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Multimodal Imaging and Digital Pathology for Prostate Cancer Prediction

NCT07614256 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 3000

Last updated 2026-05-29

No results posted yet for this study

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.

Conditions

  • Prostate Cancer (Diagnosis)
  • Clinically Significant Prostate Cancer

Interventions

OTHER

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.

Sponsors & Collaborators

  • Guangxi Medical University

    lead OTHER

Principal Investigators

  • Fubo Wang, MD · Guangxi Medical University

Eligibility

Min Age
40 Years
Max Age
90 Years
Sex
MALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-05-30
Primary Completion
2030-06-30
Completion
2030-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07614256 on ClinicalTrials.gov