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

NCT06842264 | Recruiting

• 1 other identifier: prostatemodel19-29
• Study Type: observational
• Target: 3,000
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Prostate Cancer

Keywords

clinically-significant prostate cancer; artificial intelligence; magnetic resonance imaging; predictive model

Outcome Measures

Primary Outcomes (1)

• Biopsy pathology results

  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

Study Arms (1)

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.

Eligibility Criteria

• Sex: male
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• 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.

You may qualify if:

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

You may not qualify if:

• 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

Sponsors & Collaborators

• Peking University First Hospital: lead

Study Sites (1)

Peking University First Hospital

Beijing, 100034, China

RECRUITING

MeSH Terms

Conditions

Prostatic Neoplasms

Condition Hierarchy (Ancestors)

Genital Neoplasms, Male; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Genital Diseases, Male; Genital Diseases; Urogenital Diseases; Prostatic Diseases; Male Urogenital Diseases

Study Officials

• Yi LIU

  Dept. of Urology, Peking University First Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Yi LIU

CONTACT

+8613611035261; liuyipkuhsc@163.com

Yi LIU

CONTACT

liuyipkuhsc@163.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: February 11, 2025
• First Posted: February 24, 2025
• Study Start: January 1, 2024
• Primary Completion (Estimated): December 31, 2029
• Study Completion (Estimated): December 31, 2029
• Last Updated: January 29, 2026

Record last verified: 2025-02

Locations

CN (1)