Deep learning model based on contrast-enhanced ultrasound for predicting vessels encapsulating tumor clusters in hepatocellular carcinoma.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To establish and validate a non-invasive deep learning (DL) model based on contrast-enhanced ultrasound (CEUS) to predict vessels encapsulating tumor clusters (VETC) patterns in hepatocellular carcinoma (HCC).

Authors

  • Wenxin Xu
    From Dana-Farber Cancer Institute, Boston, MA, USA.
  • Haoyan Zhang
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
  • Rui Zhang
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Xian Zhong
    The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands.
  • Xiaoju Li
    Department of Pathology, Honghui Hospital, Xi'an Jiaotong University College of Medicine, Xi'an, Shaanxi, China.
  • Wenwen Zhou
    Department of Medical Ultrasonics, The First Affiliated Hospital, Institute of Diagnostic and Interventional Ultrasound, Sun Yat-Sen University, Guangzhou, China.
  • Xiaoyan Xie
    Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, China.
  • Kun Wang
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Ming Xu
    Shenyang Analytical Application Center, Shimadzu (China) Co. Ltd., Shenyang, 167 Qingnian Street, Shenyang, 110016, PR China.