Scientists have developed an artificial intelligence (AI) algorithm capable of identifying heart disease risks in women during mammography screenings. This innovative approach enables the assessment of calcium buildup—or calcification—in the arteries, which is a key clinical indicator of cardiovascular disease.
Although cardiovascular disease is the leading cause of death in women, it often goes undetected. According to the American Heart Association, by 2050, one-third of women aged 20 to 44 will have some form of heart disease. At the same time, a large proportion of women undergo regular mammograms (nearly 70% of women over 40), creating an ideal opportunity to identify groups that do not undergo traditional cardiac screening.
Study Results
The study, which included over 120,000 women (including 74,000 participants from Emory Healthcare and 50,000 from the Mayo Clinic), saw researchers categorize mammography scans based on arterial calcification levels, defined as the “BAC score.”
The results were particularly striking. Women with “severe” calcification face twice the risk of cardiovascular complications compared to those with no calcium buildup. Furthermore, the method is effective in women under 50, allowing for the detection and management of heart disease risks at a much earlier stage.
Future Perspectives
The AI algorithm already exists and is available as an additional service in some clinics. However, experts emphasize the need for clinical trials to determine how treatment strategies should be adjusted once this information is obtained.
Physicians are urging radiologists to routinely begin documenting calcification levels during mammography. By leveraging this “hidden data,” it will be possible not only to identify risks but also to motivate patients, as visual evidence of arterial damage often has a greater impact on patients than abstract numbers from cholesterol tests.
