Coronary artery disease (CAD) is the most common manifestation of cardiovascular disease and the most common cause of mortality in the U.S. Coronary artery calcium scoring (CAC) is an important predictor of risk for CAD. If patients can be identified as high risk, they can reduce that risk through medical interventions and lifestyle changes. However, determining a CAC score requires a special, cardiac gated CT scan and is performed much less frequently than routine non-contrast chest CT.
An artificial intelligence (AI) algorithm using deep learning can enable clinicians to estimate the CAC score on routine non-contrast chest CT, potentially allowing opportunistic early preventive interventions. A multi-center team (including UCSF) took part in a study and developed a fully automatic, end-to-end deep learning model for automated CAC scoring using routine non-gated unenhanced…
