Number Needing Review: A Novel Metric to Assess Triage Efficiency of Large Vessel Occlusion Detection Systems.

Abstract

Background: Endovascular thrombectomy is the gold-standard treatment for large vessel occlusions (LVOs). A novel metric is introduced: the number needing review (NNR) to assess the triage efficiency of LVO detection systems.

Methods: Patients with suspected ischemic stroke and images processed by RapidAI LVO detection software over 6 months were reviewed. Only patients with LVOs of the M1 segment were included. The NNR was calculated for an M1 occlusion.

Results: Of 559 patients, M1 occlusion was detected in 42 patients (7.5%). RapidAI LVO had a sensitivity of 71%, specificity of 94%, positive predictive value of 49%, and negative predictive value of 92% for M1 occlusion. When gaze deviation and hyperdense sign were combined with RapidAI LVO, the specificity and positive predictive value increased to 100% for an M1 occlusion. A negative RapidAI LVO result combined with a low (<15 mL, T_max>6 seconds) or high (<50 mL, T_max>6 seconds) T_max threshold was found to have a specificity and positive predictive value of 100% for no occlusion. The combination of gaze deviation, hyperdense sign, positive RapidAI LVO, and negative RapidAI LVO with low T_max threshold yielded an NNR of 24 per 100 cases. When combined with a negative RapidAI LVO and a high T_max threshold, the NNR was 16 per 100 cases. Adding National Institutes of Health Stroke Scale score <7 decreased the NNR to 9 per 100 cases.

Conclusion: Adding gaze deviation and hyperdense sign to the RapidAI LVO increases the specificity and positive predictive value for an M1 occlusion. When combined with a negative RapidAI LVO detection and either a low or high T_max>6 seconds threshold, the NNR is significantly reduced.