Prostate CancerNCT07084779
Investigation of Impact of AI on Prostate Cancer Workflow
A study testing AI in people with Prostate Cancer and Prostatic Neoplasm, run by Case Comprehensive Cancer Center at 1 site in United States.
Trial summary
This study will enroll participants who are undergoing an MRI before a prostate biopsy due to suspected prostate cancer. The purpose of this study is to see if the use of Artificial Intelligence (AI) helps detect lesions on an MRI better than a radiologist not using AI. Read more about this study
- Who is it for?
- Ages 55 to 80 years
- Conditions the study is for
- Prostate Cancer, Prostatic Neoplasm, Cancer of the Prostate
- What is being tested?
- AI
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 150 participants
- Where
- 1 siteUnited States
- Study dates
- 9 Sep 2025to 30 Nov 2026
- 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 55 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Plan of care is to undergo a biopsy of the prostate after a pre-biopsy MRI
- Age 55-80
- Prostate-specific antigen (PSA) between 3-10 ng/mL
- No prior diagnosis or treatment of prostate cancer
Who cannot join
- Pre-biopsy MRI is of low quality
- PI-QUAL score of 1 using PI-QUAL version 2
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
Cleveland Clinic Foundation
Cleveland, Ohio, 44195
Andrei Purysko, 216-445-9005, puryska@ccf.org
About this study
This study will enroll participants who are undergoing an MRI before a prostate biopsy due to suspected prostate cancer. The purpose of this study is to see if the use of Artificial Intelligence (AI) helps detect lesions on an MRI better than a radiologist not using AI. The AI Rad Companion (AIRC) Prostate MRI application is a software that uses measurements of the prostate and will be utilized in this study to help detect potential cancerous lesions. The AI software will assign the lesions a PI-RADS score, which is a way to measure the chance of the lesion being cancer.
There are two parts to this study. The first part involves comparing the interpretation of prostate MRI images by a radiologist alone, a radiologist aided by AI, and AI alone. A systematic biopsy will be completed per standard of care. The radiologist may opt to include up to 2 additional AI-identified targets to biopsy in addition to those biopsied for standard of care.
The second part of the study involves utilizing the MRI images from the first part of the study in addition to retrospective prostate MRI images. These de-identified images, along with Prostate Image Quality (PI-QUAL) scores, clinical data, and biopsy results will be sent to Siemens in order to aid in the development of methods to identify good or bad image quality in prostate MRI images.
Read the detailed description
Prostate cancer is the most diagnosed cancer among men in the United States and the second most prevalent cancer in men worldwide (1,2). MRI can better triage patients to undergo biopsy, while providing information about tumors and treatment progress (4). However, there are challenges with MRI image quality, the interpretation of the images, and the potential for false positives and negatives. With the annual number of prostate exams rapidly increasing (5), there is a need for accurate and reliable prostate MRI interpretation. One proposed approach is to use an AI-based lesion detection software in addition to radiologists' interpretations. The Siemens Healthineers ("Siemens") business lines Digital \& Automation ("D\&A") and Magnetic Resonance ("MR") have developed the AI Rad Companion Prostate MRI (AIRC), which aids in the detection of potential prostate cancer. The goal of this study is to investigate the effects of the use of AIRC in improving the standard of care in prostate cancer detection and treatment. Participation in the study will be about an hour to review the consent form. All other study procedures (MRI, biopsy) will be standard of care.
- Being tested
- AI
- Keywords
- Artificial Intelligence, Magnetic Resonance Imaging, Biopsy
- Medical subject headings
- Prostatic Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AIDevice
Following the completion of a pre-biopsy prostate MRI, the radiologist will interpret the MRI. Once interpreted by the radiologist alone, the radiologist will interpret the scan while aided by AI. A systematic biopsy in conjunction with radiologist-identified targets will be completed per standard of care, with the optional inclusion of up to 2 AI-detected targets.
When completing a biopsy per SOC, the prostate is divided into quadrants. In addition to noted targets, samples are taken systematically from each quadrant. If targets are detected by AI that were not identified by the physician when reviewing the MRI, these targets will be sampled. Sampling of these targets will not be in addition to the systematic sampling in each quadrant, but in place of up to two of the samples biopsied systematically
| Study group | Role | What they receive |
|---|---|---|
| AI-aided MRI & Prostate Biopsy | Experimental | Not described Receives: Device: AI |
What is being measured
The primary outcome is the main question the study is designed to answer.
