Sex-specific cardiovascular risk prediction using AI-derived epicardial adipose tissue measurements on CT calcium scoring exams.

ABSTRACT:

Background

The Agatston CAC score from CT-calcium scoring (CTCS) is a standard guideline recommended measure for cardiovascular risk assessment that quantifies calcified plaque burden. However, many studies have reported lower discrimination of CTCS in females. Embedded epicardial adipose tissue (EAT) features have previously been shown to improve prediction of calcium scoring, and we hypothesized that it may provide incremental prognostic information in females. In this study, we evaluate whether integrating epicardial "fat-omics" with CAC score improves major adverse cardiac events (MACE) prediction from CTCS in females and assess the added value of sex-specific modeling.

Methods

40,851 individuals undergoing CTCS for primary prevention (CLARIFY Registry, NCT04075162) were

SUBMITTER: Singh P 

PROVIDER: S-EPMC12775966 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature