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Brief Title: The AID Study: Artificial Intelligence for Colorectal Adenoma Detection
Official Title: The AID Study: Artificial Intelligence for Colorectal Adenoma Detection
Study ID: NCT04079478
Brief Summary: Colonoscopy is clinically used as the gold standard for detection of colon cancer (CRC) and removal of adenomatous polyps. Despite the success of colonoscopy in reducing cancer-related deaths, there exists a disappointing level of adenomas missed at colonoscopy. "Back-to-back" colonoscopies have indicated significant miss rates of 27% for small adenomas (\< 5 mm) and 6% for adenomas of more than 10 mm in diameter. Studies performing both CT colonography and colonoscopy estimate that the colonoscopy miss rate for polyps over 10 mm in size may be as high as 12%. The clinical importance of missed lesions should be emphasized because these lesions may ultimately progress to CRC8. Limitations in human visual perception and other human biases such as fatigue, distraction, level of alertness during examination increases such recognition errors and way of mitigating them may be the key to improve polyp detection and further reduction in mortality from CRC. In the past years, a number of CAD systems for detection of polyps from endoscopy images have been described. However, the benefits of traditional CAD technologies in colonoscopy appear to be contradictory, therefore they should be improved to be ultimately considered useful. Recent advances in artificial intelligence (AI), deep learning (DL), and computer vision have shown potential to assist polyp detection during colonoscopy.
Detailed Description:
Minimum Age: 40 Years
Eligible Ages: ADULT, OLDER_ADULT
Sex: ALL
Healthy Volunteers: No
Endoscopy Unit, Humanitas Research Hospital, Rozzano, Milano, Italy
Name: Alessandro Repici, MD
Affiliation: Humanitas Research Hospital
Role: PRINCIPAL_INVESTIGATOR