Prostate CarcinomaNCT07162194
MRI-Based Machine Learning Approach Versus Radiologist MRI Reading for the Detection of Prostate Cancer, The PRIMER Trial
A study testing Targeted Prostate Biopsy, Prostate Imaging Reporting & Data System and Deep Learning Artificial Intelligence in people with Prostate Carcinoma, run by University of Southern California at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 20 years and older, men only
- Conditions the study is for
- Prostate Carcinoma
- What is being tested?
- Targeted Prostate Biopsy, Prostate Imaging Reporting & Data System and Deep Learning Artificial Intelligence
- Type of treatment
- Surgery or procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 130 participants
- Where
- 1 siteUnited States
- Study dates
- 19 Sep 2025to 15 Oct 2028
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 years and older
- Men only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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 365 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 365 days prior to radical prostatectomy
- RADICAL PROSTATECTOMY COHORT: Patients who consented to the study
Who cannot join
- 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
Show all 14Show fewer
- 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 locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
USC / Norris Comprehensive Cancer Center
Los Angeles, California, 90033
Andre Luis Abreu, 323-865-3000, andre.abreu@med.usc.edu
Andre Luis Abreu
About this study
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
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.
Read the detailed description
PRIMARY OBJECTIVE:
- To determine the non-inferiority of targeted biopsy according to Green Learning (GL) AI over Prostate Imaging Reporting \& Data System (PIRADS).
SECONDARY OBJECTIVES:
- 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.
- Conditions
- Prostate Carcinoma
- Being tested
- Targeted Prostate Biopsy, Prostate Imaging Reporting & Data System, Deep Learning Artificial Intelligence, Green Learning Artificial Intelligence, Radical Prostatectomy
- Medical subject headings
- Prostatic Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Targeted Prostate BiopsyProcedure or surgery
Also called TB, Prostate Biopsy, PBx
Undergo targeted prostate biopsy
Prostate Imaging Reporting & Data SystemDiagnostic test
Also called PIRADS
PIRADS Assessment
Deep Learning Artificial IntelligenceDiagnostic test
Also called DL AI
Deep Learning (DL) AI predictions
Green Learning Artificial IntelligenceDiagnostic test
Also called GL AI
Green Learning (GL) AI predictions
Radical ProstatectomyProcedure or surgery
Also called RP
Undergo RP
| Study group | Role | What they receive |
|---|---|---|
| Cohort 1 Arm I (MRI/TRUS, PIRADS, GL AI, DL AI) | Experimental | 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. Receives: Procedure: Targeted Prostate Biopsy; Diagnostic Test: Prostate Imaging Reporting & Data System; Diagnostic Test: Deep Learning Artificial Intelligence; Diagnostic Test: Green Learning Artificial Intelligence; Procedure: Radical Prostatectomy |
| Cohort 1 Arm II (MRI/TRUS, PIRADS, DL AI, GL AI) | Experimental | 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. Receives: Procedure: Targeted Prostate Biopsy; Diagnostic Test: Prostate Imaging Reporting & Data System; Diagnostic Test: Deep Learning Artificial Intelligence; Diagnostic Test: Green Learning Artificial Intelligence; Procedure: Radical Prostatectomy |
| Cohort 1 Arm III (MRI/TRUS, GL AI, PIRADS, DL AI) | Experimental | 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. Receives: Procedure: Targeted Prostate Biopsy; Diagnostic Test: Prostate Imaging Reporting & Data System; Diagnostic Test: Deep Learning Artificial Intelligence; Diagnostic Test: Green Learning Artificial Intelligence; Procedure: Radical Prostatectomy |
| Cohort 1 Arm IV (MRI/TRUS, GL AI, DL AI, PIRADS) | Experimental | 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. Receives: Procedure: Targeted Prostate Biopsy; Diagnostic Test: Prostate Imaging Reporting & Data System; Diagnostic Test: Deep Learning Artificial Intelligence; Diagnostic Test: Green Learning Artificial Intelligence; Procedure: Radical Prostatectomy |
| Cohort 1 Arm V (MRI/TRUS, DL AI, PIRADS, GL AI) | Experimental | 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. Receives: Procedure: Targeted Prostate Biopsy; Diagnostic Test: Prostate Imaging Reporting & Data System; Diagnostic Test: Deep Learning Artificial Intelligence; Diagnostic Test: Green Learning Artificial Intelligence; Procedure: Radical Prostatectomy |
| Cohort 1 Arm VI (MRI/TRUS, DL AI, GL AI, PIRADS) | Experimental | 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. Receives: Procedure: Targeted Prostate Biopsy; Diagnostic Test: Prostate Imaging Reporting & Data System; Diagnostic Test: Deep Learning Artificial Intelligence; Diagnostic Test: Green Learning Artificial Intelligence; Procedure: Radical Prostatectomy |
| Cohort 2 (Radical Prostatectomy Cohort) | Experimental | 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. Receives: Diagnostic Test: Prostate Imaging Reporting & Data System; Diagnostic Test: Deep Learning Artificial Intelligence; Diagnostic Test: Green Learning Artificial Intelligence; Procedure: Radical Prostatectomy |
What is being measured
The primary outcome is the main question the study is designed to answer.
