Improved MRI methods to distinguish benign from cancerous pelvic findings
Official title: Clinical Evidence Generation of AI Enabled Fast, Accurate and Precise Screening and Staging of Benign vs Malignant Pelvic Abnormalities
Run by Mayo Clinic · NCT07407959 · Data updated 2026-11-12
This test tries new deep-learning image-processing methods on MRI scans to get clearer images faster for adults scanned for prostate screening or suspected endometriosis.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 60 (estimated) |
| Sponsor | Mayo Clinic Academic / other |
| Locations | 1 site (Rochester, Minnesota) |
| Status | Recruiting |
| Started | September 4, 2025 |
| Main results expected | September 30, 2028 |
| Study ends | September 30, 2028 |
| Registry record updated | February 17, 2026 |
| Trial ID | NCT07407959 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults 18 and older referred for prostate MRI screening with no prior prostate treatment or biopsy, or adults referred for evaluation of suspected endometriosis before surgery, who can safely undergo MRI and provide consent.
✕Probably not a fit
People under 18, pregnant individuals, those with MR-incompatible implants or other MRI contraindications, patients unable to consent, and prostate patients with prior prostate treatment or biopsy are unlikely to qualify or benefit from this protocol.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study applies two non–FDA-approved image reconstruction approaches (Adaptive Image Reconstruction Deep Learning and Sonic Deep Learning) to pelvic MRI scans and compares image quality and scan processing time with current techniques. Adults referred for prostate MRI screening (with no prior prostate treatment or biopsy) or referred for pre-surgical evaluation of suspected endometriosis will be included. The study collects MRI data at a single site and processes images using the novel algorithms without changing clinical care. Standard MRI safety exclusions (eg, incompatible implants, pregnancy) and the ability to consent are required.
Why it matters
Potential benefit: If successful, these methods could produce clearer MRI images in less time, helping clinicians better distinguish benign from malignant pelvic abnormalities and speed diagnosis and treatment planning.
How similar studies have gone: Related deep-learning MRI reconstruction techniques have shown promising improvements in image quality and speed in prior research, but the specific AIR Recon and Sonic DL approaches used here are novel and not FDA-approved.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patient over the age of 18 * For prostate group, any patient referred for prostate MR for screening purposes with no prior prostate related treatment or prior biopsy * For endometriosis group, any patient referred for possible endometriosis evaluation (pre-surgical) Exclusion Criteria: * Individuals unable to undergo MRI imaging (MR-conditional or MR-nonconditional devices which would need additional procedures/conditions for scanning, pregnant people, individuals with implanted metal, etc.) * Patient under the age of 18 * Patient who is unable to consent
Where it's running
-
Mayo Clinic in Rochester
Rochester, Minnesota, United States Recruiting
Study contacts
- Principal investigator: Candice A. Bookwalter, MD, PhD — Mayo Clinic in Rochester
- Study coordinator: Clinical Trials Referral Office
- Email: mayocliniccancerstudies@mayo.edu
- Phone: 855-776-0015
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.