Artificial intelligence-based quantification of breast arterial calcifications to predict cardiovascular morbidity and mortality - PubMed
3 days ago
- #Cardiovascular Disease
- #Mammography
- #Artificial Intelligence
- Women are underdiagnosed and undertreated for cardiovascular disease (CVD).
- Automatic quantification of breast arterial calcification (BAC) on screening mammography can identify women at risk for CVD.
- The study included 123,762 women from two healthcare systems who had screening mammograms.
- BAC severity was categorized as zero, mild, moderate, and severe.
- BAC was detected in 16.1% (internal cohort) and 20.6% (external cohort) of women.
- BAC provided significant prognostic value incremental to the PREVENT score.
- A clear dose-response was observed between BAC severity and major adverse cardiovascular events (MACE).
- Each 1 mm² increase in BAC conferred an additional 2%-3% risk for MACE.
- Automatically quantified BAC is an independent predictor of MACE and mortality.
- This approach may provide opportunistic cardiovascular risk assessment during routine mammography screening.