Detection of arterial remodeling using epicardial adipose tissue assessment from CT calcium scoring scan.

ABSTRACT:

Introduction

Non-contrast CT calcium scoring (CTCS) exams have been widely used to assess coronary artery disease. However, their clinical applications in predicting coronary arterial remodeling remain unknown. This study aimed to develop a novel machine learning model to predict positive remodeling (PR) from CTCS scans and evaluate its clinical value in predicting major adverse cardiovascular events (MACE).

Methods

We analyzed data from 1,324 patients who underwent both CTCS and CT angiography. PR was defined as an outer vessel diameter at least 10% greater than the average diameter of the segments immediately proximal and distal to the plaque. We utilized a total of 246 features, including 23 clinical features, 12 Agatston score-derived features, and 211 epicardial fat-omi

SUBMITTER: Lee J 

PROVIDER: S-EPMC11951307 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature