AI-derived measurement of heart fat from CT scans significantly improves long-term cardiovascular disease risk prediction.
Key Details
- 1Mayo Clinic researchers augmented routine coronary artery calcium CT scans with AI to measure pericardial (heart) fat.
- 2Study included nearly 12,000 adults, followed for around 16 years.
- 3Approximately 10% of participants developed cardiovascular disease during the study period.
- 4Higher heart fat volume predicted elevated risk of cardiovascular events independently of traditional risk factors and coronary calcium scores.
- 5Adding this AI-derived metric to existing models improved predictive accuracy, especially for patients at borderline or intermediate risk.
- 6Method leverages information from scans already widely performed, without extra testing or cost.
Why It Matters

Source
EurekAlert
Related News

NIH-Backed AI Model Predicts Cancer Survival Using Single-Cell Data
Researchers have developed scSurvival, a machine learning tool that uses single-cell tumor data to accurately predict cancer patient survival and identify high-risk cell populations.

AI Pathology Model Outperforms PD-L1 in Predicting NSCLC Immunotherapy Response
MD Anderson's Path-IO machine learning platform accurately predicts immunotherapy responses in metastatic non-small cell lung cancer, surpassing current biomarker standards.

Deep Learning Pathomics Platform Improves Immunotherapy Prediction in Lung Cancer
A deep learning pathomics platform accurately predicts immunotherapy response in metastatic NSCLC using routine pathology slides.