Readers' (radiologists') mean quadrant-level area under the receiver operating characteristic curve (AUC) in predicting the presence or absence of clinically significant prostate cancer (csPCa)
csPCa is defined as Gleason grade group ≥ 2.
Measured: One-time MRI, up to 30 days post-enrollment in study.
Secondary outcomes (8)
Inter-reader agreement on the presence/absence of csPCa at the participant-level
Agreement is defined as agreement between unaided vs aided reads. If the highest lesion-level PI-RADS assigned to a patient is greater than or equal to 3, the participant is considered positive.
Measured: One-time MRI, up to 30 days post-enrollment in study.
Inter-reader agreement on the presence/absence of csPCa at the quadrant-level
Agreement is defined as agreement between unaided vs aided reads. If the highest lesion-level PI-RADS assigned to a quadrant is greater than or equal to 3, the quadrant is considered positive.
Measured: One-time MRI, up to 30 days post-enrollment in study.
Participant-level sensitivity for detection of clinically significant prostate cancer
If the highest lesion-level PI-RADS assigned to a patient is greater than or equal to 3, the patient is considered positive.
Measured: One-time MRI, up to 30 days post-enrollment in study.
Participant-level specificity for detection of clinically significant prostate cancer
If the highest lesion-level PI-RADS assigned to a patient is greater than or equal to 3, the patient is considered positive.
Measured: One-time MRI, up to 30 days post-enrollment in study.
Quadrant-level sensitivity for detection of clinically significant prostate cancer
If the highest lesion-level PI-RADS assigned to a quadrant is greater than or equal to 3, the quadrant is considered positive.
Measured: One-time MRI, up to 30 days post-enrollment in study.
Quadrant-level specificity for detection of clinically significant prostate cancer
If the highest lesion-level PI-RADS assigned to a quadrant is greater than or equal to 3, the quadrant is considered positive.
Measured: One-time MRI, up to 30 days post-enrollment in study.
Free-response ROC curve for the aided and unaided reads
The average number of false positives per patient will be on the x-axis, while lesion-level sensitivity will be on the y-axis.
Measured: One-time MRI, up to 30 days post-enrollment in study.
Comparison of the quadrant-level AUC of the unaided vs AI read
Measured: One-time MRI, up to 30 days post-enrollment in study.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Jul 2025
- Study start9 Sep 2025
- Primary completion30 Nov 2026 (estimated)
- Study completion30 Nov 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Prostate CancerStudies of the same condition, open and under way.
- More trials run by Case Comprehensive Cancer CenterThe sponsor's other registered studies.
- 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
- Screening
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 150 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Case Comprehensive Cancer Center
- Sponsor type
- University, hospital or other
- Collaborators
- Siemens Medical Solutions
- Responsible party
- Sponsor
- Investigators
- Andrei Purysko, MD, Principal investigator, Case Comprehensive Cancer Center, Cleveland Clinic
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07084779
- Sponsor's protocol ID
- CASE3825
- Status last verified
- Sep 2026
- First submitted
- 17 Jul 2025
- Last updated
- 15 Sep 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 15 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Investigation of Impact of AI on Prostate Cancer Workflow
- ClinicalTrials.gov ID
- NCT07084779
- Acronym / sponsor ID
- CASE3825
- Keywords
- Artificial Intelligence, Magnetic Resonance Imaging, Biopsy
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- Case Comprehensive Cancer CenterUniversity, hospital or other
- Collaborators
- Siemens Medical Solutions
- Study start
- 9 Sep 2025 (actual)
- Primary completion
- 30 Nov 2026 (estimated)
- Study completion
- 30 Nov 2026 (estimated)
- First posted
- 25 Jul 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 study will enroll participants who are undergoing an MRI before a prostate biopsy due to suspected prostate cancer. The purpose of this study is to see if the use of Artificial Intelligence (AI) helps detect lesions on an MRI better than a radiologist not using AI. The AI Rad Companion (AIRC) Prostate MRI application is a software that uses measurements of the prostate and will be utilized in this study to help detect potential cancerous lesions. The AI software will assign the lesions a PI-RADS score, which is a way to measure the chance of the lesion being cancer.
There are two parts to this study. The first part involves comparing the interpretation of prostate MRI images by a radiologist alone, a radiologist aided by AI, and AI alone. A systematic biopsy will be completed per standard of care. The radiologist may opt to include up to 2 additional AI-identified targets to biopsy in addition to those biopsied for standard of care.
