Development and validation of MRI-based deep learning models for prediction of microsatellite instability in rectal cancer.

Journal: Cancer medicine
PMID: 33963688

Abstract

BACKGROUND: Microsatellite instability (MSI) predetermines responses to adjuvant 5-fluorouracil and immunotherapy in rectal cancer and serves as a prognostic biomarker for clinical outcomes. Our objective was to develop and validate a deep learning model that could preoperatively predict the MSI status of rectal cancer based on magnetic resonance images.

Authors

  • Wei Zhang
    The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Hongkun Yin
    Beijing Infervision Technology Co. Ltd., Beijing, 100025, China.
  • Zixing Huang
    Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province 610000, China.
  • Jian Zhao
    Key Laboratory of Intelligent Rehabilitation and Barrier-Free for the Disabled (Changchun University), Ministry of Education, Changchun University, Changchun 130012, China.
  • Haoyu Zheng
    Department of Radiology, Sichuan Provincial Corps Hospital, Chinese People's Armed Police Forces, Leshan, China.
  • Du He
    Department of Pathology, West China Hospital, Sichuan University, Chengdu, China.
  • Mou Li
    Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
  • Weixiong Tan
    Beijing Infervision Technology Co. Ltd., Beijing, 100025, China.
  • Song Tian
    Infervision, Beijing, China.
  • Bin Song
    Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China.

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