Cardiac Volumes and Coronary Calcium Predicting Mortality

Recent advancements in artificial intelligence (AI) have enabled the quantification of coronary artery calcium (CAC) and cardiac chamber volumes from non-gated CT imaging, which is valuable for cancer screening. While manual CAC measurement is accurate but time-consuming, AI has automated this process and shown associations with cardiovascular mortality. This study integrated AI models to automatically estimate CAC, cardiac chamber volumes, and left ventricular mass from low-dose lung CT scans, aiming to evaluate their potential for predicting clinical outcomes across three external populations.