Epicardial Fat Tissue: A Potential Marker for Coronary Microvascular Dysfunction

Abstract

Background: Coronary microvascular dysfunction (CMD), which mimics symptoms of obstructive coronary artery disease, has significant prognostic implications. While epicardial adipose tissue normally has a protective role, increased epicardial adipose tissue is associated with inflammation and may contribute to CMD. However, a direct correlation remains unclear. We aimed to investigate this association.

Methods and results: The CMDR (Coronary Microvascular Disease Registry) is a prospective, 2-center registry that is enrolling patients with angina and nonobstructive coronary artery disease who underwent invasive hemodynamic assessment of the coronary microvasculature. Patients with chest computed tomography within 1 year of CMD evaluation were included. We measured epicardial fat volume (EFV) and calculated the EFV index. Logistic regression analysis was used to investigate the association between EFV and EFV index to CMD. Our study included 130 CMDR patients with associated chest CT; 35 were diagnosed with CMD. The CMD-negative patients were younger than the CMD-positive patients (58.52±11.97 versus 63.37±9.56 years; P=0.033), with numerically fewer women (64.2% versus 74.3%; P=0.279). Univariate regression analysis demonstrated a statistically significant association between EFV index and CMD diagnosis (odds ratio, 1.037 [95% CI, 1.014-1.063]; P=0.003), while no significance was observed for EFV (odds ratio, 1.006 [95% CI, 0.995-1.017]; P=0.292).

Conclusions: Our results suggest a strong association between EFV index (a significant risk factor) and the presence of CMD. Future studies involving larger cohorts are needed to confirm the association of epicardial adipose tissue with CMD and investigate therapeutic targets to prevent CMD.

Registration: URL: https://www.clinicaltrials.gov; unique identifier: NCT05960474.

Keywords: computed tomography; coronary artery disease; coronary microvascular dysfunction; epicardial fat.

Figure 1. CT imaging of EFV measurement.

Quantification of EFV on nongated noncontrast (A through C) and gated coronary CT angiography (D through F) using semiautomated software. CT images with the epicardial boundary delineated by the blue contour line on each slice from bifurcation of the main pulmonary artery and the last visible border of the pericardium (A and D). Within the region of interest, fat voxels were identified using a threshold attenuation range of − 190 to − 30 Hounsfield units (B and E). The EFV is automatically calculated by the software (C and F). CT indicates computed tomography; and EFV, epicardial fat volume.

Figure 2. Relationship between epicardial fat measures [epicardial fat volume (A) epicardial fat volume index (B)] and predicted probability of coronary microvascular dysfunction.

A, This graph displays the predictive modeling results illustrating the correlation between the epicardial fat index and the probability of coronary microvascular dysfunction diagnosis. The red line represents the predicted probability curve. The shaded pink area around the line represents the 95% CI. B, This graph displays the predictive modeling results illustrating the correlation between the epicardial fat volume and the probability of coronary microvascular dysfunction diagnosis. The red line represents the predicted probability curve. The shaded pink area around the line represents the 95% CI. OR indicates odds ratio.

Figure 3. Correlation between age and epicardial fat volume index by CMD status.

This scatter plot illustrates the correlation between age (in years) and epicardial fat volume index for 2 groups of individuals: those with a negative coronary microvascular dysfunction (CMD) status (blue circles) and those with a positive CMD status (red pluses). The blue solid line represents the linear regression model for the CMD‐negative group. The red dashed line models the trend for the CMD‐positive group. CMD indicates coronary microvascular dysfunction.