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Recruiting NCT06842264

NCT06842264 The Development and Validation of MRI-AI-based Predictive Models for csPCa

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Clinical Trial Summary
NCT ID NCT06842264
Status Recruiting
Phase
Sponsor Peking University First Hospital
Condition Prostate Cancer
Study Type OBSERVATIONAL
Enrollment 3,000 participants
Start Date 2024-01-01
Primary Completion 2029-12-31

Eligibility & Interventions

Sex Male only
Min Age N/A
Max Age N/A
Study Type OBSERVATIONAL

Eligibility Fast-Check

Enter your details for a quick preliminary check. This does not replace medical advice.

What to Expect as a Participant

This is an observational study. You will not receive an experimental treatment; researchers will collect data based on your existing condition or standard treatment.

This trial targets 3,000 participants in total. It began in 2024-01-01 with a primary completion date of 2029-12-31.

⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.

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.

Eligibility Criteria

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

Contact & Investigator

Central Contact

Yi LIU

✉ liuyipkuhsc@163.com

📞 +8613611035261

Principal Investigator

Yi LIU

PRINCIPAL INVESTIGATOR

Dept. of Urology, Peking University First Hospital

Frequently Asked Questions

Who can join the NCT06842264 clinical trial?

This trial is open to male participants only, studying Prostate Cancer. Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.

Is NCT06842264 currently recruiting?

Yes, NCT06842264 is actively recruiting participants. Contact the research team at liuyipkuhsc@163.com for enrollment information.

Where is the NCT06842264 trial being conducted?

This trial is being conducted at Beijing, China.

Who is sponsoring the NCT06842264 clinical trial?

NCT06842264 is sponsored by Peking University First Hospital. The principal investigator is Yi LIU at Dept. of Urology, Peking University First Hospital. The trial plans to enroll 3,000 participants.

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ClinicalMetric — Independent clinical trial intelligence platform. Not affiliated with NIH, ClinicalTrials.gov, the U.S. FDA, or any pharmaceutical company, hospital, or clinical research organization. Trial data is sourced from ClinicalTrials.gov for informational purposes only and does not constitute medical advice. Do not make any treatment, enrollment, or health decisions based solely on information found here — always consult a qualified healthcare professional. Full Disclaimer  ·  Last Reviewed: September 2026  ·  Data Methodology