Percentage of Low-Attenuation Epicardial Adipose Volume (LAAV%) as an Independent Predictor of Coronary Microvascular Dysfunction: A Retrospective Cohort Study.

BACKGROUND

Clinically, coronary microvascular dysfunction (CMD) remains a significant diagnostic challenge because the associated symptoms frequently overlap with obstructive coronary artery disease (CAD). This condition may contribute to cardiac ischemic events regardless of the presence of obstructive epicardial lesions. While inflammatory pathways, particularly those involving epicardial adipose tissue (EAT) accumulation, play a central role in the development of CMD, the specific influence of EAT quality, as reflected in the associated density-based composition, remains poorly understood.

METHODS

This retrospective study (n = 155) analyzed a single primary vessel per patient to ensure independence of data. Based on invasive physiological assessment, patients were stratified into an isolated CMD group (n = 81), defined as fractional flow reserve (FFR) ≥0.75 with coronary flow reserve (CFR) <2.5 and/or index of microcirculatory resistance (IMR) ≥25 and a non-CMD control group (n = 74), which included patients with obstructive CAD (FFR <0.75, stenosis >50%) and those with normal physiology. Quantitative assessment using coronary computed tomography angiography (CCTA) applied a range of -190 to -15 Hounsfield units (HU). Perivascular inflammation was evaluated by measuring the low-attenuation adipose volume (LAAV) (<-75 HU) as a percentage of total EAT (LAAV%). Independent determinants of CMD were identified using multivariable logistic regression models.

RESULTS

Multivariable analysis identified standardized LAAV% as the primary independent predictor of CMD. Specifically, each one-standard deviation (SD) increase in LAAV% was associated with a 147.1% increase in odds of CMD (odds ratios (OR) = 2.471, 95% confidence interval (CI): 1.577-4.128, p < 0.001). The predictive framework demonstrated robust performance (area under the receiver operating characteristic curve (AUC) = 0.810). Additional significant risk factors included body mass index (BMI) (OR = 1.380) and smoking history (OR = 4.005, p = 0.023).

CONCLUSIONS

Low-attenuation areas of EAT, particularly as quantified by standardized LAAV%, are strong independent predictors of CMD. The integration of LAAV% into non-invasive risk assessments may improve diagnostic accuracy and help inform targeted interventions for CMD.