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Clinical Trial Summary

The aim of this study is to evaluate the clinical benefit and safety of using an AI device in colonoscopy procedures with the indication of screening or surveillance.


Clinical Trial Description

Colorectal cancer is the second most common cause of cancer related mortality in the U.S., and affecting 150,000 people annually. Colonoscopy is the gold standard for the screening and detection of colorectal polyps and cancers. Screening for colorectal cancer has been shown to be effective in reducing both incidence and mortality. The capability of colonoscopy as an effective screening tool is based on the accurate detection and removal of precancerous polyps. However, it has been documented in several tandem colonoscopy studies that up to 28% of colorectal polyps are missed. Detection and identification of adenomatous polyps is provider dependent, as evidenced by the large variability in adenoma detection rates between providers.

Additionally, procedural factors, such as poor bowel preparation, and histomorphological qualities, such as those of serrated polyps, can impact a clinician's ability to detect and characterize polyps. Iterative Scopes has developed a computer aided detection (CADe) or AI model that can identify colorectal polyps in real-time during colonoscopy. The Iterative Scopes AI model analyzes video digital images taken during endoscopy and then directs the gastroenterologist's attention to areas of interest on the colon wall.

The purpose of this study is to evaluate the health benefits and safety in using the AI device during screening and surveillance colonoscopy. One of the reasons for the development of interval colorectal cancers is polyps missed during colonoscopy. Our hypothesis is that with the aid of AI device, the adenomas detected per colonoscopy will increase, and it is plausible to believe that this increase in detection could reduce the incidence of interval cancers. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT04149184
Study type Interventional
Source University of Minnesota
Contact Aasma Shaukat, MD, MPH
Phone 612-208-1570
Email shaukat@umn.edu
Status Recruiting
Phase N/A
Start date October 1, 2019
Completion date December 31, 2020

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