Ultrasound evaluation of epicardial fat and Eco-Obesity body composition assessment

To validate echocardiographic epicardial adipose tissue (EAT) thickness as a non-invasive marker of cardiometabolic risk in obesity and compare Eco-Obesity ultrasound-derived measurements of epicardial, preperitoneal, omental, and peri-renal fat depots with standard body composition analysis by dual-energy X-ray absorptiometry (DEXA).

In a cross-sectional study of 402 adults with obesity attending two Barcelona centers, Eco-Obesity ultrasound was performed in 114 subjects, alongside DEXA scans. Thickness of epicardial and abdominal fat depots, metabolic markers, and anthropometric indices were measured using standardized protocols. Relationships among ultrasound fat measurements, DEXA indices, anthropometric variables, and biochemical markers were analyzed by Pearson correlation coefficients; subgroup comparisons used ANOVA.

Moderate (>7mm) and severe (>10mm) EAT thickness were found in 35.6% and 53.1% of patients. EAT measured in long-axis, short-axis, and posterior cardiac recess (PPR) projections correlated significantly with BMI, waist circumference, and waist-to-height ratio (all p<0.02), and was associated with omental and peri-renal fat compartments. The EAT long-axis projection showed the strongest and most consistent correlations with anthropometric and DEXA visceral fat indices. Omental and peri-renal fat layers correlated significantly with anthropometric and DEXA visceral fat, while pre-peritoneal fat did not. EAT PPR correlated positively with glycemia, HOMA-IR, triglycerides, and negatively with HDL cholesterol; EAT long- and short-axis also correlated with glycemia and HOMA-IR. Omental fat exhibited the strongest associations with glycemia, HOMA index, and HbA1c, and peri-renal fat showed significant positive association with fasting glycemia and inverse association with HDL.

EAT is a metabolically active visceral depot associated with adiposity and metabolic dysfunction in obesity. Routine ultrasonographic assessment of EAT should be integrated into clinical protocols for body composition analysis in the obese population (Eco-Obesity approach).