Evaluation of ArTificial Intelligence System (Gi-Genius) for adenoMa dEtection in Lynch Syndrome.

Study Overview
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Brief Summary
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The purpose of this study is to assess if artificial intelligence aid colonoscopy colonoscopy is superior to conventional colonoscopy for the detection of adenomas during surveillance colonoscopy in patients with Lynch syndrome.

Detailed Description
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To compare the performance of white-light colonoscopy (HD-WLE) versus white-light + CAD (CAD) for detection of adenomas (1:1 ratio). The CAD system will include an artificial intelligence-based medical device (GI Genius, Medtronic) trained to process colonoscopy images and superimpose them, in real time, on the endoscopy display as a green box over suspected lesion. An adequate bowel preparation and minimum withdrawal time of 6 min will be required. Colonoscopies will be performed by experienced endoscopists and with high-definition scopes. Lesions will be collected, and histopathology findings used as the reference standard. The primary outcome of this trial will be the mean number of adenomas per colonoscopy (APC).

Official Title
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Evaluation of ArTificial Intelligence System (Gi-Genius) for adenoMa dEtection in Lynch Syndrome. A Randomized, Parallel, Multicenter, Controlled Trial. TIMELY Study.

Conditions
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Lynch Syndrome

Intervention / Treatment
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* Device: Gi Genius, Medtronic
* Other: White light standart colonoscopy


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Age ≥18 years with a proven pathogenic germline variant in one of the MMR genes (MLH1, MSH2, MSH6) or Epcam deletion who are under surveillance colonoscopy. Exclusion Criteria: Previous history of total colectomy, Concomitant inflammatory bowel disease, Inability or refuse to sign the informed consent, Previous colonoscopy < 12 months. Inadequate bowel preparation. Incomplete procedure. PMS2 mutation carriers

Ages Eligible for Study
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Minimum Age: 18 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
Masking: Double


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Active Comparator: CAD arm<br>Patients allocated to CAD arm will receive during colonoscopy withdrawal high definition white light endoscopy aided with artificial intelligence device (Gi Genius, Medtronic) | Device: Gi Genius, Medtronic<br>* GI geniusTM (Medtronic) is an artificial intelligence device designed and validated on a dataset of white-light endoscopy videos from high-quality randomized controlled trials for the detection of colorectal lesions during colonoscopy. Based on a deep learning system using convolutional neural networks, GI genius works in real-time side-to-side with the gastroenterologist during colonoscopy highlighting the presence of precancerous lesions with a visual marker (green box) in real time and designed to be integrated with the majority of colonoscopies.<br>|
| Placebo Comparator: WLE arm<br>Patients allocated to WLE arm will receive during colonoscopy withdrawal high definition white light endoscopy as standart of care. | Other: White light standart colonoscopy<br>* High definition white light endoscopy will be used during the scope withdrawal<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Mean number of adenomas per colonoscopy | Compare mean number of adenomas in both arms calculated by dividing the total number of adenomas detected by the total number of colonoscopies in each arm | 18 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Withdrawal time | time spent on inspection, from the cecum to endoscope extraction through the anus, excluding the time needed for therapeutic measures (including polypectomy). | 18 months | 
| Mean number of polyps per colonoscopy | Compare mean number of polyps in both arms calculated by dividing the total number of polyps (including serrated lesions and adenomas) detected by the total number of colonoscopies in each arm | 18 months | 
| Adenoma detection rate | proportion of individuals undergoing a complete colonoscopy who had at least one adenoma detected between two arms. | 18 months | 
| Polyp detection rate | proportion of individuals undergoing a complete colonoscopy who had at least one polyp detected between two arms. | 18 months | 
| False positives in CAD arm | Combination of: Lesions detected by CAD (>2s green box) after an adequate inspection with a high confidence optical diagnosis negative for neoplasia made by the endoscopist. Lesions detected by CAD (>2s green box) after an adequate inspection resected by the endoscopist and with a clinically non-significant histology. | 18 months | 
| Mean number of non-clinically significant removed lesions | Lesions removed and with a histology of normal or inflammatory mucosa or removed diminutive recto-sigmoid polyps with a histology of hyperplastic | 18 months | 
| Subjective endoscopist measures | Questionary addresing the easiness and satisfaction of the procedure, detection of lesions and performance of artificial intelligence will be filled in by each endoscopist | 18 months |