Work

Correlation Between Epicardial Adipose Tissue and PET Cardiac Perfusion: A Systematic Review

Year: 2026

Type: review

Abstract: Background: Evidence on the presence of an association between epicardial adipose tissue (EAT) and myocardial perfusion imaging (MPI) as assessed by positron emission tomography (PET) has been reported. This systematic review aimed to synthesize the existing literature investigating this topic. Methods: A comprehensive and systematic search of the PubMed/MEDLINE, Scopus, and Embase databases was performed to identify published studies investigating the association between EAT and myocardial perfusion assessed by PET imaging. Eligible studies included original research articles evaluating EAT and reporting PET MPI outcomes. Data regarding the study design, patient characteristics, imaging protocols, and main findings were extracted and qualitatively analyzed. Results: Ten studies were included in the final analysis. Overall, most studies demonstrated a significant association between increased EAT and impaired myocardial perfusion on PET imaging. In several studies, EAT remained an independent predictor of abnormal PET MPI after adjustment for traditional clinical risk factors. Nonetheless, important methodological differences among studies were observed, including heterogeneity in EAT measurement techniques, quantification methods, and PET tracers used for MPI evaluation, which limit the generalizability of these findings. Conclusions: This systematic review seems to suggest a potential association between increased EAT and impaired myocardial perfusion, as assessed by PET. However, significant methodological heterogeneity across the available studies—including differences in EAT quantification, PET protocols, and tracer selection—limits the strength of this conclusion. Standardized imaging protocols and larger, prospective, multicenter studies are required to validate this relationship, determine its incremental prognostic value, and evaluate its potential for integration into routine clinical risk stratification pathways.

Source: Medical Sciences

DOI: 10.3390/medsci14020194