MRI-Based Machine Learning Approach Versus Radiologist MRI Reading for the Detection of Prostate Cancer, The PRIMER Trial
Public ClinicalTrials.gov record NCT07162194. Field values are reproduced from the official study page; the official ClinicalTrials.gov record remains the source of truth for eligibility, enrollment, and contact information.
Data is sourced from official ClinicalTrials.gov public API records. Always review the official ClinicalTrials.gov record for the latest information.
Official title
PRIMER (Prostate MRI With Machine LEarning vs. Radiologist) A Novel MRI-Based Machine Learning Approach vs Radiologist MRI Reading for Targeted Prostate Biopsy: A Non-Inferiority, Within-Person Randomized Controlled Trial for Prostate Cancer Detection
Brief summary
Reproduced verbatim from the official ClinicalTrials.gov record. Not medical advice.
This clinical trial studies how well a magnetic resonance imaging (MRI)-based machine learning approach (i.e., artificial intelligence \[AI\]) works as compared to radiologist MRI readings in detecting prostate cancer. One of the current methods used to help diagnose possible prostate cancer is performing a prostate MRI. An MRI uses a magnetic field to take pictures of the body. The MRI images are examined by a radiologist. If a suspicious area is seen in the MRI, the radiologist assigns it a PIRADS score. This stands for Prostate Imaging Reporting and Data System. The PIRADS score is used to report how likely it is that a suspicious area in the prostate is cancer. The AI system has been developed also to be able to analyze prostate MRI images and detect suspicious areas in the prostate that may be cancer. The AI system's ability to diagnose aggressive prostate cancer may be similar to detection performed by experienced radiologists using the standard PIRADS system of analyzing prostate MRI.
Study identification
- NCT ID
- NCT07162194
- Recruitment status
- Recruiting
- Study type
- Interventional
- Phase
- Not applicable
- Enrollment
- 130 participants
Conditions and interventions
Conditions
Interventions
- Targeted Prostate Biopsy Procedure
- Prostate Imaging Reporting & Data System Diagnostic Test
- Deep Learning Artificial Intelligence Diagnostic Test
- Green Learning Artificial Intelligence Diagnostic Test
- Radical Prostatectomy Procedure
Procedure · Diagnostic Test
Eligibility (public fields only)
- Age range
- 20 Years and older
- Sex
- Male
- Healthy volunteers
- Healthy volunteers not accepted
This page does not interpret eligibility. Detailed inclusion and exclusion criteria are on the official ClinicalTrials.gov record.
Study timeline
- Start date
- Sep 18, 2025
- Primary completion
- Oct 14, 2027
- Completion
- Oct 14, 2028
- Last update posted
- Aug 31, 2026
2025 – 2028
United States locations
- U.S. sites
- 1
- U.S. states
- 1
- U.S. cities
- 1
| Facility | City | State | ZIP | Site status |
|---|---|---|---|---|
| USC / Norris Comprehensive Cancer Center | Los Angeles | California | 90033 | Recruiting |
Site contact phone numbers, emails, and investigator names are intentionally not displayed here. Open the official ClinicalTrials.gov record for site contact information.
About this trial record page
- What this page shows
- Public field values for ClinicalTrials.gov record NCT07162194, including study identification, conditions, interventions, eligibility (age, sex, healthy volunteer), timeline, and U.S. site list.
- What this page does not do
- No medical advice, eligibility judgments, treatment recommendations, study quality scoring, or AI-generated medical summaries. No site contact phone numbers, emails, or investigator names.
- Where the data comes from
- Sourced from the official ClinicalTrials.gov public API. The official record is the source of truth.
- Last refresh
- Last update posted Aug 31, 2026 · Synced Sep 3, 2026
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Open the official record
The complete protocol, eligibility criteria, and contact information for NCT07162194 live on ClinicalTrials.gov.