A Multiparametric Fusion Deep Learning Model Based on DCE-MRI for Preoperative Prediction of Microvascular Invasion in Intrahepatic Cholangiocarcinoma.

Journal: Journal of magnetic resonance imaging : JMRI
PMID:

Abstract

BACKGROUND: Assessment of microvascular invasion (MVI) in intrahepatic cholangiocarcinoma (ICC) by using a noninvasive method is an unresolved issue. Deep learning (DL) methods based on multiparametric fusion of MR images have the potential of preoperative assessment of MVI.

Authors

  • Wenyu Gao
    Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China.
  • Wentao Wang
    Department of Radiation Oncology, Duke University Medical Center, Durham, NC, United States.
  • 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.
  • Kang Wang
    Department of Orthopedics, Third Hospital of Changsha, Changsha 410015.
  • Danlan Lian
    Department of Radiology, Xiamen Branch, Zhongshan Hospital, Fudan University, Xiamen, China.
  • Chun Yang
    State Key Laboratory of Biogeology and Environmental Geology, School of Earth Sciences, China University of Geosciences, Wuhan, 430074, China.
  • Kai Zhu
    Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
  • Jiaping Zheng
  • Mengsu Zeng
    Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Sheng-Xiang Rao
    Department of Radiology, Cancer center, Zhongshan Hospital, Fudan University, China.
  • Manning Wang
    Digital Medical Research Center, Fudan University, Shanghai, China.