AI-Driven segmentation and morphogeometric profiling of epicardial adipose tissue in type 2 diabetes.

Journal: Cardiovascular diabetology
Published Date: Jul 18, 2025

Abstract

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 segmentation and morphogeometric analysis of EAT in T2D.

Authors

  • Fan Feng
    Institute of Forming Technology & Equipment, Shanghai Jiao Tong University, Shanghai, China.
  • Abdallah I Hasaballa
    Department of Computer Science, University of Oxford, Oxford, UK.
  • Ting Long
    Department of Radiology, PET Center, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, People's Republic of China.
  • Xinyi Sun
    Faculty of Medical and Health Sciences, School of Medicine, The University of Auckland, Auckland, New Zealand.
  • Justin Fernandez
    Auckland Bioengineering Institute, The University of Auckland, 70 Symonds Street, Auckland, 1010, New Zealand.
  • Carl-Johan Carlhäll
    Division of Diagnostics and Specialist Medicine, Department of Health Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
  • Jichao Zhao
    Auckland Bioengineering Institute, The University of Auckland, Auckland, 1142, New Zealand. Electronic address: j.zhao@auckland.ac.nz.

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