AI-driven quantification of breast arterial calcification (BAC) on mammograms predicts risk of major cardiovascular events in women, independent of traditional risk scores.
Key Details
- 1Study used a transformer-based segmentation model to quantify BAC on mammograms from 123,762 women across Emory Healthcare and Mayo Clinic Enterprise.
- 2BAC severity (mild, moderate, severe) was associated with incrementally higher hazard ratios for major adverse cardiovascular events (up to HR 3.29 for severe BAC in the Emory cohort).
- 3Incidence of major cardiovascular events increased more than 8-fold from zero to severe BAC category in the Emory cohort.
- 4Dose-response noted: each 1 mm² increase in BAC conferred an additional 2–3% risk for major events (p < 0.001).
- 5AI-derived BAC scores add prognostic value beyond the PREVENT cardiovascular risk calculator, offering a non-invasive risk assessment using existing mammogram data.
Why It Matters

Source
AuntMinnie
Related News

Study Reveals Major Impact of Incorrect AI Suggestions in Mammography Reads
Incorrect AI suggestions, especially false-negatives, significantly reduce reader sensitivity and alter visual search in mammography interpretation.

Framework Assesses Real-World Financial Impact of Radiology AI Adoption
A new analysis presents a financial calculator for objectively assessing the return on investment (ROI) of implementing radiology AI solutions.

AI Technique Unveils Previously Hidden MS Gray Matter Lesions on MRI
Researchers developed an AI-enhanced method to detect previously invisible gray matter lesions in multiple sclerosis using MRI.