Application and prospect of artificial intelligence in diagnostic imaging of prostate cancer

Xiaoxiao Wang; Shan Zhong; Kun Fang; Yangchun Du; Jianlin Huang

doi:10.1038/s41746-026-02354-6

Application and prospect of artificial intelligence in diagnostic imaging of prostate cancer

NPJ Digit Med. 2026 Feb 5;9(1):168. doi: 10.1038/s41746-026-02354-6.

Authors

Xiaoxiao Wang^#¹, Shan Zhong^#², Kun Fang^#², Yangchun Du³, Jianlin Huang⁴

Affiliations

¹ Department of Urology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
² Department of Organ Transplantation, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
³ Department of Organ Transplantation, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China. duyangchun@med.uestc.edu.cn.
⁴ Department of Urology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China. huangjianlin@med.uestc.edu.cn.

^# Contributed equally.

Abstract

Prostate cancer is a leading cause of male cancer mortality, and early, accurate diagnosis is critical. Artificial intelligence (AI), including machine learning, deep learning, and radiomics, enhances detection, characterization, and treatment assessment across TRUS, mp-MRI, and PSMA PET/CT. AI models achieve high accuracy, often matching experts, improving small-lesion detection, and supporting risk stratification. Challenges remain in data quality, generalization, clinical integration, and ethics, with future prospects in multi-omics, explainable AI, and workflow-embedded decision support.

Publication types

Review