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

University of Southern California

Status: Enrolling

Conditions: Prostate Carcinoma

Treatments: Procedure: Radical Prostatectomy; Procedure: Targeted Prostate Biopsy; Diagnostic Test: Prostate Imaging Reporting & Data System; Diagnostic Test: Green Learning Artificial Intelligence; Diagnostic Test: Deep Learning Artificial Intelligence

Study type: Interventional

Funder types: Other; NIH

Identifiers

NCT07162194

P30CA014089 (U.S. NIH Grant/Contract)

4P-25-1 (Other Identifier)

NCI-2025-03027 (Registry Identifier)

Details and patient eligibility

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.

Full description

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.

Enrollment: 130 estimated patients

Sex: Male

Ages: 20+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• PROSTATE BIOPSY COHORT: Patients undergoing transperineal MRI/TRUS fusion prostate biopsy (PBx) as per standard of care
• PROSTATE BIOPSY COHORT: Patients who underwent or are undergoing 3T multiparametric MRI (T2W, diffusion weighted imaging [DWI], apparent diffusion coefficient [ADC], and dynamic contrast-enhanced [DCE]) within 90 days prior to biopsy
• PROSTATE BIOPSY COHORT: Patients who consented to the study
• RADICAL PROSTATECTOMY COHORT: Patients undergoing radical prostatectomy for primary treatment of prostate cancer as per standard of care
• RADICAL PROSTATECTOMY COHORT: Patients who underwent or are undergoing 3T multiparametric MRI (T2W, DWI, ADC, and DCE) within 180 days prior to radical prostatectomy
• RADICAL PROSTATECTOMY COHORT: Patients who consented to the study

Exclusion criteria

• PROSTATE BIOPSY COHORT: Patients with a history of prostate cancer
• PROSTATE BIOPSY COHORT: Patients with a history of surgical treatment on benign prostate hyperplasia
• PROSTATE BIOPSY COHORT: Patients undergoing saturation prostate biopsy
• PROSTATE BIOPSY COHORT: Patients under 20 years old
• PROSTATE BIOPSY COHORT: Patients with previous PBx history
• PROSTATE BIOPSY COHORT: MRI which was not interpreted by PIRADS
• PROSTATE BIOPSY COHORT: MRI with significant artifact
• RADICAL PROSTATECTOMY COHORT: Patients who are undergoing neo-adjuvant hormonal therapy in conjunction with radical prostatectomy
• RADICAL PROSTATECTOMY COHORT: Patients with a history of surgical treatment on benign prostate hyperplasia
• RADICAL PROSTATECTOMY COHORT: Patients under 20 years old
• RADICAL PROSTATECTOMY COHORT: Patients without pre-treatment MRI
• RADICAL PROSTATECTOMY COHORT: MRI which was not interpreted by PIRADS
• RADICAL PROSTATECTOMY COHORT: MRI with significant artifact
• RADICAL PROSTATECTOMY COHORT: Patients who are included in the Biopsy cohort

Trial design

Primary purpose: Diagnostic

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Quadruple Blind

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130 participants in 7 patient groups

Cohort 1 Arm I (MRI/TRUS, PIRADS, GL AI, DL AI)

Experimental group

Description:

Patients undergo MRI/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.

Treatment:

Diagnostic Test: Deep Learning Artificial Intelligence

Diagnostic Test: Green Learning Artificial Intelligence

Diagnostic Test: Prostate Imaging Reporting & Data System

Procedure: Targeted Prostate Biopsy

Procedure: Radical Prostatectomy

Cohort 1 Arm II (MRI/TRUS, PIRADS, DL AI, GL AI)

Experimental group

Description:

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. Patients undergo up to 12 additional prostate biopsies per SOC. Based on biopsy results, patients will either come off study or undergo radical prostatectomy without hormonal therapy within 180 days from baseline MRI.

Treatment:

Diagnostic Test: Deep Learning Artificial Intelligence

Diagnostic Test: Green Learning Artificial Intelligence

Diagnostic Test: Prostate Imaging Reporting & Data System

Procedure: Targeted Prostate Biopsy

Procedure: Radical Prostatectomy

Cohort 1 Arm III (MRI/TRUS, GL AI, PIRADS, DL AI)

Experimental group

Description:

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. Patients undergo up to 12 additional prostate biopsies per SOC. Based on biopsy results, patients will either come off study or undergo radical prostatectomy without hormonal therapy within 180 days from baseline MRI.

Treatment:

Diagnostic Test: Deep Learning Artificial Intelligence

Diagnostic Test: Green Learning Artificial Intelligence

Diagnostic Test: Prostate Imaging Reporting & Data System

Procedure: Targeted Prostate Biopsy

Procedure: Radical Prostatectomy

Cohort 1 Arm IV (MRI/TRUS, GL AI, DL AI, PIRADS)

Experimental group

Description:

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. Patients may also undergo DRE on study.

Treatment:

Diagnostic Test: Deep Learning Artificial Intelligence

Diagnostic Test: Green Learning Artificial Intelligence

Diagnostic Test: Prostate Imaging Reporting & Data System

Procedure: Targeted Prostate Biopsy

Procedure: Radical Prostatectomy

Cohort 1 Arm V (MRI/TRUS, DL AI, PIRADS, GL AI)

Experimental group

Description:

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. Patients undergo up to 12 additional prostate biopsies per SOC. Based on biopsy results, patients will either come off study or undergo radical prostatectomy without hormonal therapy within 180 days from baseline MRI.

Treatment:

Diagnostic Test: Deep Learning Artificial Intelligence

Diagnostic Test: Green Learning Artificial Intelligence

Diagnostic Test: Prostate Imaging Reporting & Data System

Procedure: Targeted Prostate Biopsy

Procedure: Radical Prostatectomy

Cohort 1 Arm VI (MRI/TRUS, DL AI, GL AI, PIRADS)

Experimental group

Description:

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. Patients undergo up to 12 additional prostate biopsies per SOC. Based on biopsy results, patients will either come off study or undergo radical prostatectomy without hormonal therapy within 180 days from baseline MRI.

Treatment:

Diagnostic Test: Deep Learning Artificial Intelligence

Diagnostic Test: Green Learning Artificial Intelligence

Diagnostic Test: Prostate Imaging Reporting & Data System

Procedure: Targeted Prostate Biopsy

Procedure: Radical Prostatectomy

Cohort 2 (Radical Prostatectomy Cohort)

Experimental group

Description:

Patients undergo MRI/TRUS then a radical prostatectomy (RP), which are performed per standard of care at our institution. PIRADS, GL AI, and DL AI will be used to interpret the MRI/TRUS results prior to RP.

Treatment:

Diagnostic Test: Deep Learning Artificial Intelligence

Diagnostic Test: Green Learning Artificial Intelligence

Diagnostic Test: Prostate Imaging Reporting & Data System

Procedure: Radical Prostatectomy