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Advances in artificial intelligence research in prostate cancer
YE Mengmeng  ZHOU Taohu  GE Yanming  FAN Li 

Cite this article as: YE M M, ZHOU T H, GE Y M, et al. Advances in artificial intelligence research in prostate cancer[J]. Chin J Magn Reson Imaging, 2025, 16(7): 192-201. DOI:10.12015/issn.1674-8034.2025.07.031.


[Abstract] Prostate cancer (PCa) has the second highest incidence of malignant tumors among men worldwide, and its precise diagnosis and treatment decision-making urgently needs more accurate auxiliary tools. The rise of artificial intelligence (AI) technology has brought unprecedented opportunities for early diagnosis and precision treatment of PCa. This paper provides a systematic review of the current state of AI in three core areas of prostate cancer: (1) Diagnosis and prognosis assessment, we review the current status of the application of traditional PCa diagnostic tools and focus on the progress of the application of AI in multimodal imaging technology; (2) Molecular mechanism research, we explore the application model of AI in genomics, proteomics and other high-throughput genomics data, revealing key molecular mechanisms of disease development; (3) Treatment decision optimization, we illustrate the innovative practice of AI in surgical planning and intraoperative navigation, personalized design of targeted treatment protocols, and postoperative dynamic monitoring, highlighting the potential value of AI in improving outcomes and reducing and minimizing the risk of complications. This paper describes clinical-grade PCa-specific AI systems and analyzes their advantages in improving the efficiency and accuracy of diagnosis and treatment. Aiming at the challenges faced by AI in PCa applications, such as single data source, insufficient model generalization ability, "black box" characteristics, and lack of multimodal data standardization, future research should focus on building cross-center, multimodal standardized databases and introducing privacy computing technology applications such as federated learning; developing interpretable AI frameworks to enhance clinical trust; and continuously optimizing algorithmic performance to improve the utility and reliability of models. The purpose of this review is to summarize the latest advances and challenges in the application of AI in the field of PCa, and to provide guidance for future research directions in order to promote the deep integration of AI technology with PCa clinical research and practice.
[Keywords] prostate cancer；artificial intelligence；magnetic resonance imaging；image segmentation；personalized treatment

YE Mengmeng1, 2   ZHOU Taohu2   GE Yanming1, 3   FAN Li2*  

1 Shandong Second Medical University, Weifang 261000, China

2 Department of Radiology, Changzheng Hospital, Naval Medical University, Shanghai 200003, China

3 Medical Imaging Center, Affiliated Hospital of Shandong Second Medical University, Weifang 261000, China

Corresponding author: FAN L, E-mail: fanli0930@163.com

Conflicts of interest   None.

Received  2024-12-18
Accepted  2025-05-07
DOI: 10.12015/issn.1674-8034.2025.07.031
Cite this article as: YE M M, ZHOU T H, GE Y M, et al. Advances in artificial intelligence research in prostate cancer[J]. Chin J Magn Reson Imaging, 2025, 16(7): 192-201. DOI:10.12015/issn.1674-8034.2025.07.031.

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