The Development and Validation of MRI-AI-based Predictive Models for csPCa

January 27, 2026 updated by: Peking University First Hospital
This study retrospectively included patients who underwent prostate magnetic resonance imaging (MRI) and subsequent ultrasound-guided prostate biopsy at Peking University First Hospital from January 2019 to December 2023, and prospectively enrolls patients from January 2024 to December 2029. Clinical information such as age, PSA levels, PI-RADS scores, and digital rectal examination findings are collected. A well-performing artificial intelligence model is employed to measure prostate volume, transitional zone volume, and lesion volume using MRI images. Furthermore, prostate-specific antigen density (PSAD), transitional zone-based prostate-specific antigen density (TZ-PSAD) and lesion-based prostate-specific antigen density (lesion-PSAD) are calculated using prostate volume, transitional zone volume and lesion volume. Utilizing the aforementioned data, machine learning predictive models for clinically-significant prostate cancer (csPCa) are developed and validated.

Study Overview

Status

Recruiting

Conditions

Detailed Description

This study retrospectively included patients who underwent prostate magnetic resonance imaging (MRI) and subsequent ultrasound-guided prostate biopsy at Peking University First Hospital from January 2019 to December 2023, and prospectively enrolls patients from January 2024 to December 2029. Clinical information such as age, PSA levels, PI-RADS scores, and digital rectal examination findings are collected. A well-performing artificial intelligence model is employed to measure prostate volume, transitional zone volume, and lesion volume using MRI images. Furthermore, prostate-specific antigen density (PSAD), transitional zone-based prostate-specific antigen density (TZ-PSAD) and lesion-based prostate-specific antigen density (lesion-PSAD) are calculated using prostate volume, transitional zone volume and lesion volume. Utilizing the aforementioned data, machine learning predictive models for clinically-significant prostate cancer (csPCa) are developed and validated

Study Type

Observational

Enrollment (Estimated)

3000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • China
      • Beijing, China, 100034
        • Recruiting
        • Peking University First Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Patients who underwent prostate magnetic resonance imaging (MRI) at Peking University First Hospital between January 2024 and December 2029, followed by an ultrasound-guided prostate biopsy.

Description

Inclusion Criteria:

  • The interval between prostate MRI and biopsy within 3 months
  • Integrity of related data

Exclusion Criteria:

  • PSA less than 50ng/ml
  • Any treatment for PCa prior to either MRI or biopsy, including radical prostatectomy, radiotherapy, chemotherapy, and endocrine therapy
  • Previous history of surgical treatment or 5α-reductase inhibitor therapy for benign prostatic hyperplasia
  • Subjects undergoing MRI with an indwelling urinary catheter or suprapubic catheter
  • Inadequate quality of MRI images

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
cohort 1
Cohort 1 comprises patients who underwent prostate magnetic resonance imaging (MRI) at Peking University First Hospital between January 2024 and December 2029, followed by an ultrasound-guided prostate biopsy.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Biopsy pathology results
Time Frame: 1week after biopsy
The pathology report will include the ISUP grade; if it is greater than or equal to 2, it is considered csPCa (clinically significant prostate cancer), otherwise, it is classified as non-csPCa.
1week after biopsy

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Peking University First Hospital

Investigators

  • Principal Investigator: Yi LIU, Dept. of Urology, Peking University First Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2024

Primary Completion (Estimated)

December 31, 2029

Study Completion (Estimated)

December 31, 2029

Study Registration Dates

First Submitted

February 11, 2025

First Submitted That Met QC Criteria

February 18, 2025

First Posted (Actual)

February 24, 2025

Study Record Updates

Last Update Posted (Actual)

January 29, 2026

Last Update Submitted That Met QC Criteria

January 27, 2026

Last Verified

February 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • prostatemodel19-29

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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