Nationwide Study of Artificial Intelligence in Adenoma Detection for Colonoscopy

Study Overview
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Brief Summary
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The goal of this trial is to determine whether use of a Computer Assisted Detection (CADe) programme leads to an increase in ADR for either units or individual colonoscopists, independent of setting or expertise

Detailed Description
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This is a case-control study comparing adenoma detection rate (ADR) in hospitals (and individual colonoscopists), before, during and after use with an artificial intelligence unit called GI Genius™ (GIG). GIG is a Computer-assisted detection (CADe) module that assists the human colonoscopist in real-time, by detecting and marking out polyps during colonoscopy. It has been shown to be effective in expert colonoscopists, but the effect in non-expert, general, colonoscopists is not known. The investigator wish to deploy GIG into colonoscopy through the UK using a step-wedge design. Sites will be randomly allocated a start date for GIG deployment, collecting data for four months prior to this. In this way, all sites will have the active intervention and will provide their own case-control data. (4 months collection prior to activating GIG, 4 months with GIG, 4 months afterwards without GIG) The study will concentrate on non-expert colonoscopists, to determine whether GIG can increase ADR. Patients will undergo the same colonoscopy that they would have had in any case, with no additional trial visits or interventions. There will be no alteration to the usual care pathway from the patient's perspective. If the investigator can prove GIG increases ADR in this way, it will provide support to roll out this technology routinely to improve the quality of colonoscopy nationwide.

Official Title
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Nationwide Study of Artificial Intelligence in Adenoma Detection for Colonoscopy

Conditions
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Colonic Polyp, Colonic Adenoma, Colo-rectal Cancer

Intervention / Treatment
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* Device: GI Genius (GIG)


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Any patient aged 18-85 scheduled for colonoscopy by current NHSE / British Society of Gastroenterology criteria Exclusion Criteria: Colonoscopy being performed for polyp surveillance Unable to provide informed, written consent

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 85 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| All patients<br>Patient ≥18 years old, with capacity to consent, scheduled for diagnostic colonoscopy | Device: GI Genius (GIG)<br>* GIG is an artificial intelligence unit that assists human colonoscopist in real-time to detect polyps during colonoscopy. Four months collection period prior to activating GIG, then four months with GIG, and Four months afterwards without GIG<br>* Other names: CADe;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| CADe-ADR in real world practice | The primary outcome measure will be adenoma detection rate. This will be studied across three phases: prior to use of CADe (baseline practice), while using CADe (study period) and finally after CADe (without the device in situ: washout phase). | 24 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| APC | Mean adenomas per colonoscopy (APC) | 24 months | 
| Polyp characteristics | Polyp size (mm) and location (in colonic segments) | 24 months | 
| Procedure time | Total procedure (insertion+withdrawal) and withdrawal time | 24 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Artificial Intelligence, Computer assisted detection (CADe), Colorectal cancer, Adenoma Detection Rate (ADR)