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The Application of Multimodal Artificial Intelligence Systems in Prostate Cancer Diagnosis and Prognosis Analysis
Sponsor: Shanghai Changzheng Hospital
Summary
Prostate-specific antigen (PSA) testing has limited specificity for prostate cancer diagnosis, leading to a high rate of unnecessary biopsies. This multi-center study aims to develop and validate a non-invasive, multi-modal artificial intelligence model that combines cell-free DNA (cfDNA) profiles with multi-parametric MRI (mpMRI). The primary goal is to improve the accuracy of prostate cancer detection and risk stratification, particularly for men with PSA levels in the 4-10 ng/mL "gray zone," thereby providing a robust tool to guide clinical decision-making and reduce avoidable invasive procedures.
Key Details
Gender
MALE
Age Range
18 Years - 80 Years
Study Type
OBSERVATIONAL
Enrollment
1651
Start Date
2024-10-10
Completion Date
2025-07-30
Last Updated
2026-07-23
Healthy Volunteers
Yes
Interventions
Multi-modal artificial intelligence model (BEAM)
Data from mpMRI and cfDNA analysis will be integrated and processed by deep learning. The model's output will be compared against the final pathological diagnosis from the prostate biopsy to evaluate its performance.
Locations (10)
Cancer Hospital, Chinese Academy of Medical Sciences
Beijing, Beijing Municipality, China
The First Affiliated Hospital of Guangzhou Medical University
Guangzhou, Guangdong, China
Jiangsu Provincial People's Hospita
Nanjing, Jiangsu, China
Zhongda Hospital, Southeast University
Nanjing, Jiangsu, China
The First Affiliated Hospital of Soochow University
Suzhou, Jiangsu, China
Northern Jiangsu People's Hospita
Yangzhou, Jiangsu, China
Changhai Hospital
Shanghai, Shanghai Municipality, China
Shanghai Changzheng Hospital
Shanghai, Shanghai Municipality, China
West China Hospital, Sichuan University
Chengdu, Sichuan, China
Ningbo No. 1 Hospita
Ningbo, Zhejiang, China