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
Related News
•Radiology Business
CARPL.ai Raises $10M to Expand Radiology AI Marketplace
CARPL.ai secured $10M in Series A funding to expand its global radiology AI marketplace.
•Radiology Business
AI-Powered Tool Streamlines CT Scan Prioritization in Emergency Departments
An AI-based CT queue system significantly reduces wait times for ED patients by prioritizing scans likely to reveal critical findings.
•Radiology Business
AI Workflow Enables General Radiologists to Match Breast Specialists in Screening
AI-powered workflow helps generalist radiologists detect breast cancer at rates comparable to specialists.