MRI-based machine-learning radiomics of the liver to predict liver-related events in hepatitis B virus-associated fibrosis.

Journal: European radiology experimental
Published Date: Aug 27, 2025

Abstract

BACKGROUND: The onset of liver-related events (LREs) in fibrosis indicates a poor prognosis and worsens patients' quality of life, making the prediction and early detection of LREs crucial. The aim of this study was to develop a radiomics model using liver magnetic resonance imaging (MRI) to predict LRE risk in patients undergoing antiviral treatment for chronic fibrosis caused by hepatitis B virus (HBV).

Authors

  • Yuankai Luo
    Hepatobiliary and Pancreatic Tumor Diagnosis and Treatment Center, Yuebei People's Hospital, Shaoguan, China.
  • Qinian Luo
    Department of Pain Management, Shaoguan Zhengtong Hospital, Shaoguan, China.
  • Yaobo Wu
    Infection and Hepatology Department, Zhuhai Clinical Medical College of Jinan University (Zhuhai People's Hospital), Zhuhai, China.
  • Shaorui Zhang
    Department of Ultrasound Medicine, Zhanjiang Central People's Hospital, Zhanjiang, China.
  • Huan Ren
    School of Medicine, Sun Yat-sen University, Shenzhen, China.
  • XiaoFeng Wang
    Indiana University Bloomington.
  • Xiujuan Liu
    Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China.
  • Qin Yang
    State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China; School of Physics and Optoelectronic Engineering, Yangtze University, Jingzhou 434023, China.
  • Weiguo Xu
  • Qingsong Wu
  • Yong Li
    Department of Surgical Sciences, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI, United States.

Keywords

External Resources

Popular Topics
Recent Journals