Colonic Diseases
Conditions
Brief summary
The purpose of this project is to examine the role of machine learning and computer aided diagnostics in automatic polyp detection and to determine in real-time how a computer-aided detection (CADe) algorithm will perform when compared to standard screening or surveillance colonoscopy alone. Design will be a multi-center, prospective, unblinded randomized tandem colonoscopy study. 196 patients referred for either screening or surveillance colonoscopy will be included.
Interventions
colonoscopy without automated polyp detection software
automated polyp detection software
Sponsors
Study design
Eligibility
Inclusion criteria
* Patients presenting to the endoscopy unit for a screening colonoscopy or a surveillance colonoscopy * Willingness to undergo tandem colonscopies with and without the use of computer-aided software while undergoing conventional colonoscopy with sedation * Ability to provide written, informed consent (approved by IRB) and understand the responsibilities of trial participation
Exclusion criteria
* People with diminished cognitive capacity * Patients undergoing diagnostic colonoscopy (e.g. as an evaluation for active GI bleed) * Patients with incomplete colonoscopies (those where endoscopists did not successfully intubate the cecum due to technical difficulties or poor bowel preparation) * Patients that have standard contraindications to colonoscopy in general (e.g. documented acute diverticulitis, fulminant colitis and known or suspected perforation). * Patients with inflammatory bowel disease * Patients referred for endoscopic mucosal resection (EMR)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Number of adenomas detected in combination technique compared to adenomas detected in standard technique Measured by Adenoma Miss Rate (AMR) | 1 Year | AMR will be calculated as the number of adenomas detected on the second pass or portion in either group divided by the total number of adenomas detected during both passes. |
Countries
United States