Prediction of prognosis of immune checkpoint inhibitors combined with anti-angiogenic agents for unresectable hepatocellular carcinoma by machine learning-based radiomics.

Journal: BMC cancer
Published Date: May 19, 2025

Abstract

OBJECTIVES: This study aims to develop and validate a novel radiomics model utilizing magnetic resonance imaging (MRI) to predict progression-free survival (PFS) in patients with unresectable hepatocellular carcinoma (uHCC) who are receiving a combination of immune checkpoint inhibitors (ICIs) and antiangiogenic agents. This is an area that has not been previously explored using MRI-based radiomics.

Authors

  • Xuni Xu
    Department of Radiology, Shaoxing Central Hospital, The Central Affiliated Hospital, Shaoxing University, Shaoxing, 312000, China.
  • Xue Jiang
    Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China.
  • Haoran Jiang
    Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States.
  • Xiaoye Yuan
    Department of Radiation and Chemotherapy Oncology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
  • Mengjing Zhao
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China.
  • Yuqi Wang
    Graduate School at Shenzhen, Tsinghua University, Shenzhen, Guangdong, P.R. China.
  • Gang Chen
    Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
  • Gang Li
    The Centre for Cyber Resilience and Trust, Deakin University, Australia.
  • Yuxia Duan
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China.

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