Automated proximal coronary artery calcium identification using artificial intelligence: advancing cardiovascular risk assessment.

ABSTRACT:

Aims

Identification of proximal coronary artery calcium (CAC) may improve prediction of major adverse cardiac events (MACE) beyond the CAC score, particularly in patients with low CAC burden. We investigated whether the proximal CAC can be detected on gated cardiac CT and whether it provides prognostic significance with artificial intelligence (AI).

Methods and results

A total of 2016 asymptomatic adults with baseline CAC CT scans from a single site were followed up for MACE for 14 years. An AI algorithm to classify CAC into proximal or not was created using expert annotations of total and proximal CAC and AI-derived cardiac structures. The algorithm was evaluated for prognostic significance on AI-derived CAC segmentation. In 303 subjects with expert annotations, the classif

SUBMITTER: Zhou J 

PROVIDER: S-EPMC11879235 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature