Multilayer perceptron deep learning radiomics model based on Gd-BOPTA MRI to identify vessels encapsulating tumor clusters in hepatocellular carcinoma: a multi-center study.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
Published Date: Jul 7, 2025

Abstract

OBJECTIVES: The purpose of this study is to mainly develop a predictive model based on clinicoradiological and radiomics features from preoperative gadobenate-enhanced (Gd-BOPTA) magnetic resonance imaging (MRI) using multilayer perceptron (MLP) deep learning to predict vessels encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC) patients.

Authors

  • Mengting Gu
    Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Wenjie Zou
    Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
  • HuiLin Chen
    Shanghai Jiangong Hospital Intensive Care Unit (ICU), Shanghai 200083, China.
  • Ruilin He
    School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Xingyu Zhao
    University of Science and Technology of China, Hefei, China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.
  • Ningyang Jia
    Department of Radiology, Easter Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China. ningyangjia@163.com.
  • Wanmin Liu
    Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Peijun Wang
    Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, P.R. China.

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