Artificial intelligence-based model to predict recurrence after local excision in T1 rectal cancer.

Journal: European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Published Date: Feb 20, 2025

Abstract

BACKGROUND: According to current guideline, patients with resected specimens showing high-risk features are recommended additional surgery after local excision (LE) of T1 colorectal cancer, despite the low incidence of recurrence. However, surgical resection in patients with low rectal cancer (RC) is challenging and may compromise anal function, leading to a low quality of life. To reduce unnecessary surgical resection in these patients, we used artificial intelligence (AI) to develop and validate a prediction model for the risk of recurrence after LE.

Authors

  • Jiarui Su
    Department of Urology, Singapore General Hospital, Singapore.
  • Zhiyuan Liu
    State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China.
  • Haiming Li
    Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai, 200032, People's Republic of China.
  • Li Kang
    College of Information Engineering, Shenzhen University, Shenzhen 518060, China. Electronic address: kangli@szu.edu.cn.
  • Kaihong Huang
    Department of Computer Science and Engineering, Southeast University, Nanjing 211189, China.
  • Jiawei Wu
    Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, P. R. China.
  • Han Huang
    School of Software Engineering, South China University of Technology, Guangzhou 510006, China. hhan@scut.edu.cn.
  • Fei Ling
    School of Biology and Biological Engineering, South China University of Technology, Guangzhou, People's Republic of China.
  • Xueqing Yao
    Department of Gastrointestinal Surgery, Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510000, China; The Second School of Clinical Medicine, Southern Medical University, Guangzhou, 510000, China; Department of General Surgery, Guangdong Provincial People's Hospital Ganzhou Hospital (Ganzhou Municipal Hospital), Ganzhou, 341000, China; Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510000, China; School of Medicine, South China University of Technology, Guangzhou, 510006, China. Electronic address: syyaoxueqing@scut.edu.cn.
  • Chengzhi Huang
    Key Laboratory of Luminescent and Real-Time Analytical Chemistry of Ministry of Education, College of Chemistry and Chemical Engineering, Southwest University, Beibei, Chongqing 400715, China; Chongqing Key Laboratory of Biomedical Analysis, Chongqing Science and Technology Commission, College of Pharmaceutical Sciences, Southwest University, Beibei, Chongqing 400715, China.

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