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Nationwide Study of Artificial Intelligence in Adenoma Detection for Colonoscopy

Nationwide Study of Artificial Intelligence in Adenoma Detection for Colonoscopy

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05870332
Acronym
NAIAD
Enrollment
4000
Registered
2023-05-23
Start date
2023-10-16
Completion date
2025-05-31
Last updated
2024-03-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Colonic Adenoma, Colonic Polyp, Colo-rectal Cancer

Keywords

Artificial Intelligence, Computer assisted detection (CADe), Colorectal cancer, Adenoma Detection Rate (ADR)

Brief summary

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

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.

Interventions

DEVICEGI Genius (GIG)

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

Sponsors

Medtronic
CollaboratorINDUSTRY
National Institute for Health Research, United Kingdom
CollaboratorOTHER_GOV
King's College Hospital NHS Trust
Lead SponsorOTHER

Study design

Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 85 Years
Healthy volunteers
Yes

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

Design outcomes

Primary

MeasureTime frameDescription
CADe-ADR in real world practice24 monthsThe 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).

Secondary

MeasureTime frameDescription
APC24 monthsMean adenomas per colonoscopy (APC)
Polyp characteristics24 monthsPolyp size (mm) and location (in colonic segments)
Procedure time24 monthsTotal procedure (insertion+withdrawal) and withdrawal time

Countries

United Kingdom

Contacts

Primary ContactProf Bu'Hussain B Hayee, PHD FRCP
b.hayee@nhs.net02032996044
Backup ContactDr Olaolu Olabintan, MBBS MRCP
olaolu.olabintan@nhs.net07939056819

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026