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NCT06059378: AI-OD

Using AI-assisted Optical Polyp Diagnosis for Diminutive Colorectal Polyps

Recruiting now NA Last updated 19 February 2025
What this trial tests

NA trial testing Artificial intelligence-assisted classification (CADx) in Artificial Intelligence in 204 participants. Currently enrolling.

Timeline
1 September 2023
Primary endpoint
1 May 2025
30 June 2025

Quick facts

Lead sponsorDaniel Von Renteln
PhaseNA
StatusRecruiting now
Study typeINTERVENTIONAL
Allocationnon randomized
Designparallel
Maskingnone
Primary purposediagnostic
Enrollment204
Start date1 September 2023
Primary completion1 May 2025
Estimated completion30 June 2025
Sites1 location across Canada

Drugs / interventions tested

Conditions studied

Sponsor

Daniel Von Renteln

Who can join

Adults 45 to 80, any sex, with Artificial Intelligence. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

This is a prospective study that is the first to implement resect and discard and diagnose and leave strategies in real-time practice using stringent documentation and adjudication by 2 expert endoscopists as the gold standard. The primary aim of this study is to show the accuracy of intracolonoscopy AI-assisted optical diagnosis (CADx; autonomous or with human input) when the AI-assisted optical diagnosis made by the expert endoscopists is used as the reference standard. The specific aims are: 1. To evaluate the accuracy of intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) by comparing it to the obtained optical histology diagnoses provided by two independent expert endoscopists as the reference standard. 2. To evaluate the agreement between the intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) and the AI-assisted optical diagnosis performed by two independent expert endoscopists. 3. To determine whether AI-assisted optical polyp diagnosis for diminutive (1-5 mm) polyps can be implemented in routine clinical practice by demonstrating that at least 70% of the approached patients are interested in undergoing AI-assisted optical diagnosis (autonomous or with human input). 4. To evaluate the cost savings resulting from replacing pathology with AI-assisted optical diagnosis.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

  1. UEG Week 2025 Oral Presentations
    · 2025

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