Clinically-significant prostate cancer (CSPCa) detection rate on Green Learning (GL) artificial intelligence (AI)-targeted and Prostate Imaging-Reporting and Data System (PIRADS)-targeted biopsies
Detection rates of PIRADS and GL AI-targeted biopsy will be evaluated per index region of interest (ROI), respectively.
Measured: Up to 3 months
CSPCa detection rate on GL AI-targeted and Deep Learning (DL) AI-targeted biopsies
Detection rates of GL AI and DL AI targeted biopsy will be evaluated per index ROI, respectively.
Measured: Up to 3 months
Secondary outcomes (4)
Patient-level diagnostic performance of GL AI and PIRADS for CSPCa detection
Sensitivity, specificity, accuracy, positive predictive value, and negative predictive value will be compared between PIRADS, GL AI, and DL AI predictions by McNemar test. The performance will be calculated according to the definitions below. Additionally, decision curve analysis will be conducted.
Measured: Up to 3 months
Targeted biopsy core characteristics
Will include prostate cancer subtypes, benign elements, lesion locations, cancer core length (mm), cancer core involvement (%), and Gleason Grade Group. Will be compared between PIRADS, GL AI, and DL AI by Chi-square test or Wilcoxon rank sum test.
Measured: Up to 3 months
Predictors for patient-level CSPCa detection
Independent predictors for patient-level CSPCa detection will be assessed by logistic regression. Predictors include age, race, ethnicity, prostate-specific antigen (PSA), PSA density (PSA/prostate volume measured on magnetic resonance imaging [MRI]), digital rectal examination (DRE) abnormality, PIRADS score, GL AI prediction score, and DL AI prediction score. Classifier will be created using the strong predictors for CSPCa, and its discriminant performance will be assessed by the receiver operating characteristic (ROC) analysis.
Measured: Up to 3 months
Dice score and linear correlation coefficient of CSPCa distribution on radical prostatectomy (RP) specimens and ROI generated by GL AI, DL AI and PIRADS
Distribution of CSPCa on the RP specimen will be annotated on the digitized slides and 3-dimensional reconstructed as ground truth. ROI segmentations according to PIRADS, GL AI prediction heatmap, and DL AI prediction heatmap also will be 3D reconstructed. The spatial concordance between GL-ROI, DL AI-ROI, PIRADS-ROI, and CSPCa distribution on RP specimen will be assessed. The accuracy of the spatial concordance and volume estimation will be analyzed by the Dice score and linear correlation analysis, respectively.
Measured: Up to 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Sep 2025
- Study start19 Sep 2025
- Primary completion15 Oct 2027 (estimated)
- Study completion15 Oct 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Prostate CarcinomaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Quadruple blind
- Who is masked
- Participant, Care provider, Investigator, Outcomes assessor
- Enrolment
- 130 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Southern California
- Sponsor type
- University, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Responsible party
- Sponsor
- Investigators
- Andre Luis Abreu, MD, Principal investigator, University of Southern California
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07162194
- Sponsor's protocol ID
- 4P-25-1
- Other IDs
- NCI-2025-03027, 4P-25-1, P30CA014089
- Status last verified
- Aug 2026
- First submitted
- 29 Aug 2025
- Last updated
- 1 Sep 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
Study at a glance
From the registry record, last updated by the sponsor on 1 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- 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
- ClinicalTrials.gov ID
- NCT07162194
- Acronym / sponsor ID
- 4P-25-1
- Conditions
- Prostate Carcinoma
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 130 participants (estimated)
- Lead sponsor
- University of Southern CaliforniaUniversity, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Study start
- 19 Sep 2025 (actual)
- Primary completion
- 15 Oct 2027 (estimated)
- Study completion
- 15 Oct 2028 (estimated)
- First posted
- 9 Sep 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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:
- To determine the non-inferiority of targeted biopsy according to Green Learning (GL) AI over Prostate Imaging Reporting \& Data System (PIRADS).
