Objectives: Epicardial adipose tissue (EAT) from coronary CT angiography (CCTA) is strongly associated with coronary artery disease (CAD). We investigated the additive value of EAT volume to coronary plaque quantification and CT-derived fractional flow reserve (CT-FFR) to predict lesion-specific ischemia. 

Methods: Patients (n=128, 60.6±10.5 years, 61% male) with suspected CAD who had undergone invasive coronary angiography (ICA) and CCTA were retrospectively analyzed. EAT volume and plaque measures were derived from CCTA using a semi-automatic software approach, while CT-FFR was calculated using a machine-learning algorithm. The predictive value and discriminatory power of EAT volume, plaque measures, and CT-FFR to identify ischemic CAD were assessed using invasive FFR as the reference standard. 

Results: Fifty-five of 152 lesions showed ischemic CAD by invasive FFR. EAT volume, CCTA ≥50% stenosis, and CT-FFR were significantly different in lesions with and without hemodynamic significance (all p<0.05). Multivariate analysis revealed predictive value for lesion-specific ischemia of these parameters: EAT volume (OR 2.93, p=0.021), CCTA ≥50% (OR 4.56, p=0.002), and CT-FFR (OR 6.74, p<0.001). ROC analysis demonstrated incremental discriminatory value with the addition of EAT volume to plaque measures alone (AUC 0.84 vs. 0.62, p<0.05). CT-FFR (AUC 0.89) showed slightly superior performance over EAT volume with plaque measures (AUC 0.84), however, without significant difference (p>0.05). 

Conclusions:  EAT volume is significantly associated with ischemic CAD.  The combination of EAT volume with plaque quantification demonstrates a predictive value for lesion-specific ischemia similar to that of CT-FFR. Thus, EAT assessment has the potential to improve the therapeutic management of CAD.