Company Spotlight: Qure.ai qER-CTA - AI Stroke Triage and the 6.36-Minute Notification Race

We unpack the FDA's 510(k) summary for Qure.ai's qER-CTA, an AI triage tool designed to detect large vessel occlusions on head CT scans. We explore its clinical performance data, how it compares to its predicate device Viz LVO, and the strict workflow limitations hospitals need to know before buying.

Key points

• qER-CTA uses deep learning to analyze CT angiograms for suspected large vessel occlusions in the ICA and M1 segment of the MCA.
• In a standalone study of 584 scans, the software demonstrated 91.35% sensitivity and 91.86% specificity, with a mean notification time of 6.36 minutes.
• The FDA cleared it based on substantial equivalence to Viz LVO, placing it in the highly competitive Radiological Computer Aided Triage and Notification Software category.
• The system generates a passive notification flag in the worklist rather than proactively alerting users or altering the worklist order itself.
• Images viewed on the mobile application are compressed and strictly for informational purposes; clinical decisions require reviewing non-compressed images on a diagnostic viewer.

Source: FDA 510(k) summary K251610: qER-CTA (v1.0) (Qure.ai Technologies) - U.S. Food and Drug Administration, 2025

This episode is an AI-generated conversation summarising a public document; the hosts' voices are synthetic. It is for information only and is not medical advice. Always refer to the original source.

Company: Qure.ai Technologies · Product: qER-CTA (v1.0) · FDA 510(k) K251610

Full transcript: https://ai-in-medicine-podcast.vercel.app/episodes/company-spotlight-qure-ai-qer-cta-ai-stroke-triage-and-the-6-36-minute-082141