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

Status: Recruiting
Location: See location...
Study Type: Observational
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
Participation Requirements
Sex: Male
Healthy Volunteers: f
View:

• The interval between prostate MRI and biopsy within 3 months

• Integrity of related data

Locations
Other Locations
China
Peking University First Hospital
RECRUITING
Beijing
Contact Information
Primary
Yi LIU
liuyipkuhsc@163.com
+8613611035261
Backup
Yi LIU
liuyipkuhsc@163.com
Time Frame
Start Date: 2024-01-01
Estimated Completion Date: 2029-12-31
Participants
Target number of participants: 3000
Treatments
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.
Related Therapeutic Areas
Sponsors
Leads: Peking University First Hospital

This content was sourced from clinicaltrials.gov