). In the region-based analysis, two e-ASPECTS operating points (sensitivity, specificity, and accuracy of 44%, 93%, 87% and 44%, 91%, 85%) were statistically non-inferior to all three neuroradiologists (all p-values <0.003). Both Matthews correlation coefficients for e-ASPECTS were higher (0.36 and 0.34) than those of all neuroradiologists (0.32, 0.31, and 0.3). Conclusions e-ASPECTS was non-inferior to three neuroradiologists in scoring ASPECTS on non-contrast enhanced computed tomography images of acute stroke patients.
Keywords: Alberta Stroke Program Early Computed Tomography Score; computed tomography; ischemic stroke; machine learning.