Computed tomography-based deep learning radiomics model for preoperative prediction of tumor immune microenvironment in colorectal cancer.

Journal: World journal of gastrointestinal oncology
Published Date: May 15, 2025

Abstract

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer-related death globally, with the tumor immune microenvironment (TIME) influencing prognosis and immunotherapy response. Current TIME evaluation relies on invasive biopsies, limiting its clinical application. This study hypothesized that computed tomography (CT)-based deep learning (DL) radiomics models can non-invasively predict key TIME biomarkers: Tumor-stroma ratio (TSR), tumor-infiltrating lymphocytes (TILs), and immune score (IS).

Authors

  • Chuan Zhou
    Department of Radiology, The University of Michigan, Ann Arbor, MI, 48109, USA.
  • Yun-Feng Zhang
    The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, China.
  • Zhi-Jun Yang
    The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.
  • Yu-Qian Huang
    Center of Medical Cosmetology, Chengdu Second People's Hospital, Chengdu 610017, Sichuan Province, China.
  • Ming-Xu Da
    The First Clinical Medical College of Lanzhou University, Lanzhou University, Lanzhou 730000, Gansu Province, China.

Keywords

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