Prediction of Tumor Budding Grading in Rectal Cancer Using a Multiparametric MRI Radiomics Combined with a 3D Vision Transformer Deep Learning Approach.

Journal: Academic radiology
Published Date: Apr 16, 2025

Abstract

RATIONALE AND OBJECTIVES: The objective is to assess the effectiveness of a multiparametric MRI radiomics strategy combined with a 3D Vision Transformer (ViT) deep learning (DL) model in predicting tumor budding (TB) grading in individuals diagnosed with rectal cancer (RC).

Authors

  • Zhanhong Liu
    CT/MRI Department, Beijing Anzhen Nanchong Hospital, Capital Medical University & Nanchong Central Hospital, No.97, People's South Road, Nanchong, China.
  • Hao Yang
    College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China.
  • Lin Nie
    CT/MRI Department, Beijing Anzhen Nanchong Hospital, Capital Medical University & Nanchong Central Hospital, No.97, People's South Road, Nanchong, China.
  • Peng Xian
    CT/MRI Department, Beijing Anzhen Nanchong Hospital, Capital Medical University & Nanchong Central Hospital, No.97, People's South Road, Nanchong, China.
  • Junfan Chen
  • Jianru Huang
    CT/MRI Department, Beijing Anzhen Nanchong Hospital, Capital Medical University & Nanchong Central Hospital, No.97, People's South Road, Nanchong, China.
  • Zhengkang Yao
    CT/MRI Department, Beijing Anzhen Nanchong Hospital, Capital Medical University & Nanchong Central Hospital, No.97, People's South Road, Nanchong, China.
  • Tianqi Yuan
    CT/MRI Department, Beijing Anzhen Nanchong Hospital, Capital Medical University & Nanchong Central Hospital, No.97, People's South Road, Nanchong, China.

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