Using deep learning to predict microvascular invasion in hepatocellular carcinoma based on dynamic contrast-enhanced MRI combined with clinical parameters.

Journal: Journal of cancer research and clinical oncology
Published Date: Apr 10, 2021

Abstract

PURPOSE: Microvascular invasion (MVI) is a critical determinant of the early recurrence and poor prognosis of patients with hepatocellular carcinoma (HCC). Prediction of MVI status is clinically significant for the decision of treatment strategies and the assessment of patient's prognosis. A deep learning (DL) model was developed to predict the MVI status and grade in HCC patients based on preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical parameters.

Authors

  • Danjun Song
    Department of Liver Surgery, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, People's Republic of China.
  • Yueyue Wang
    Digital Medical Research Center, School of Basic Medical Science, Fudan University, Shanghai, 200032, People's Republic of China.
  • Wentao Wang
    Department of Radiation Oncology, Duke University Medical Center, Durham, NC, United States.
  • Yining Wang
    Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China.
  • Jiabin Cai
    Department of Liver Surgery, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, People's Republic of China.
  • Kai Zhu
    Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
  • Minzhi Lv
    Department of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
  • Qiang Gao
    Faculty of Material Science and Chemistry, China University of Geosciences, Wuhan 430074, PR China.
  • Jian Zhou
    CTIQ, Canon Medical Research USA, Inc., Vernon Hills, 60061, USA.
  • Jia Fan
    Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Shengxiang Rao
    Department of Radiology, Zhongshan Hospital, Fudan University, 200032, Shanghai, People's Republic of China. raoxray@163.com.
  • Manning Wang
    Digital Medical Research Center, Fudan University, Shanghai, China.
  • XiaoYing Wang

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