SECONDARY OBJECTIVES:
- 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.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Quadruple blind (participant, care provider, investigator, outcomes assessor)
- Number of arms
- 7
| Arm | Type | Receives |
|---|---|---|
| Cohort 1 Arm I (MRI/TRUS, PIRADS, GL AI, DL AI) | Experimental | Procedure: Targeted Prostate Biopsy, Diagnostic Test: Prostate Imaging Reporting & Data System, Diagnostic Test: Deep Learning Artificial Intelligence, Diagnostic Test: Green Learning Artificial Intelligence, Procedure: Radical ProstatectomyPatients 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. |
| Cohort 1 Arm II (MRI/TRUS, PIRADS, DL AI, GL AI) | Experimental | Procedure: Targeted Prostate Biopsy, Diagnostic Test: Prostate Imaging Reporting & Data System, Diagnostic Test: Deep Learning Artificial Intelligence, Diagnostic Test: Green Learning Artificial Intelligence, Procedure: Radical ProstatectomyPatients 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. |
| Cohort 1 Arm III (MRI/TRUS, GL AI, PIRADS, DL AI) | Experimental | Procedure: Targeted Prostate Biopsy, Diagnostic Test: Prostate Imaging Reporting & Data System, Diagnostic Test: Deep Learning Artificial Intelligence, Diagnostic Test: Green Learning Artificial Intelligence, Procedure: Radical ProstatectomyPatients 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. |
| Cohort 1 Arm IV (MRI/TRUS, GL AI, DL AI, PIRADS) | Experimental | Procedure: Targeted Prostate Biopsy, Diagnostic Test: Prostate Imaging Reporting & Data System, Diagnostic Test: Deep Learning Artificial Intelligence, Diagnostic Test: Green Learning Artificial Intelligence, Procedure: Radical ProstatectomyPatients 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. |
| Cohort 1 Arm V (MRI/TRUS, DL AI, PIRADS, GL AI) | Experimental | Procedure: Targeted Prostate Biopsy, Diagnostic Test: Prostate Imaging Reporting & Data System, Diagnostic Test: Deep Learning Artificial Intelligence, Diagnostic Test: Green Learning Artificial Intelligence, Procedure: Radical ProstatectomyPatients 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. |
| Cohort 1 Arm VI (MRI/TRUS, DL AI, GL AI, PIRADS) | Experimental | Procedure: Targeted Prostate Biopsy, Diagnostic Test: Prostate Imaging Reporting & Data System, Diagnostic Test: Deep Learning Artificial Intelligence, Diagnostic Test: Green Learning Artificial Intelligence, Procedure: Radical ProstatectomyPatients 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. |
| Cohort 2 (Radical Prostatectomy Cohort) | Experimental | Diagnostic Test: Prostate Imaging Reporting & Data System, Diagnostic Test: Deep Learning Artificial Intelligence, Diagnostic Test: Green Learning Artificial Intelligence, Procedure: Radical ProstatectomyPatients 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. |
Who may qualify
- Ages
- 20 years and older
- Sex
- Male only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- 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 365 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 365 days prior to radical prostatectomy
Key exclusion criteria (14 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Targeted Prostate BiopsyAlso: TB, Prostate Biopsy, PBxUndergo targeted prostate biopsy | Procedure or surgery | Cohort 1 Arm I (MRI/TRUS, PIRADS, GL AI, DL AI), Cohort 1 Arm II (MRI/TRUS, PIRADS, DL AI, GL AI), Cohort 1 Arm III (MRI/TRUS, GL AI, PIRADS, DL AI), Cohort 1 Arm IV (MRI/TRUS, GL AI, DL AI, PIRADS), Cohort 1 Arm V (MRI/TRUS, DL AI, PIRADS, GL AI), Cohort 1 Arm VI (MRI/TRUS, DL AI, GL AI, PIRADS) |
