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

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

Abstract Objective This study aimed to construct a multimodal imaging deep learning (DL) model integrating mpMRI and 18F-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. Methods...

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Bibliographic Details
Main Authors: Fei Yao, Heng Lin, Ying-Nan Xue, Yuan-Di Zhuang, Shu-Ying Bian, Ya-Yun Zhang, Yun-Jun Yang, Ke-Hua Pan
Format: Article
Language:English
Published: BMC 2025-08-01
Series:Cancer Imaging
Subjects:
Deep learning
Extraprostatic extension
Magnetic resonance imaging
Multimodal imaging
Positron emission tomography
Prostate cancer
Online Access:https://doi.org/10.1186/s40644-025-00927-4
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https://doi.org/10.1186/s40644-025-00927-4

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