Deep learning model based on endoscopic images predicting treatment response in locally advanced rectal cancer undergo neoadjuvant chemoradiotherapy: a multicenter study.

Journal: Journal of cancer research and clinical oncology
PMID: 39001926

Abstract

PURPOSE: Neoadjuvant chemoradiotherapy has been the standard practice for patients with locally advanced rectal cancer. However, the treatment response varies greatly among individuals, how to select the optimal candidates for neoadjuvant chemoradiotherapy is crucial. This study aimed to develop an endoscopic image-based deep learning model for predicting the response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

Authors

  • Junhao Zhang
  • Ruiqing Liu
    Department of Otorhinolaryngology, Kunming City Women and Children Hospital, Kunming, China.
  • Xujian Wang
  • Shiwei Zhang
    Department of Stomatology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, China.
  • Lizhi Shao
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Computer Science and Engineering, Southeast University, Nanjing, China.
  • Junheng Liu
    Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Jiahui Zhao
    Department of Gastroenterology, Endoscopy Center, The First Hospital of Jilin University, Changchun, China.
  • Quan Wang
    Laboratory of Surgical Oncology, Peking University People's Hospital, Peking University, Beijing, China.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Yun Lu
    Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.

Keywords

External Resources

Popular Topics
Recent Journals