Artificial Intelligence-Parallel Stroke Workflow Tool Improves Reperfusion Rates and Door-In to Puncture Interval

The Viz.ai artificial intelligence (AI) software module Viz large-vessel occlusion (LVO) utilizes AI-powered LVO detection and triage technology to automatically identify suspected LVOs through computed tomographic angiogram imaging and alert on-call stroke teams. We performed this analysis to determine whether the Viz LVO software can reduce the door-in to puncture time interval within a comprehensive stroke center (CSC) for patients requiring endovascular treatment.

We conducted a retrospective chart review that compared the time interval between patient arrival in the emergency department (door-in) to puncture for patients who presented consecutively with a stroke code to our CSC between November 2016 and May 2020. The implementation of the AI software (Viz LVO) at the CSC was in November 2018. Using a prospectively collected database at the CSC, demographics, and outcomes were examined. This study was based on evaluating real-world practice.

We analyzed 86 patients from the pre-AI study phase (average age, 68.53±13.13 years, 40.7% female) and 102 patients from the post-AI study phase (average age, 69.87±15.75 years, 43.1% women). Following the implementation of the software, the mean door-in to puncture time interval within the CSC significantly improved by 86.7 minutes (206.6 versus 119.9 minutes; P<0.001); significant improvements were also noted in the rate of reperfusion (modified Thrombolysis in Cerebral Infraction 2B-3) for patients in the post-AI population (P=0.036).

The incorporation of the software was associated with a significant improvement in treatment time within the CSC, as well as significantly higher rates of adequate reperfusion. Prospective, multicenter, controlled studies with a larger cohort are warranted to expand on the ability of Viz LVO to improve treatment times and outcomes for patients with an LVO stroke.