An observational study in Cholecystitis, sponsored by University of Massachusetts, Worcester. Completed at 1 site in United States. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-03-17.
Sponsored by University of Massachusetts, Worcester · Observational
Lumen apposing metal stents are now being used to help patients who suffer from cholecystitis (infection of the gallbladder), especially in cases where patients are not candidates for surgery. Lumen apposing metal stents are effective for draining the gallbladder, however, placement is technically challenging. Scientists have developed an artificial intelligence to aid doctors in the deployment of these stents into the gallbladder. The aim of this study is test the performance of an artificial intelligence in providing physicians accurate information for gallbladder drainage.
266 studies on the registry are indexed under Cholecystitis; 46 are open to participants now.
This study's enrollment of 38 is below the median of 200 across 90 observational studies indexed under Cholecystitis.
Browse Cholecystitis studies →University of Massachusetts, Worcester is the lead sponsor of 288 studies on the registry; 54 are open to participants now.
Of its 25 completed or terminated interventional studies of FDA-regulated products, 18 (72%) have results posted.
Counted across the registry records on this site, refreshed daily.
Patients undergoing endoscopic ultrasound who have a gallbladder present
Exclusion Criteria:
Accuracy of the EUS AI system in providing a recommendation (i.e. whether it is safe or not to drain the gallbladder)
An expert endoscopist will perform the endoscopic ultrasound procedure. When the gallbladder comes into view the expert will comment as to whether they believe that the gallbladder is safe to drain. The expert will be blinded to the AI computers interpretation of the view of the gallbladder. A second observer will record what the AI recommended at the time of the blinded expert. The expert will be considered the "gold standard" and the outcome will be accuracy of the AI in mimicking the experts recommendations.
Time frame: Day 1
Plan to share: Yes — Other researchers can reach out to UMass Chan to obtain deidentified data on a case-by-case basis.
Supporting information: Study protocol, Sap
No publications or documents are linked to this record.
This study is completed, as verified in Mar 2026. You cannot join it, but the record below documents what was studied.
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University of Massachusetts, Worcester