# Prognostic value of lesion-specific and proximal coronary segment pericoronary adipose tissue CT Attenuation in ischemic heart disease with angina pectoris

## TL;DR

This study shows that measuring fat tissue around coronary arteries using CT scans can help predict heart disease risks, with specific areas providing better insights into severe outcomes.

## Contribution

The study introduces lesion-specific and proximal pericoronary adipose tissue attenuation as novel predictors of cardiovascular events in ischemic heart disease.

## Key findings

- Proximal and lesion-specific PCATa are independent predictors of MACE with comparable performance.
- RCA-PCATa shows superior association with severe outcomes like sudden cardiac death and myocardial infarction.
- Incorporating PCATa into clinical models significantly improves predictive accuracy for MACE.

## Abstract

This study aimed to evaluate the prognostic value of lesion-specific and proximal 40 mm pericoronary adipose tissue attenuation (PCATa) in predicting major adverse cardiovascular events (MACE) in patients with ischemic heart disease presenting with angina pectoris and to compare their predictive performance. This retrospective study included 213 patients with ≥ 50% coronary artery stenosis who underwent coronary computed tomography angiography and digital subtraction angiography between January 2020 and August 2023. MACE was assessed over a median follow-up period of 15 months. Cox proportional hazards models were used to identify MACE risk factors, and the incremental predictive value of PCATa was evaluated using the C-index and global Chi-square statistics. MACE occurred in 72 patients (33.80%). The proximal 40 mm PCATa (LAD: HR = 1.041, LCX: HR = 1.046, RCA: HR = 1.043; all P < 0.01) and lesion-specific PCATa (HR = 1.048, P = 0.001) were independent predictors of MACE, and their prognostic performance was comparable. In the secondary endpoint analysis, defined as a composite of all-cause mortality, sudden cardiac death, and acute myocardial infarction, only elevated RCA-PCATa (HR = 1.084, 95% CI: 1.026–1.146, P = 0.004) was independently associated with adverse outcomes. Risk stratification models integrating PCATa cutoff values and angina status demonstrated robust predictive ability for MACE. Incorporating PCATa into clinical risk models significantly improved the C-index and global Chi-square values for MACE prediction (all P < 0.01). These findings suggest that incorporating PCATa to clinical models significantly improves prognostic accuracy, with comparable performance between proximal and lesion-specific PCATa, while RCA-PCATa may provide superior prognostic value for the most severe cardiovascular outcomes.

The online version contains supplementary material available at 10.1038/s41598-025-25445-y.