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Multimodal Imaging and Digital Pathology for Prostate Cancer Prediction
Sponsor: Guangxi Medical University
Summary
This is a multicenter observational study. A deep learning model integrated with multimodal imaging and digital pathology spatial registration is built based on preoperative multiparametric magnetic resonance imaging, transrectal ultrasound and postoperative digital pathological whole slide images. The study is designed to achieve accurate prediction of clinically significant prostate cancer and non-invasive risk stratification. Unnecessary prostate biopsy and overdiagnosis can be reduced to support the optimization of clinical diagnosis and treatment strategies.
Official title: A Multicenter Study of a Deep Learning Model Based on Spatial Registration of Multimodal Imaging and Digital Pathology for Predicting Clinically Significant Prostate Cancer
Key Details
Gender
MALE
Age Range
40 Years - 90 Years
Study Type
OBSERVATIONAL
Enrollment
3000
Start Date
2025-05-30
Completion Date
2030-12-31
Last Updated
2026-05-29
Healthy Volunteers
No
Interventions
No Intervention: Observational Cohort
This is an observational study. No new treatment, drug, device, or procedure is being administered to participants. Only standard-of-care clinical data, imaging, and pathology records are collected and analyzed.
Locations (1)
Liuzhou People's Hospital Affiliated to Guangxi Medical University
Liuzhou, Guangxi, China