What happened
Mayo Clinic researchers developed an AI method to measure fat surrounding the heart from standard coronary artery calcium scans, significantly improving long-term cardiovascular disease risk prediction. The study, following nearly 12,000 adults for approximately 16 years, found higher heart fat volume independently associated with increased risk, even after accounting for traditional factors and coronary calcium scores. This AI-enhanced measurement improved overall prediction accuracy, particularly for patients in low-risk categories, without requiring additional testing or cost.
Why it matters
This advancement shifts how clinicians assess cardiovascular risk, providing a scalable mechanism to enhance existing diagnostic pathways. Procurement teams and healthcare providers gain a no-cost metric for improved patient stratification, enabling earlier, more effective interventions. For medical researchers, the ability to automatically quantify pericardial fat from routine scans offers a new data point for personalised prevention strategies, building on previous efforts to accelerate heart research with AI.
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