EligibleTrials

MRI-Based Machine Learning Approach Versus Radiologist MRI Reading for the Detection of Prostate Cancer, The PRIMER Trial

Recruiting · NCT07162194 · Interventional (participants receive a specific treatment)

View the official record on ClinicalTrials.gov →
Prostate cancer

Interventions studied

Deep Learning Artificial IntelligenceGreen Learning Artificial IntelligenceProstate Imaging Reporting & Data SystemRadical ProstatectomyTargeted Prostate Biopsy

What this trial is about

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.

Who can take part

Age range
20 Years and older
Sex
Male
Healthy volunteers
No - a diagnosis or condition is required
Phase
Not applicable (e.g. observational or device study)
Study type
Interventional (participants receive a specific treatment)

Inclusion criteria

Exclusion criteria

Where it is running

1 location listed across 1 US state.

Read the full protocol, contacts and eligibility on ClinicalTrials.gov →

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