Multimodal imaging deep learning model for predicting extraprostatic extension in prostate cancer using MpMRI and 18 F-PSMA-PET/CT.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
Published Date: Aug 19, 2025

Abstract

OBJECTIVE: This study aimed to construct a multimodal imaging deep learning (DL) model integrating mpMRI and F-PSMA-PET/CT for the prediction of extraprostatic extension (EPE) in prostate cancer, and to assess its effectiveness in enhancing the diagnostic accuracy of radiologists.

Authors

  • Fei Yao
    The Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
  • Heng Lin
    The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
  • Ying-Nan Xue
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, No. 1 of Xuefubei Road, Ouhai District, Wenzhou, 325000, Zhejiang Province, China.
  • Yuan-Di Zhuang
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, No. 1 of Xuefubei Road, Ouhai District, Wenzhou, 325000, Zhejiang Province, China.
  • Shu-Ying Bian
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, No. 1 of Xuefubei Road, Ouhai District, Wenzhou, 325000, Zhejiang Province, China.
  • Ya-Yun Zhang
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, No. 1 of Xuefubei Road, Ouhai District, Wenzhou, 325000, Zhejiang Province, China.
  • Yun-Jun Yang
    Department of Radiology, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China.
  • Ke-Hua Pan
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, No. 1 of Xuefubei Road, Ouhai District, Wenzhou, 325000, Zhejiang Province, China. pankehuapan@126.com.

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