Epicardial Fat Parameters on Multidetector Computed Tomography as Predictors of Obstructive Coronary Artery Disease

Objective This study was designed to test if multidetector computed tomography-derived epicardial fat parameters like epicardial fat volume, thickness, and attenuation can predict obstructive coronary artery disease in a South Indian Population. Methods All 60 patients underwent a coronary angiogram using 128-slice multidetector computed tomography. Computed tomography coronary angiogram studies were evaluated for coronary artery calcium score, presence of plaque, type of plaque, epicardial fat volume, and degree of coronary stenosis. Results 60 patients had a mean age of 51.7 ± 11.4 years. Obstructive coronary artery disease (≥50% luminal narrowing) was found in 91.7% of males. Various risk factors for coronary artery disease were diabetes mellitus (40%), hypertension (55%), hyperlipidemia (58.33%), smoking (15%), and body mass index >25 (41.67%). These risk factors were higher in the “obstructive coronary artery disease” group than in the “no/non-obstructive coronary artery disease” group, with a statistically significant correlation. Mean epicardial fat volume for the studied population was found to be 114.26 ± 45.68 cm 3 with values ranging from 38.55 cm 3 to 270.08 cm 3 . The mean epicardial fat volume of “obstructive coronary artery disease” group was found to be higher, that is, 137.69 ± 29.44 cm 3 compared to “no/non-obstructive coronary artery disease” group, which was 108.4 ± 47 cm 3 , showing a statistically significant correlation ( P = .046). Multiple variables showed a positive correlation of epicardial fat volume with the increasing degree of coronary artery stenosis. Epicardial fat volume demonstrated a statistically significant correlation with age ( P = .007), hypertension ( P = .001), hyperlipidemia ( P = .034), smoking ( P = .002), and body mass index ( P 110.48 cm 3 was obtained, which shows a sensitivity and specificity of 91.67% and 60.42%, respectively. Epicardial fat volume (multidetector computed tomography) is a significant imaging biomarker for predicting obstructive coronary artery disease with a cutoff value of >110.48 cm³ for differentiating.