Ignite Creation Date:
2025-12-25 @ 1:40 AM
Ignite Modification Date:
2026-01-04 @ 3:47 AM
Study NCT ID:
NCT07162194
Status:
SUSPENDED
Last Update Posted:
2025-11-26
First Post:
2025-08-29
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
MRI-Based Machine Learning Approach Versus Radiologist MRI Reading for the Detection of Prostate Cancer, The PRIMER Trial
Sponsor:
University of Southern California
Organization:
Study Overview
Official Title:
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
Status:
SUSPENDED
Status Verified Date:
2025-11
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Pending IRB approval and implementation of protocol amendment
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief 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.
Detailed 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 patient-level diagnostic performance of GL AI, Deep Learning (DL) AI and PIRADS for clinically significant prostate cancer (CSPCa) detection.
II. To assess Targeted biopsy core characteristics. III. To evaluate the predictors for patient-level CSPCa detection. IV. 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.
All patients may also undergo digital rectal exam (DRE) on study.
After completion of study intervention, patients are followed up at 10 days and at 3 months.
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 patient-level diagnostic performance of GL AI, Deep Learning (DL) AI and PIRADS for clinically significant prostate cancer (CSPCa) detection.
II. To assess Targeted biopsy core characteristics. III. To evaluate the predictors for patient-level CSPCa detection. IV. 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.
All patients may also undergo digital rectal exam (DRE) on study.
After completion of study intervention, patients are followed up at 10 days and at 3 months.
Study Oversight
Has Oversight DMC:
True
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?:
Secondary ID Infos
| Secondary ID | Type | Domain | Link | View |
|---|---|---|---|---|
| NCI-2025-03027 | REGISTRY | CTRP (Clinical Trial Reporting Program) | View | |
| 4P-25-1 | OTHER | USC / Norris Comprehensive Cancer Center | View | |
| P30CA014089 | NIH | None | https://reporter.nih.gov/quic… | View |