AI analysis of cardiac MRI is better linked to patient survival than clinician measurements, suggesting a key role for AI in heart function assessment.
Key Details
- 1Study analyzed cardiac MRI scans from 27,382 patients across the UK and US.
- 2AI-derived ejection fraction measurements predicted mortality risk slightly but significantly better than clinician-derived measurements, even after adjusting for age and sex.
- 3AI analyzed scans in 2-3 seconds per patient, compared to 13 minutes for expert clinicians.
- 4Error rate for AI measurements was low: ~1% at patient level, affecting 0.08% of images.
- 5Research led by City St George’s, University of London and UCL, published in The Lancet Digital Health.
- 6Findings support AI as a first-line tool for cardiac MRI analysis, with human oversight remaining important.
Why It Matters
This large-scale, multi-center study demonstrates that AI can provide fast, consistent, and more prognostically relevant cardiac MRI measurements, potentially streamlining workflows and improving patient triage. Adoption of such tools could reduce workload pressure and help guide timely, lifesaving treatments, while maintaining clinical oversight for rare errors.
Source
EurekAlert
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