Cardiac adipose tissue, imaging segmentation, and quantification for cardiovascular disease assessment

Read full text
Authors: Julian Rene Cuellar Buritica, Mukul Bhattarai, Pedro Luis González Carrillo, Manjula V. Burri, Jon D. Klingensmith
Cited by: 0
References: 132

Abstract

Cardiac adipose tissue (CAT) has emerged as a critical and clinically relevant factor in cardiovascular disease (CVD), yet its full impact remains largely overlooked. The amount of fat surrounding the heart can influence major blood vessels by promoting plaque formation. In conditions such as cardiac steatosis or fatty heart disease, fat infiltration or accumulation within the heart muscle compromises its function may play a role in heart failure (HF) and coronary artery disease (CAD). This review explores the different types of fat deposits surrounding the heart, focusing on the potential contribution of CAT to cardiovascular disease (CVD). Three main imaging modalities for assessing cardiac fat are discussed, including magnetic resonance imaging (MRI), computed tomography (CT), and echocardiography. The segmentation and quantification of the fat for each imaging modality are also presented, correlating these measurements with CVD risk. Each imaging modality offers distinct advantages and limitations in segmenting and quantifying fat. Despite its clinical significance, quantification and characterization of CAT remain challenging, requiring advanced imaging techniques for precise assessment. Future research should focus on unlocking the mechanistic pathways that link CAT to adverse cardiovascular outcomes, ultimately enhancing our ability to predict, prevent, and treat heart disease with greater precision. As imaging technology advances, there is a need for refined segmentation methods and consensus-driven guidelines to establish CAT as a key biomarker in CVD risk stratification.

Fields of Study & Subjects

Cardiovascular Disease and Adiposity Cardiovascular Function and Risk Factors Cardiac Imaging and Diagnostics

Publication details

Journal / source
Frontiers in Imaging
Volume
4
Publication date
8 January 2026