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

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. 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.

Description

Eligibility

Age range

20+ years

Sex

Male

Healthy volunteers

No

Interventions

• Procedure
  Targeted Prostate Biopsy

  Undergo targeted prostate biopsy

• Diagnostic Test
  Prostate Imaging Reporting & Data System

  PIRADS Assessment

• Diagnostic Test
  Deep Learning Artificial Intelligence

  Deep Learning (DL) AI predictions

• Diagnostic Test
  Green Learning Artificial Intelligence

  Green Learning (GL) AI predictions

• Procedure
  Radical Prostatectomy

  Undergo RP

Location