Improving Polyp Detection Rate by Artificial Intelligence in Colonoscopy

Not Applicable

Recruiting

• Conditions: Colonic Polyp
• Interventions: Device: Standard white light colonoscope; Device: GI Genius

• Registration Number: NCT05322993
• Lead Sponsor: Haraldsplass Deaconess Hospital

Brief Summary

The aim of this study is to investigate if the use of artificial intelligence (AI) in colonoscopy improves the polyp detection rate, and if the use of AI has a learning effect.

Detailed Description

The endoscopists will use GI Genius from Medtronic, a device that uses artificial intelligence (AI) based on machine learning to detect polyps in the colon in real time during colonoscopy. The device interprets the endoscopy pictures and superimposes possible polyps with frames.

The patients will be included in regular outpatient clinics in Western Norway. The endoscopists will be divided into groups depending on their experience. The endoscopists will perform colonoscopies in three phases; (1) before the use of AI, (2) during the use of AI and (3) after the use of AI. The investigators will then evaluate the polyp detection rate (PDR) in the three phases to see if AI increases PDR, and if there is a learning effect on PDR after the use of AI. The investigators will also evaluate if there is a difference in the learning-effect from AI-use depending on if the endoscopist is experienced or inexperienced.

The PDR's are registered as part of Norway's national quality register of colonoscopy, Gastronet. The data registered in Gastronet can also help the investigators evaluate other outcomes such as withdrawal time, bowel preparation, patient reported pain, patient satisfaction and complications.

Study Timeline

• Study Start: 2021-11-19
• Study First Submitted: 2022-04-04
• Study First Submitted QC: 2022-04-04
• Study First Posted: 2022-04-12
• Status Verified: 2023-10
• Last Update Submitted: 2024-01-30
• Last Update Posted: 2024-02-01
• Primary Completion: 2024-06-30
• Study Completion: 2024-12-31

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 4500

Inclusion Criteria

• Patients coming to outpatient clinics to perform colonoscopies

Exclusion Criteria

• Total colectomy
• Reservation against registration in Gastronet, the national quality register for colonoscopy in Norway

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: CROSSOVER

Arm && Interventions

Group	Intervention	Description
Without artificial intelligence	Standard white light colonoscope	Use of standard colonoscopy equipment without GI Genius.
With artificial intelligence (AI)	GI Genius	Use of GI Genius artificial intelligence device during colonoscopy.

Primary Outcome Measures

Name	Time	Method
PDR after the use of AI, is there a learning effect?	18 months	Evaluate if there is an improved PDR after the use of AI
Polyp detection rate (PDR) with and without artificial intelligence (AI)	18 months	Evaluate the PDR with and without the use of GI Genus artificial intelligence

Secondary Outcome Measures

Name	Time	Method
Complications	24 months	To evaluate if there are more registered complications with the use of AI
Withdrawal time	18 months	To evaluate if the withdrawal time is influenced by the use of artificial intelligence

Trial Locations

Locations (3)

Kanalspesialistene AS; 🇳🇴 Bergen, Vestland, Norway

Haukeland University Hospital; 🇳🇴 Bergen, Vestland, Norway

Haraldsplass Deaconess Hospital; 🇳🇴 Bergen, Vestland, Norway