Fully Automated Online Adaptive Radiation Therapy Decision-Making for Cervical Cancer Using Artificial Intelligence.

Journal: International journal of radiation oncology, biology, physics
Published Date: Apr 17, 2025

Abstract

BACKGROUND: Interfraction variations during radiation therapy pose a challenge for patients with cervical cancer, highlighting the benefits of online adaptive radiation therapy (oART). However, adaptation decisions rely on subjective image reviews by physicians, leading to high interobserver variability and inefficiency. This study explores the feasibility of using artificial intelligence for decision-making in oART.

Authors

  • Shuai Sun
    Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
  • Xinyue Gong
    Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China; Eight-Year Program of Clinical Medicine, Peking Union Medical College, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China.
  • Songyang Cheng
    Department of Computer Science, University of Wisconsin-Madison, Madison, WI, USA.
  • Ran Cao
    Radiotherapy Business Unit, AP-Application, Shanghai United Imaging Healthcare Co., Ltd, Shanghai, China.
  • Shumeng He
    Intelligent Radiation Treatment Laboratory, United Imaging Research Institute of Intelligent Imaging, Beijing, China.
  • Yongguang Liang
    Department of Radiotherapy, Peking Union Medical College Hospital, Beijing, 100730, China.
  • Bo Yang
    Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China.
  • Jie Qiu
    Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. Electronic address: qiujie@pumch.cn.
  • Fuquan Zhang
    Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China.
  • Ke Hu
    Medical College, Hunan University of Medicine, Huaihua 418000, China.

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