The second part of the study involves utilizing the MRI images from the first part of the study in addition to retrospective prostate MRI images. These de-identified images, along with Prostate Image Quality (PI-QUAL) scores, clinical data, and biopsy results will be sent to Siemens in order to aid in the development of methods to identify good or bad image quality in prostate MRI images.
Detailed description
Prostate cancer is the most diagnosed cancer among men in the United States and the second most prevalent cancer in men worldwide (1,2). MRI can better triage patients to undergo biopsy, while providing information about tumors and treatment progress (4). However, there are challenges with MRI image quality, the interpretation of the images, and the potential for false positives and negatives. With the annual number of prostate exams rapidly increasing (5), there is a need for accurate and reliable prostate MRI interpretation. One proposed approach is to use an AI-based lesion detection software in addition to radiologists' interpretations. The Siemens Healthineers ("Siemens") business lines Digital \& Automation ("D\&A") and Magnetic Resonance ("MR") have developed the AI Rad Companion Prostate MRI (AIRC), which aids in the detection of potential prostate cancer. The goal of this study is to investigate the effects of the use of AIRC in improving the standard of care in prostate cancer detection and treatment. Participation in the study will be about an hour to review the consent form. All other study procedures (MRI, biopsy) will be standard of care.
Study design
- Primary purpose
- Screening
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| AI-aided MRI & Prostate Biopsy | Experimental | Device: AI |
Who may qualify
- Ages
- 55 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Plan of care is to undergo a biopsy of the prostate after a pre-biopsy MRI
- Age 55-80
- Prostate-specific antigen (PSA) between 3-10 ng/mL
- No prior diagnosis or treatment of prostate cancer
Key exclusion criteria (2 listed)
- Pre-biopsy MRI is of low quality
- PI-QUAL score of 1 using PI-QUAL version 2
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 |
|---|---|---|
| AIFollowing the completion of a pre-biopsy prostate MRI, the radiologist will interpret the MRI. Once interpreted by the radiologist alone, the radiologist will interpret the scan while aided by AI. A systematic biopsy in conjunction with radiologist-identified targets will be completed per standard of care, with the optional inclusion of up to 2 AI-detected targets. When completing a biopsy per SOC, the prostate is divided into quadrants. In addition to noted targets, samples are taken systematically from each quadrant. If targets are detected by AI that were not identified by the physician when reviewing the MRI, these targets will be sampled. Sampling of these targets will not be in addition to the systematic sampling in each quadrant, but in place of up to two of the samples biopsied systematically | Device | AI-aided MRI & Prostate Biopsy |
Primary outcome
Readers' (radiologists') mean quadrant-level area under the receiver operating characteristic curve (AUC) in predicting the presence or absence of clinically significant prostate cancer (csPCa)
Time frame: One-time MRI, up to 30 days post-enrollment in study.
csPCa is defined as Gleason grade group ≥ 2.
8 secondary outcomes
Inter-reader agreement on the presence/absence of csPCa at the participant-level
Time frame: One-time MRI, up to 30 days post-enrollment in study.
Inter-reader agreement on the presence/absence of csPCa at the quadrant-level
Time frame: One-time MRI, up to 30 days post-enrollment in study.
Participant-level sensitivity for detection of clinically significant prostate cancer
Time frame: One-time MRI, up to 30 days post-enrollment in study.
Participant-level specificity for detection of clinically significant prostate cancer
Time frame: One-time MRI, up to 30 days post-enrollment in study.
Quadrant-level sensitivity for detection of clinically significant prostate cancer
Time frame: One-time MRI, up to 30 days post-enrollment in study.
Quadrant-level specificity for detection of clinically significant prostate cancer
Time frame: One-time MRI, up to 30 days post-enrollment in study.
Free-response ROC curve for the aided and unaided reads
Time frame: One-time MRI, up to 30 days post-enrollment in study.
Comparison of the quadrant-level AUC of the unaided vs AI read
Time frame: One-time MRI, up to 30 days post-enrollment in study.
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 15 Sep 2026.
- Individual participant dataSharing planned: No
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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.
Andrei Purysko, MD principal investigator
Case Comprehensive Cancer Center, Cleveland Clinic
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI in people with Prostate Cancer and Prostatic Neoplasm, run by Case Comprehensive Cancer Center 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 4 inclusion and 2 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 15 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 Andrei Purysko, MD (216-445-9005, puryska@ccf.org), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Readers' (radiologists') mean quadrant-level area under the receiver operating characteristic curve (AUC) in predicting the presence or absence of clinically significant prostate cancer (csPCa) (time frame: One-time MRI, up to 30 days post-enrollment in study.). 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 15 Sep 2026.