Artificial Intelligence in the Detection of Right Sided Colonic Polyp in Different Operator Experience

Study Overview
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Brief Summary
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Colonoscopy is the gold standard modality for the detection of colonic polyp. However, miss polyp occurs especially in right sided colon. Artificial intelligence (AI) is one of the modality to improve polyp detection but the benefit of AI in operators with different endoscopic experience is still limited. This study aimed to evaluate the efficacy of AI in the detection of right sided colonic polyp in operators with different endoscopic experience by using double insertion of right side colon, back-to-back basis.

Official Title
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Efficacy of Artificial Intelligence in the Detection of Right Sided Colonic Polyp in Operators With Different Endoscopic Experience: A Randomized Control Trial

Conditions
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Colon Polyp

Intervention / Treatment
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* Device: Artificial intellegence. CADe syste,
* Device: control


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: participants age 40-80 years Exclusion Criteria: History of colonic surgery (except appendectomy) Lower gastrointestinal bleeding unstable vital sign during endoscopy of pregnancy history of inflammatory bowel disease, polyposis syndrome, colon cancer, colonic stricture, abnormal coaglulation, organ failure

Ages Eligible for Study
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Minimum Age: 40 Years
Maximum Age: 80 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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Design Details

Primary Purpose: Screening
Allocation: Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: Patients randomized to 4 arms: control with experienced operator, control with beginner operator, AI with experienced operator, AI with beginner operator
Masking: Single


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Active Comparator: control, experienced<br>Patients received colonoscopy with double insertion of right sided colon under white light by experienced endoscopist | Device: control<br>* The patient received endoscopy under conventional white light for polyp detection during second endoscopic withdrawal.<br>|
| Active Comparator: control, beginner<br>Patients received colonoscopy with double insertion of right sided colon under white light by beginner endoscopist | Device: control<br>* The patient received endoscopy under conventional white light for polyp detection during second endoscopic withdrawal.<br>|
| Experimental: AI, experience<br>Patients received colonoscopy with double insertion of right sided colon under AI by experienced endoscopist | Device: Artificial intellegence. CADe syste,<br>* The patient received endoscopy under CADe system for polyp detection during second endoscopic withdrawal.<br>|
| Experimental: AI, beginner<br>Patients received colonoscopy with double insertion of right sided colon under AI by beginner endoscopist | Device: Artificial intellegence. CADe syste,<br>* The patient received endoscopy under CADe system for polyp detection during second endoscopic withdrawal.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| polyp detection rate | the number of polyp detected during endoscopy | during endoscopy | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| type of polyp | the type of polyp detected during endoscopy | during endoscopy | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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colon polyp, artificial intellegence, colonoscopy