Overview

Researchers at Mass General Brigham, in collaboration with the United States Department of Veterans Affairs (VA), have developed an innovative AI tool designed to analyze previously collected CT scans. This tool aims to identify individuals with elevated coronary artery calcium (CAC) levels, which are indicative of a higher risk for cardiovascular events. The findings of their study, published in NEJM AI, demonstrate that the AI tool, named AI-CAC, exhibits high accuracy and predictive capabilities for future heart attacks and 10-year mortality rates.

Key Findings

• The AI-CAC tool can analyze chest CT scans, which are often performed for other health screenings, such as lung cancer.
• Senior author Hugo Aerts, PhD, emphasized that significant cardiovascular risk information is often overlooked in these scans.
• The AI-CAC model achieved an accuracy of 89.4% in detecting CAC and 87.3% in assessing moderate cardiovascular risk.
• Patients with a CAC score exceeding 400 were found to have a 3.49 times higher risk of death over a decade compared to those with a score of zero.
• Cardiologists confirmed that 99.2% of patients identified with high CAC scores would benefit from lipid-lowering therapy.

Implications for Clinical Practice

According to first author Raffi Hagopian, MD, the existing VA imaging systems contain millions of non-gated chest CT scans, which can be utilized for cardiovascular risk evaluation. The implementation of AI-CAC could shift the medical approach from reactive to proactive, enhancing disease prevention and potentially reducing healthcare costs.

Study Limitations

While the study presents promising results, it is important to note that the AI model was developed using a veteran population. Future research is planned to assess its applicability in the general population and to evaluate the effects of lipid-lowering medications on CAC scores.

For further details, refer to the original study: AI Opportunistic Coronary Calcium Screening at Veterans Affairs Hospitals.