Machine learning-based Radiomics analysis for differentiation degree and lymphatic node metastasis of extrahepatic cholangiocarcinoma.

Journal: BMC cancer
PMID:

Abstract

BACKGROUND: Radiomics may provide more objective and accurate predictions for extrahepatic cholangiocarcinoma (ECC). In this study, we developed radiomics models based on magnetic resonance imaging (MRI) and machine learning to preoperatively predict differentiation degree (DD) and lymph node metastasis (LNM) of ECC.

Authors

  • Yong Tang
    Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Chun Mei Yang
    Department of Radiology, The Affiliated Hospital of Southwest Medical University, and Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, 646000, Sichuan, China.
  • Song Su
    Business School, Beijing Normal University, Beijing 100875, China. Electronic address: sus@bnu.edu.cn.
  • Wei Jia Wang
    School of Information and Software Engineering, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, Sichuan, China.
  • Li Ping Fan
    Department of Ultrasound, The Affiliated Hospital of Southwest Medical University, 25 Taiping Street, Luzhou, 646000, Sichuan, China. 934221663@qq.com.
  • Jian Shu
    Key Laboratory of Analysis and Detection for Food Safety (MOE and Fujian Province), Collaborative Innovation Center of Detection Technology for Haixi Food Safety and Products (Fujian Province), State Key Laboratory of Photocatalysis on Energy and Environment, Department of Chemistry, Fuzhou University , Fujian Province, China , 350002.