Background:
Identification of large vessel occlusion (LVO) is paramount in the urgent evaluation of acute ischemic stroke (AIS). Emergent interpretation of large and high-complexity data sets, however, may impose strains upon imaging and clinical workflows, motivating development of fast and accurate computer-aided approaches to facilitate LVO detection in the emergency setting. This study investigates the performance of a fully automated LVO detection platform in a mixed cohort of stroke subjects with and without LVO on head and neck CT angiography (CTA).
Methods:
CTA from two cerebrovascular trials were enriched with cases from eleven global sites. Imaging and clinical variables were balanced between populations including in LVO positivity and across demographic and imaging environments to the extent achievable. Independent and fully blinded review for intracranial ICA or MCA M1 LVO was performed by two subspecialty neuroradiologists. A novel, user-independent imaging analysis application (
RAPID-LVO
, iSchemaview inc) was used to predict LVO presence, location, and overall performance relative to reader consensus. Any discordance between readers was adjudicated by a blinded tertiary reader with subspecialty training. Sensitivity, specificity, and receiver-operating characteristics were determined by an independent statistician. Performance thresholds were set a priori, including a lower bound of the 95% CI of sensitivity and specificity of ≥0.8 at mean times-to-notification <3.5 minutes.
Results:
217 CTA (median age 65.5, 53% male, 109 LVO(+)) were included. Lower confidence limits of sensitivity and specificity exceeded 90% (sensitivity 0.963, 95% CI 0.909-0.986; specificity 0.981, 95% CI 0.935-0.995), surpassing pre-specified performance benchmarks. Subgroup analyses revealed no decrement in performance relative to subject age or sex, vendor systems, or location of the examination within or outside the United States. The area under the receiver operating characteristics curve was 0.99 (95% CI: 0.971-0.999) and average time-to-notification was 3.18 minutes.
Conclusion:
RAPID-LVO
offers fast, highly accurate, and fully user-independent large vessel occlusion detection across all tested clinical and imaging environments.
Early detection of large‐vessel occlusion stroke after cardiac surgery using CT angiography leading to early recanalization with endovascular thrombectomy