AI model detects breast arterial calcification on mammography

CHICAGO -- AI-based breast arterial calcification (BAC) detection on mammography is feasible and accurate, according to research presented November 28 at the RSNA 2023 annual meeting. In his presentation, Chirag Parghi, MD, from Solis Mammography discussed his team’s findings, which found that its algorithm showed high accuracy in BAC detection. This included a prevalence and distribution of BAC increasing with age in a screening population. “The reality is women are being diagnosed with heart attacks at an unprecedented rate,” Parghi said. “We poorly understand heart disease in women and who among women will get heart disease. We have a finding on a mammogram that can find women who can benefit from additional cardiovascular surveillance.” BACs have traditionally been evaluated as BI-RADS 2 lesions, often meaning no treatment is recommended. However, previous reports suggest that these benign findings are tied to the risk of developing type 2 diabetes, high blood pressure, and inflammation, as well as being a biomarker of stiffening in the arteries. Parghi and colleagues analyzed the accuracy and feasibility of using AI to detect and assess BAC on mammography in a large screening population across 15 sites. In their prospective study, the researchers included 2D mammography data from 117,189 asymptomatic women undergoing screening during a one-month period in 2023. The study assessed the overall prevalence and distribution of BAC across four age groups:
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: Breast Breast Imaging RSNA 2023 Source Type: news