A machine learning radiomics based on enhanced computed tomography to predict neoadjuvant immunotherapy for resectable esophageal squamous cell carcinoma.

Journal: Frontiers in immunology
Published Date: Jun 14, 2024

Abstract

BACKGROUND: Patients with resectable esophageal squamous cell carcinoma (ESCC) receiving neoadjuvant immunotherapy (NIT) display variable treatment responses. The purpose of this study is to establish and validate a radiomics based on enhanced computed tomography (CT) and combined with clinical data to predict the major pathological response to NIT in ESCC patients.

Authors

  • Jia-Ling Wang
    Department of Biotherapy, Cancer Center, West China Hospital of Sichuan University, Chengdu, China.
  • Lian-Sha Tang
    Department of Biotherapy, Cancer Center, West China Hospital of Sichuan University, Chengdu, China.
  • Xia Zhong
    Pattern Recognition Laboratory, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Martensstr. 3, 91058, Erlangen, Germany. xia.zhong@fau.de.
  • Yi Wang
    Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
  • Yu-Jie Feng
    West China School of Medicine, Sichuan University, Chengdu, China.
  • Yun Zhang
    Biology Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China.
  • Ji-Yan Liu
    Department of Biotherapy, Cancer Center, West China Hospital of Sichuan University, Chengdu, China.

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