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

PRIMARY OBJECTIVE: I. To determine the non-inferiority of targeted biopsy according to Green Learning (GL) AI over Prostate Imaging Reporting \& Data System (PIRADS). SECONDARY OBJECTIVES: I. To determine the clinically significant prostate cancer (CSPCa) detection rate on Deep Learning (DL) AI-targeted biopsy. II. To determine the patient-level diagnostic performance of GL AI, Deep Learning (DL) AI and PIRADS for clinically significant prostate cancer (CSPCa) detection. III. To assess Targeted biopsy core characteristics. IV. To evaluate the predictors for patient-level CSPCa detection. V. To assess the spatial correlation of CSPCa distribution on radical prostatectomy (RP) specimens and region of interest (ROI) generated by GL AI and PIRADS. OUTLINE: Patients undergoing prostate biopsy per standard of care (SOC) are assigned to Group 1. Patients who underwent a prostate biopsy followed by a radical prostatectomy within 6 months, as well as patients only undergoing a radical prostatectomy are assigned to Group 2. GROUP 1: Patients are randomized to 1 of 6 arms. ARM I: Patients undergo MRI/transrectal ultrasound (TRUS) followed by a targeted prostate biopsy using PIRADS on study. Patients then undergo a 2nd MRI/TRUS followed by a targeted prostate biopsy based on GL AI predictions. Patients then undergo a 3rd MRI/TRUS followed by a targeted biopsy based on DL AI predictions. Finally, patients undergo up to 12 additional prostate biopsies per SOC. ARM II: Patients undergo MRI/TRUS followed by a targeted prostate biopsy using PIRADS. Patients then undergo a 2nd MRI/TRUS followed by a targeted prostate biopsy based on DL AI predictions. Patients then undergo a 3rd MRI/TRUS followed by a targeted biopsy based on GL AI predictions. Finally, patients undergo up to 12 additional prostate biopsies per SOC. ARM III: Patients undergo MRI/TRUS followed by a targeted prostate biopsy using GL AI predictions. Patients then undergo a 2nd MRI/TRUS followed by a targeted prostate biopsy using PIRADS. Patients then undergo a 3rd MRI/TRUS followed by a targeted biopsy based on DL AI predictions. Finally, patients undergo up to 12 additional prostate biopsies per SOC. ARM IV: Patients undergo MRI/TRUS followed by a targeted prostate biopsy using GL AI predictions. Patients then undergo a 2nd MRI/TRUS followed by a targeted prostate biopsy based on DL AI predictions. Patients then undergo a 3rd MRI/TRUS followed by a targeted biopsy using PIRADS. Finally, patients undergo up to 12 additional prostate biopsies per SOC. ARM V: Patients undergo MRI/TRUS followed by a targeted prostate biopsy using DL AI predictions. Patients then undergo a 2nd MRI/TRUS followed by a targeted prostate biopsy based on GL AI predictions. Patients then undergo a 3rd MRI/TRUS followed by a targeted biopsy using PIRADS. Finally, patients undergo up to 12 additional prostate biopsies per SOC. ARM VI: Patients undergo MRI/TRUS followed by a targeted prostate biopsy using DL AI predictions. Patients then undergo a 2nd MRI/TRUS followed by a targeted prostate biopsy using PIRADS. Patients then undergo a 3rd MRI/TRUS followed by a targeted biopsy based on GL AI predictions. Finally, patients undergo up to 12 additional prostate biopsies per SOC. GROUP 2: Patients have their removed prostate evaluated using a special mold on study. Prostate tissue is mapped and compared with the prostate cancer prediction on MRI generated by radiologists and AI reports. After completion of study intervention, patients are followed up at 10 days and at 3 months.