Association of deep learning-derived epicardial fat volume with target organ damage in subjects with nonobstructive coronary artery disease.

ABSTRACT:

Background

Epicardial fat exerts both protective and deleterious effects on organs through diverse cytokine-mediated pathways. This study aimed to investigate computed tomography (CT)-based indexed epicardial fat volume (EFVi) in association with target organ damage parameters.

Methods

The prospectively enrolled cohort of 75 patients with nonobstructive coronary artery disease underwent electrocardiogram-gated CT and was evaluated for target organ damage parameters: estimated glomerular filtration rate, proteinuria, echocardiographic septal e' velocity, E/e' and tricuspid regurgitation velocity, brachial-ankle pulse wave velocity, and ankle-brachial index. EFVi was measured from semiautomated 3D segmentation of electrocardiogram-gated CT. Partial correlation, multiple linear

SUBMITTER: Kim MY 

PROVIDER: S-EPMC12739840 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature