Computer Aided Diagnosis of Colorectal Polyps

Study Overview
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Brief Summary
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The purpose of this study is to assess whether computer aided technology (CAD) can help in the diagnosis of polyps found the bowel compared with visual inspection alone and therefore whether it is beneficial in helping clinicians to decide whether to remove a polyp or not. Presently, most endoscopists remove all polyps found and send them to the laboratory for testing. The number of colonoscopies is increasing, meaning that more polyps are detected and removed. This comes at a significant cost to the health service and increases the time taken to complete a colonoscopy.

Detailed Description
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Removing precancerous polyps from the bowel during a colonoscopy (camera test) is the cornerstone of colorectal cancer screening and prevents polyps developing into bowel cancer. Most polyps develop in the rectosigmoid colon (lower part of the bowel). Many polyps never grow into cancer and it can be difficult for the clinicians performing the procedure (endoscopists) to tell which ones are precancerous. This means many polyps are removed unnecessarily, with a considerable waste of resources. A recent preliminary study indicates a novel artificial intelligence system (EndoBRAIN) for computer-aided diagnosis may be able to distinguish different types of polyps during colonoscopy and therefore help doctors decide which polyps to remove. This study aims to compare the in accuracy of artificial intelligence against the endoscopist's assessment for diagnosis of diminutive (<5mm) polyps in the lower colon. Patients who are age 18 years or older who undergo colonoscopy for any indication at the participating clinical centres and are diagnosed with diminutive rectosigmoid polyps are eligible for study enrolment. For each detected polyp in the rectosigmoid colon, endoscopists will assess the polyp type using standard colonoscopies (cameras) and then with the use of the EndoBRAIN technology. The polyps will be removed and sent to the laboratory for testing. The difference between clinician diagnosis and EndoBRAIN diagnosis will be compared with the laboratory findings. We hypothesize that the EndoBRAIN technology provides a superior accuracy in identifying precancerous rectosigmoid polyps, compared to endoscopist's own prediction with a standard colonoscope. If the trial confirms the superior accuracy of the EndoBRAIN system, polyps classified as non-cancerous with the EndoBRAIN system no longer need to be removed, meaning a large gain for patients and society, due to significantly less polypectomies and pathology reviews.

Official Title
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Real-Time Artificial Intelligence Aided Diagnosis of Colorectal Polyps During Colonoscopy: A Clinical Trial With the EndoBRAIN Technology

Conditions
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Colonic Polyp, Colorectal Cancer

Intervention / Treatment
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* Diagnostic Test: Endobrain, Computer Aided Diagnosis (CAD)


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Individuals 18 years or older who are scheduled for screening, surveillance, diagnostic, or therapeutic colonoscopy at at King's College Hospital with diminutive rectosigmoid polyps. Exclusion Criteria: Diminutive polyps with known histology Inflammatory bowel disease Polyposis syndrome (e.g., familial adenomatous polyposis, serrated polyposis) History of chemotherapy or radiation therapy for colorectal lesions Inability to undergo polypectomy (e.g. intake of anticoagulants, comorbidities, or patient refusal) Pregnancy

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 90 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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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Treatment Group<br>All patients will undergo CAD of any diminutive polyps found in the rectosigmoid on colonoscopy | Diagnostic Test: Endobrain, Computer Aided Diagnosis (CAD)<br>* Artificial intelligence<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| True positive adenoma detection rate | True positive adenoma detection rate with visual inspection versus true positive adenoma detection rate with visual inspection plus CAD | 6 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| True negative adenoma detection rate | True negative adenoma detection rate with visual inspection versus true negative adenoma detection rate with visual inspection plus CAD | 6 months | 
| To estimate the sensitivity, specificity, of visual inspection and the use of the EndoBRAIN CAD technology | To estimate the sensitivity, specificity, of visual inspection and the use of the EndoBRAIN CAD technology | 6 months | 
| To estimate the positive predictive value [PPV], and NPV of the combination of visual inspection and the use of the EndoBRAIN CAD technology | To estimate the positive predictive value [PPV], and NPV of the combination of visual inspection and the use of the EndoBRAIN CAD technology | 6 months | 
| To estimate the percentage of diminutive colorectal polyps from which endocytoscopic images can be successfully captured (acquisition rate). | To estimate the percentage of diminutive colorectal polyps from which endocytoscopic images can be successfully captured (acquisition rate). | 6 months | 
| To estimate the rate of high-confidence diagnosis with EndoBRAIN as compared to visual polyp inspection alone. | To estimate the rate of high-confidence diagnosis with EndoBRAIN as compared to visual polyp inspection alone. | 6 months | 
| Time of colonoscopy | Time of colonoscopy to be recorded. | during procedure | 
| Complications | complications to be recorded. | 6 months |