| Prostate Imaging Reporting & Data SystemAlso: PIRADSPIRADS Assessment | Diagnostic test | Cohort 1 Arm I (MRI/TRUS, PIRADS, GL AI, DL AI), Cohort 1 Arm II (MRI/TRUS, PIRADS, DL AI, GL AI), Cohort 1 Arm III (MRI/TRUS, GL AI, PIRADS, DL AI), Cohort 1 Arm IV (MRI/TRUS, GL AI, DL AI, PIRADS), Cohort 1 Arm V (MRI/TRUS, DL AI, PIRADS, GL AI), Cohort 1 Arm VI (MRI/TRUS, DL AI, GL AI, PIRADS), Cohort 2 (Radical Prostatectomy Cohort) |
| Deep Learning Artificial IntelligenceAlso: DL AIDeep Learning (DL) AI predictions | Diagnostic test | Cohort 1 Arm I (MRI/TRUS, PIRADS, GL AI, DL AI), Cohort 1 Arm II (MRI/TRUS, PIRADS, DL AI, GL AI), Cohort 1 Arm III (MRI/TRUS, GL AI, PIRADS, DL AI), Cohort 1 Arm IV (MRI/TRUS, GL AI, DL AI, PIRADS), Cohort 1 Arm V (MRI/TRUS, DL AI, PIRADS, GL AI), Cohort 1 Arm VI (MRI/TRUS, DL AI, GL AI, PIRADS), Cohort 2 (Radical Prostatectomy Cohort) |
| Green Learning Artificial IntelligenceAlso: GL AIGreen Learning (GL) AI predictions | Diagnostic test | Cohort 1 Arm I (MRI/TRUS, PIRADS, GL AI, DL AI), Cohort 1 Arm II (MRI/TRUS, PIRADS, DL AI, GL AI), Cohort 1 Arm III (MRI/TRUS, GL AI, PIRADS, DL AI), Cohort 1 Arm IV (MRI/TRUS, GL AI, DL AI, PIRADS), Cohort 1 Arm V (MRI/TRUS, DL AI, PIRADS, GL AI), Cohort 1 Arm VI (MRI/TRUS, DL AI, GL AI, PIRADS), Cohort 2 (Radical Prostatectomy Cohort) |
| Radical ProstatectomyAlso: RPUndergo RP | Procedure or surgery | Cohort 1 Arm I (MRI/TRUS, PIRADS, GL AI, DL AI), Cohort 1 Arm II (MRI/TRUS, PIRADS, DL AI, GL AI), Cohort 1 Arm III (MRI/TRUS, GL AI, PIRADS, DL AI), Cohort 1 Arm IV (MRI/TRUS, GL AI, DL AI, PIRADS), Cohort 1 Arm V (MRI/TRUS, DL AI, PIRADS, GL AI), Cohort 1 Arm VI (MRI/TRUS, DL AI, GL AI, PIRADS), Cohort 2 (Radical Prostatectomy Cohort) |
Primary outcome
Clinically-significant prostate cancer (CSPCa) detection rate on Green Learning (GL) artificial intelligence (AI)-targeted and Prostate Imaging-Reporting and Data System (PIRADS)-targeted biopsies
Time frame: Up to 3 months
Detection rates of PIRADS and GL AI-targeted biopsy will be evaluated per index region of interest (ROI), respectively.
CSPCa detection rate on GL AI-targeted and Deep Learning (DL) AI-targeted biopsies
Time frame: Up to 3 months
Detection rates of GL AI and DL AI targeted biopsy will be evaluated per index ROI, respectively.
4 secondary outcomes
Patient-level diagnostic performance of GL AI and PIRADS for CSPCa detection
Time frame: Up to 3 months
Targeted biopsy core characteristics
Time frame: Up to 3 months
Predictors for patient-level CSPCa detection
Time frame: Up to 3 months
Dice score and linear correlation coefficient of CSPCa distribution on radical prostatectomy (RP) specimens and ROI generated by GL AI, DL AI and PIRADS
Time frame: Up to 3 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 1 Sep 2026.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Andre Luis Abreu, MD principal investigator
University of Southern California
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Targeted Prostate Biopsy, Prostate Imaging Reporting & Data System and Deep Learning Artificial Intelligence in people with Prostate Carcinoma, run by University of Southern California at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 14 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 1 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Ileana Aldana (323-865-0702, Ileana.aldana@med.usc.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Clinically-significant prostate cancer (CSPCa) detection rate on Green Learning (GL) artificial intelligence (AI)-targeted and Prostate Imaging-Reporting and Data System (PIRADS)-targeted biopsies (time frame: Up to 3 months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 1 Sep 2026.