Comparing CADe Software for Enhanced Polyp Detection

Study Overview
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Brief Summary
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Purpose & Research Questions The purpose of this study is to evaluate whether artificial intelligence (AI) improves the detection of polyps and whether the system can classify the type and severity of detected changes. The investigators will also assess if there are any differences between the various AI systems and whether the polyps that may be missed are benign or malignant.

Detailed Description
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Materials: Selection, Representativeness, and Grouping The study is a randomized controlled clinical trial conducted at Västra Götaland region. Patients are randomized to receive either AI or conventional endoscopy, and each endoscopy unit has access to at least one AI device. Informed consent is obtained from patients before the examination. Before the examination, patients are asked if they want to participate in the study. If the patient wishes to participate, informed consent is obtained. The endoscopist then draws a slip from an envelope, determining whether conventional colonoscopy or AI will be used. During conventional colonoscopy, the patient is examined according to routine practice. After the examination, a questionnaire is filled out, recording various findings from the examination. During AI examinations, the AI system is activated only during instrument withdrawal. The system identifies polyps and alerts the endoscopist. Additionally, two of the AI systems (GI-Genius, CADEYE) have the ability to characterize the detected polyps and provide an interpretation of whether the changes are benign or malignant. After the examination, a similar questionnaire is completed as in conventional colonoscopy. Method: Data Collection Basic data will be recorded, including the reason for the examination, other illnesses, medications, demographic data such as gender, age, family history of cancer, and the time of the examination (morning or afternoon). During the examination, the following will be recorded: the number of polyps, macroscopic classification of polyps, AI system's characterization of the polyps, bowel cleansing quality, laxative method, medication during the examination, complications occurring during or after the examination. Withdrawal time is recorded, as well as the number of false-positive polyps and supplementation with histological data of polyps after review by the pathologist. Three different AI systems will be used at the various hospital sites, namely EndoAid (Olympus), CADEYE (Fujinon), and GI-Genius (Medtronic). All units will randomize each examination to either AI or non-AI.

Official Title
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Comparing CADe Software for Enhanced Polyp Detection: A Randomized Controlled Trial

Conditions
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Colonic Polyp, Colon Lesion

Intervention / Treatment
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* Device: AI


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Age > 50 years Elective colonoscopy Exclusion Criteria: Patient declines to participate in the study. Age < 50 years Emergency examinations Contraindications for biopsy/polypectomy Unprepared bowel

Ages Eligible for Study
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Minimum Age: 50 Years
Maximum Age: 90 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Diagnostic
Allocation: Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: A Randomized Controlled Trial.
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Active Comparator: CAD-EYE<br>CADx 1 | Device: AI<br>* AI system<br>|
| Active Comparator: GI-GENIUS<br>CADx 2 | Device: AI<br>* AI system<br>|
| Active Comparator: Endo-AID<br>CADe | Device: AI<br>* AI system<br>|
| No Intervention: No AI<br>No AI | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Comparison of Adenoma Detection Rates (ADR) between colonoscopies assisted by Artificial Intelligence (AI) and conventional colonoscopies without AI | The ADR is typically expressed as a percentage and is calculated using the following formula:Number of colonoscopies with adenoma detection/ Total number of colonoscopies ×100. | 40 minutes, equivalent to one endoscopy session | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| To compare the effectiveness of AI systems in characterizing polyps with conventional histology | Two of the AI systems include a characterization feature, and this assessment will be compared to conventional histology | 40 minutes, equivalent to one endoscopy session |