Screening and Staging of Benign vs Malignant Pelvic Abnormalities
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorMayo Clinic
About this trial
This study evaluates whether newly developed non-FDA approved image processing techniques \[Adaptive Image Reconstruction (AIR Recon) Deep Learning (DL) and Sonic DL\] can provide improved quality and decreased time compared to current scanning techniques.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
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)
Disqualifiers
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
Trial population
Healthy volunteers, patients referred for prostate MR and patients referred for endometriosis evaluation
Trial design
Design model
Case-control
Time perspective
Cross-sectional
Treatments tested in this trial
Non-Interventional Study
Other interventionNon-interventional study
Treatment groups
60 Participants
are divided into 1 treatment groupGroup A: Observational1 intervention
Trial outcomes
Primary outcomes
1
Change in image quality (healthy volunteers)
Three expert radiologists will read scans (blinded to technique) and provide qualitative feedback to score image quality for standard of care (SOC) imaging, SOC with AirRecon DL, SOC with Sonic DL, and SOC with AirRecon DL and Sonic DL. Reader scoring will use a 1-5 Likert scale (1-5; 1:poor, 5:excellent).
Time frame
Baseline2
Change in scan time
Will be considered improved if the duration of the added imaging does not exceed 10 minutes
Time frame
BaselineSponsors and contacts
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Source ClinicalTrials.gov