Relationship of epicardial fat volume with coronary plaque characteristics, coronary artery calcification score, coronary stenosis, and CT-FFR for lesion-specific ischemia in patients with known or suspected coronary artery disease

Highlights

• EFV was associated with adverse plaque characteristics and lesion-specific ischemia in patients with known or suspected CAD.

Abstract

Background

We explored the association of epicardial fat volume (EFV) with coronary plaque characteristics, coronary artery calcification (CAC) score, coronary stenosis, lesion-specific ischemia in patients with known or suspected coronary artery disease (CAD).

Methods

88 controls and 221 patients were analyzed in the study. High-risk plaque was defined as existing≥2 features, including positive remodeling, low attenuation, napkin-ring sign and spotty calcification. EFV, CAC score was measured. The severity of coronary stenosis was quantified using Gensini score. CT-FFR was performed in three major coronary arteries, with a threshold of ≤0.8 considered the presence of ischemia. Univariate and multivariate regression was used to evaluate the association of EFV with CAD, palque characteristics, CAC score, Gensini score, and lesion-specific ischemia derived from CT-FFR.

Results

Median EFV was 104.97 cm³ (85.47–136.09) in controls and 129.28cm³ (101.19–159.44) in patients (P < 0.001). Logistic regression analysis revealed a significant association of EFV with CAD even after adjusting for confounding factors (P < 0.05). At linear regression analysis, EFV was significantly correlated with high-risk plaque and lesion-specific ischemia, but not with non-calcified plaque, mixed plaque, calcified plaque, CAC score and Gensini score (P ≥ 0.05).

Conclusion

We found that EFV was associated with CAD, suggesting that it may be a promising marker of CAD. EFV was also correlated with high-risk plaque and lesion-specific ischemia, indicating that EAT was likely to be involved in myocardial ischemia and had the potential to definite patients' risk profile.

Introduction

Coronary artery disease (CAD) is one of the most frequent forms of cardiovascular disease and is mainly caused by coronary atherosclerosis. CAD is characterized by progressive atherosclerotic occlusion of the coronary arteries, resulting in the heart not acquiring sufficient oxygen-rich blood to meet its metabolic demands [1]. CAD can cause a series of conditions including myocardial infarction, heart failure, or sudden death. Recently, organ-specific adiposity has attracted increasing attention due to its pathophysiological role in cardiometabolic diseases. Epicardial adipose tissue (EAT) is a metabolically active fat depot surrounding the cardiac and coronary [2]. Because of its proximity to the cardiac anatomy, the two tissues share the same microcirculation supply, and EAT can directly regulate coronary and affect myocardium through paracrine and vascular secretory pathways [[3], [4], [5]]. When EAT is dysfunctional, it secretes various pro-inflammatory cytokines, bioactive molecules, and adipokines, which influence metabolism and cause local inflammation and various pathological changes [6,7]. An increasing number of studies have accepted that EAT plays a role in the development and progression of CAD [4,8], possibly due to the decrease of beneficial adipokines and the increase of pathogenic adipokines [9]. Thus, a deeper understanding of the relationship between EAT and CAD may help predict the occurrence and progression of CAD and contribute to identifying better therapeutic strategies. Recently, a multicenter study demonstrated that epicardial fat volume (EFV) could improve the predictive ability of pretest probability of obstructive CAD over traditional risk factors, providing a valuable tool to determine optimal imaging modality [10]. Over the past years, there have been considerable interest in the association between EAT and CAD risks, such as coronary stenosis, plaque characteristics, coronary artery calcification (CAC) score, myocardial ischemia [[11], [12], [13], [14], [15], [16]]. Although these evidences indicating that increased EAT is associated with CAD risk, the clinical significance of EAT in CAD remains largely unknown.

Coronary computed tomography angiography (CCTA) has emerged as a non-invasive imaging technique used for the assessment of CAD. However, purely assessing anatomy has certain limitations in predicting the functional significance of CAD [17], which is essential for guiding meaningful clinical decision-making and providing reliable prognostic information. The non-invasive fractional flow reserve (FFR) derived from CCTA (CT-FFR) based on machine learning algorithm or computational fluid dynamics (CFD) model can be used to accurately detect lesion-specific ischemia, and has been verified by the gold standard invasive coronary angiography (ICA) with FFR [[18], [19], [20], [21], [22]]. Therefore, in this study, multidetector computed tomography scans were used to quantify EFV to explore whether EFV is associated with plaque characteristics, CAC score, coronary stenosis and lesion-specific ischemia evaluated by CT-FFR in patients with known or suspected CAD.