MRI-Based Machine Learning Approach Versus Radiologist MRI Reading for the Detection of Prostate Cancer, The PRIMER Trial
NCT07162194
This study is recruiting at 1 US site in 1 state, according to its ClinicalTrials.gov record last updated .
Summary
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.
Shortened from the sponsor's brief summary. View official record on ClinicalTrials.gov
Conditions studied
- Prostate Carcinoma
Eligibility basics and study details
- Study type
- Interventional
- Phase
- Not applicable
- Ages
- 20 years and older
- Sex
- Male
- Healthy volunteers
- Not accepted
- Sponsor
- University of Southern California
- Last updated on ClinicalTrials.gov
- September 1, 2026
These are the basic criteria only. The full inclusion and exclusion criteria are on the official record, and the study team decides who can take part.
US recruiting sites
California · 1
- USC / Norris Comprehensive Cancer Center · Los Angeles, CA
Source: ClinicalTrials.gov, data processed . Recruiting US sites filtered by distance and site status; summaries shortened.