Radiomics and deep learning features of pericoronary adipose tissue on non-contrast computerized tomography for predicting non-calcified plaques.

Journal: Journal of X-ray science and technology
PMID: 39973776

Abstract

BACKGROUND: Inflammation of coronary arterial plaque is considered a key factor in the development of coronary heart disease. Early the plaque detection and timely treatment of the atherosclerosis could effectively reduce the risk of cardiovascular events. However, there is no study combining radiomics with deep learning techniques to predict non-calcified plaques (NCP) in coronary artery at present.

Authors

  • Junli Yu
    School of Medical Technology, Qiqihar Medical University, Qiqihar, China.
  • Yan Ding
    Department of Computer Science and Engineering, Changshu Institute of Technology, Changshu 215500, China.
  • Li Wang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Shunxin Hu
    School of Medical Technology, Qiqihar Medical University, Qiqihar, China.
  • Ning Dong
    Jinling Clinical Medical College, Nanjing Medical University，Nanjing，Jiangsu 210002，China.
  • Jiangnan Sheng
    Department of Radiology, The Third Affiliated Hospital of Qiqihar Medical University, Qiqihar, China.
  • Yingna Ren
    Department of Radiology, The Third Affiliated Hospital of Qiqihar Medical University, Qiqihar, China.
  • Ziyue Wang
    Mingxu Technology Co., Ltd., Shanghai, China.

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