Clinical trial NCT05322993: Improving Polyp Detection Rate by Artificial Intelligence in Colonoscopy
Official title: Improving Polyp Detection Rate by Artificial Intelligence in Colonoscopy
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Colonic Polyp
Keywords: Colonoscopy
Artificial intelligence
Polyp detection
Lead sponsor: Haraldsplass Deaconess Hospital
Sponsor class: OTHER
Collaborators: name: Haukeland University Hospital
name: European Society of Gastrointestinal Endoscopy
name: Kanalspesialistene AS
First posted: 2022-04-12
Enrollment: 4500
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NON_RANDOMIZED
Intervention model: CROSSOVER
Intervention model description: Endoscopists will perform colonoscopies in three consecutive phases; 1. without artificial intelligence (AI), 2. with AI, 3. without (AI).
Primary purpose: DIAGNOSTIC

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.

Eligibility criteria: 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

Primary outcomes:
measure: Polyp detection rate (PDR) with and without artificial intelligence (AI)
timeFrame: 18 months
measure: PDR after the use of AI, is there a learning effect?
timeFrame: 18 months
Secondary outcomes:
measure: Withdrawal time
timeFrame: 18 months
measure: Complications
timeFrame: 24 months
Other outcomes:
Locations:
city: Bergen
country: Norway
facility: Haraldsplass Deaconess Hospital
state: Vestland
city: Bergen
country: Norway
facility: Haukeland University Hospital
state: Vestland
city: Bergen
country: Norway
facility: Kanalspesialistene AS
state: Vestland
Study officials:
affiliation: Helse Bergen
name: Roald F. Havre, Professor
role: STUDY_DIRECTOR
References: