MedTrace Logo

Development and Validation of a Non-Invasive AI Diagnostic Model for Prostate Cancer Using Multiparametric MRI and PSMA PET/CT

NCT07690306 · Status: ENROLLING_BY_INVITATION · Type: OBSERVATIONAL · Enrollment: 1500

Last updated 2026-07-08

No results posted yet for this study

Summary

Prostate cancer is one of the most common malignancies in men. Currently, due to the limited diagnostic accuracy of existing imaging tests, there is a risk of missed diagnosis or unnecessary prostate biopsy. This study aims to develop and validate a non-invasive artificial intelligence (AI) diagnostic model using two advanced imaging techniques: multiparametric MRI (mpMRI) and PSMA PET/CT. By integrating information from both imaging modalities, the AI model is expected to improve the diagnostic accuracy of prostate cancer, reduce unnecessary biopsies, and assist physicians in making better clinical decisions. This is a retrospective, multicenter study that plans to collect imaging and pathology data from approximately 1,000 to 1,500 patients across six major hospitals in China. The diagnostic performance of the model will be evaluated, including its ability to identify clinically significant prostate cancer and its value in assisting diagnosis in patients with PSA levels in the gray zone (4-20 ng/mL).

Conditions

  • Prostate Cancer (Diagnosis)

Sponsors & Collaborators

  • Qilu Hospital of Shandong University

    collaborator OTHER

  • Chinese PLA General Hospital

    collaborator OTHER

  • The First Affiliated Hospital of Guangzhou Medical University

    collaborator OTHER

  • RenJi Hospital

    collaborator OTHER

  • Xiangya Hospital of Central South University

    lead OTHER

Eligibility

Min Age
18 Years
Sex
MALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-01-13
Primary Completion
2026-09-30
Completion
2026-12-31

Countries

  • China

Study Locations

More Related Trials

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 NCT07690306 on ClinicalTrials.gov