Predicting overall survival and prophylactic cranial irradiation benefit in small-cell lung cancer with CT-based deep learning: A retrospective multicenter study.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PMID: 38479441

Abstract

BACKGROUND AND PURPOSE: To develop a computed tomography (CT)-based deep learning model to predict overall survival (OS) among small-cell lung cancer (SCLC) patients and identify patients who could benefit from prophylactic cranial irradiation (PCI) based on OS signature risk stratification.

Authors

  • Xiaomin Zheng
    Department of Radiation and Medical Oncology, The 1st Affiliated Hospital of Wenzhou Medical University, No.2 Fuxue Lane, Wenzhou, 325000, People's Republic of China.
  • Kaicai Liu
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230031, China; Department of Radiology, The First Affiliated Hospital of University of Science and Technology of China, Hefei 230001, China.
  • Na Shen
    Hong Kong Shue Yan University, Hong Kong, China.
  • Yankun Gao
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
  • Chao Zhu
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
  • Cuiping Li
  • Chang Rong
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230031, China.
  • Shuai Li
    School of Molecular Biosciences, Center for Reproductive Biology, College of Veterinary Medicine, Washington State University.
  • Baoxin Qian
    Huiying Medical Technology, Beijing 100192, China.
  • Jianying Li
    CT Research Center, GE Healthcare China, Beijing 100176, China.
  • Xingwang Wu
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.

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