AI quantification of breast arterial calcifications (BACs) on mammograms enhances prediction of cardiovascular events beyond traditional risk models.
Key Details
- 1AI model (cmAngio, CureMetrix) used on 21,514 women aged 40+ from U.S. and Australia mammography data.
- 222.7% of women had BAC; prevalence rose to 61% for those over 70.
- 3Each 10-percentile BAC increase correlated to a 17% higher adjusted risk for major adverse cardiovascular events (MACE).
- 4Integration of BAC percentiles improved net risk reclassification by 5% and C-statistic from 0.67 to 0.71 (p = 0.04).
- 5Low and intermediate ASCVD risk women showed significantly increased MACE rates when BAC was above or below the median.
- 6Authors developed an online tool to aid clinical decision-making based on BAC percentiles.
Why It Matters
This study supports the use of mammogram-derived BAC scoring, automated by AI, to better stratify cardiovascular risk in women—potentially enabling earlier, more effective preventive care using routinely available imaging.
Source
AuntMinnie
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