CT-derived epicardial adipose tissue density: Systematic review and meta-analysis. Issue 143 (October 2021) - Monti, Caterina B.; Capra, Davide; Zanardo, Moreno; Guarnieri, Gianluca; Schiaffino, Simone; Secchi, Francesco; Sardanelli, Francesco
Highlights: There is a need for standardization of EAT density evaluation methods. Patients with coronary artery disease show higher EAT density values. EAT volume and segmentation thresholds correlate significantly with EAT density. Abstract: Purpose: The aim of our work was to systematically review and meta-analyze epicardial adipose tissue (EAT) density values reported in literature, assessing potential correlations of EAT density with segmentation thresholds and other technical and clinical variables. Method: A systematic search was performed, aiming for papers reporting global EAT density values in Hounsfield Units (HU) in patients undergoing chest CT for any clinical indication. After screening titles, abstract and full text of each retrieved work, studies reporting mean and standard deviation for EAT density were ultimately included. Technical, clinical and EAT data were extracted, and divided into subgroups according to clinical conditions of reported subjects. Pooled density analyses were performed both overall and for subgroups according to clinical conditions. Metaregression analyses were done to appraise the impact of clinical and technical variables on EAT volume. Results: Out of 152 initially retrieved works, 13 were ultimately included, totaling for 7683 subjects. EAT density showed an overall pooled value of −85.86 HU (95% confidence interval [95% CI] −91.84, −79.89 HU), being −86.40 HU (95% CI −112.69, −60.12 HU) in healthy subjects and −80.71 HU (95% CI −87.43, −73.99 HU) in patients with coronary artery disease. EAT volume and lower and higher segmentation thresholds were found to be significantly correlated with EAT density ( p = 0.044, p < 0.001 and p < 0.001 respectively). Conclusions: Patients with coronary artery disease appear to present with higher EAT density values, while the correlations observed at metaregression highlight the need for well-established, shared thresholds for EAT segmentation.