BACKGROUND: Obesity is a disease with high heterogeneity. Both overall obesity and central obesity are associated with increased risks of having cardio-metabolic co-morbidities. This study is aimed to examine the cardio-metabolic characteristics and ...
BACKGROUND: Epicardial adipose tissue is gaining increasing interest as a cardiometabolic imaging biomarker, but its exact role in coronary artery disease is not fully understood. This study aimed to investigate the relationship between epicardial ad...
Metabolic dysfunction-associated steatotic liver disease (MASLD) in children with obesity correlates with metabolic dysfunction, yet interactions between anthropometrics, liver enzymes, and risk of MASLD remain unclear. This study included 219 childr...
BACKGROUND: Epicardial adipose tissue (EAT) is associated with cardiometabolic risk in type 2 diabetes (T2D), but its spatial distribution and structural alterations remain understudied. We aim to develop a shape-aware, AI-based method for automated ...
Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysiological correlates of this tissue are unclear, and its genetic determinants remain unknown. Here, w...
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Sep 5, 2024
BACKGROUND: Cardiovascular magnetic resonance (CMR) chemical shift encoding (CSE) enables myocardial fat imaging. We sought to develop a deep learning network (fast chemical shift encoding [FastCSE]) to accelerate CSE.
BACKGROUND: The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D).
Diabetes research and clinical practice
Jun 25, 2024
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a growing chronic disease that can lead to disability and early death. This study aimed to establish a predictive model for the 10-year incidence of T2DM based on novel anthropometric indices.
PURPOSE: The purpose of this study is to compare fully automated CT-based measures of adipose tissue at the L1 level versus the standard L3 level for predicting mortality, which would allow for use at both chest (L1) and abdominal (L3) CT.
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