Comparison of clinical, radiomics, deep learning, and fusion models for predicting early recurrence in locally advanced rectal cancer based on multiparametric MRI: a multicenter study.

Journal: European journal of radiology
Published Date: Aug 1, 2025

Abstract

OBJECTIVE: Predicting early recurrence (ER) in locally advanced rectal cancer (LARC) is critical for clinical decision-making. This study aimed at comparing clinical, deep learning (DL), radiomics, and two fusion models for ER prediction based on multiparametric MRI.

Authors

  • Zhiheng Li
    College of Computer Science and Technology, Dalian University of Technology, Dalian, China.
  • Yangyang Qin
    Department of Radiology, The First Affiliated Hospital of Ningbo University, Ningbo 315020 Zhejiang, China.
  • Xiaoqing Liao
    Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou 515041 Guangzhou, China.
  • Enqi Wang
    Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou 515041 Guangzhou, China.
  • Rongzhi Cai
    Department of Radiology, Cancer Hospital of Shantou University Medical College, Shantou 515041 Guangzhou, China.
  • Yuning Pan
    Department of Radiology, Ningbo First Hospital, Ningbo, Zhejiang, China.
  • Dandan Wang
    Department of Traditional Chinese Medicine Orthopedics and Traumatology, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
  • Yan Lin

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