Machine learning-based radiomic features of perivascular adipose tissue in coronary computed tomography angiography predicting inflammation status around atherosclerotic plaque: a retrospective cohort study.

Journal: Annals of medicine
PMID: 39665384

Abstract

OBJECTIVES: This study expolored the relationship between perivascular adipose tissue (PVAT) radiomic features derived from coronary computed tomography angiography (CCTA) and the presence of coronary artery plaques. It aimed to determine whether PVAT radiomic could non-invasively assess vascular inflammation associated with plaque presence.

Authors

  • Kunlin Ye
    Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China.
  • Lingtao Zhang
    Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China.
  • Hao Zhou
    State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China.
  • Xukai Mo
    Medical Imaging Center, The First Affiliated Hospital of Jinan University, No 613 Huangpu Dadao West, Guangzhou, 510630, China.
  • Changzheng Shi
    Medical Imaging Center, The First Affiliated Hospital of Jinan University, No 613 Huangpu Dadao West, Guangzhou, 510630, China. tsczcn@jnu.edu.cn.

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