Enhancing brain metastasis prediction in non-small cell lung cancer: a deep learning-based segmentation and CT radiomics-based ensemble learning model.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
Published Date: Jan 2, 2024

Abstract

BACKGROUND: Brain metastasis (BM) is most common in non-small cell lung cancer (NSCLC) patients. This study aims to enhance BM risk prediction within three years for advanced NSCLC patients by using a deep learning-based segmentation and computed tomography (CT) radiomics-based ensemble learning model.

Authors

  • Jing Gong
    Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai, 200032, China.
  • Ting Wang
    CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
  • Zezhou Wang
    Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
  • Xiao Chu
    Ping An Healthcare Technology, Shanghai, China.
  • Tingdan Hu
    Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai, 200032, China.
  • Menglei Li
    School of Mechanical Science and Engineering, Huazhong University of Science & Technology, Wuhan 430074, China.
  • Weijun Peng
    Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
  • Feng Feng
    Department of Microbiology, Boston University, Boston, MA 02118, USA.
  • Tong Tong
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Yajia Gu
    Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China. cjr.guyajia@vip.163.com.

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