Deep Learning in Emergency Radiology: Evaluating a Tool for Automated ASPECT Scoring in Acute Ischemic Stroke

Background and Purpose The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) quantifies ischemic damage in middle cerebral artery territory strokes, guiding treatment decisions including thrombolysis and mechanical thrombectomy. However, inter‐rater variability in scoring limits its clinical reliability. Automated ASPECTS tools like CINA‐ASPECTS (v1.4.3, Avicenna.AI) have shown potential to enhance consistency and efficiency. This study validated CINA‐ASPECTS using a multinational, multi‐scanner external dataset against a ground truth (GT) established by expert neuroradiologists. Methods Head NCCT scans from 339 patients (20 ASPECTS regions each) were collected from clinical sites in the United States, France, and Japan. Five US board‐certified expert neuroradiologists participated in establishing the GT using NCCT and additional imaging when available, blinded to each other and the device output. CINA‐ASPECTS outputs were compared to this GT on a region‐based and score‐based level. Stratified analyses were conducted by scanner manufacturer, cortical versus deep regions, and individual ASPECTS regions. Results CINA‐ASPECTS demonstrated 72.8% sensitivity, 91.8% specificity, and an area under the receiver operating characteristic curve of 0.823 in region‐based analysis. Score‐based agreement showed an intraclass correlation coefficient (ICC) of 0.83 [95% CI: 0.79–0.86]. Dichotomized score‐based analysis showed good specificity, sensitivity, and ICC. Stratified analysis confirmed consistent performance across scanner manufacturers and cortical/deep ASPECTS regions. Performance was robust regardless of ASPECTS region, potentially aiding in the scoring of difficult regions. Conclusions CINA‐ASPECTS reliably identifies ischemic changes across diverse clinical and imaging conditions, achieving good agreement with expert consensus. These findings support its utility in clinical decision‐making for acute stroke management.