Deep learning radiomics based on contrast enhanced computed tomography predicts microvascular invasion and survival outcome in early stage hepatocellular carcinoma.

Journal: European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Published Date: Nov 19, 2021

Abstract

OBJECTIVE: To evaluate the performance of a deep learning (DL)-based radiomics strategy on contrast-enhanced computed tomography (CT) to predict microvascular invasion (MVI) status and clinical outcomes, recurrence-free survival (RFS) and overall survival (OS) in patients with early stage hepatocellular carcinoma (HCC) receiving surgical resection.

Authors

  • Yuhan Yang
    West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China. Electronic address: yyh_1023@163.com.
  • Yin Zhou
    West China Hospital, Sichuan University, Guoxue Road 37, Chengdu, 610041, China. Electronic address: 653508203@qq.com.
  • Chen Zhou
    West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China. Electronic address: 13258389785@163.com.
  • Xuelei Ma

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