Real-World Performance of Ai-Powered Ich Triage System

Abstract

Intracranial hemorrhage (ICH) is a life-threatening condition with high mortality and disability rates. In March 2018, the FDA cleared Viz ICH [1], an AI tool that analyzes brain NCCT studies for the presence of an ICH. Upon detection of a suspected ICH, Viz.ai sends a notification to alert a multidisciplinary team to promote an efficient workflow, leading to quick diagnosis and treatment. The objective of this study is to characterize the performance of Viz ICH in real-world settings. The FDA clearance is based on data generated in controlled settings; however, an effective AI tool should prove its potency and efficacy with heterogeneous data, originating from sites with varying equipment, protocols, and personnel skills. 3139 patients from 127 hospitals were analyzed using Viz ICH. Results were used to evaluate the detection of ICH, measured by accuracy, sensitivity, specificity, PPV, NPV, and time to notification. On a real-life consecutive set of 3156 scans, Viz ICH showed a high accuracy rate of 98.57%, and sensitivity, specificity, PPV and NPV of 90.48%, 98.97%, 81.1% and 99.53%, respectively. Mean time to notification was 3.39 minutes for ICH suspected cases. Viz ICH demonstrates robust performance in heterogeneous, real-world settings. Furthermore, the swift time to notification can assist clinicians in speeding up diagnoses. Viz ICH can therefore be considered a reliable AI tool for medical centers of various sizes and capabilities for the goal of improving patient outcomes.