Colonic Polyp
Conditions
Keywords
Colonoscopy, Artificial intelligence, Polyp detection
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.
Interventions
DEVICEGI Genius
The use of artificial intelligence during colonoscopy to improve polyp detection.
DEVICEStandard white light colonoscope
Standard colonoscopy.
Sponsors
Haraldsplass Deaconess Hospital
Haukeland University Hospital
European Society of Gastrointestinal Endoscopy
Kanalspesialistene AS
Study design
Allocation
NON_RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
DIAGNOSTIC
Masking
NONE
Intervention model description
Endoscopists will perform colonoscopies in three consecutive phases; 1. without artificial intelligence (AI), 2. with AI, 3. without (AI).
Eligibility
Sex/Gender
ALL
Healthy volunteers
Yes
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| 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 |
| 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 |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Withdrawal time | 18 months | To evaluate if the withdrawal time is influenced by the use of artificial intelligence |
| Complications | 24 months | To evaluate if there are more registered complications with the use of AI |
Countries
Norway
Contacts
STUDY_DIRECTORRoald F. Havre, Professor
Helse Bergen
Outcome results
None listed