The AID Study: Artificial Intelligence for Colorectal Adenoma Detection (AID)
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|ClinicalTrials.gov Identifier: NCT04079478|
Recruitment Status : Completed
First Posted : September 6, 2019
Last Update Posted : February 12, 2020
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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.
|Condition or disease||Intervention/treatment|
|Colon Cancer||Other: AI|
|Study Type :||Observational|
|Actual Enrollment :||700 participants|
|Official Title:||The AID Study: Artificial Intelligence for Colorectal Adenoma Detection|
|Actual Study Start Date :||September 25, 2019|
|Actual Primary Completion Date :||December 31, 2019|
|Actual Study Completion Date :||December 31, 2019|
Artificial Intelligence colonoscopy
Artificial intellignece colonoscopy
White light colonoscopy
- Additional diagnostic yield obtained by AI-aided colonoscopy to the yield obtained by the Standard (high-definition) colonoscopy [ Time Frame: 3 Months ]To compare the additional diagnostic yield obtained by AI-aided colonoscopy to the yield obtained by the Standard (high-definition) colonoscopy
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|Ages Eligible for Study:||40 Years to 80 Years (Adult, Older Adult)|
|Sexes Eligible for Study:||All|
|Accepts Healthy Volunteers:||No|
|Sampling Method:||Non-Probability Sample|
All 40-80 years-old subjects undergoing a colonoscopy.
- subjects with personal history of CRC, or IBD.
- patients with inadequate bowel preparation (defined as Boston Bowel Preparation Scale > 2 in any colonic segment).
- patients with previous colonic resection.
- patients on antithrombotic therapy, precluding polyp resection.
- patients who were not able or refused to give informed written consent.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04079478
|Endoscopy Unit, Humanitas Research Hospital|
|Rozzano, Milano, Italy, 20089|
|Principal Investigator:||Alessandro Repici, MD||Humanitas Research Hospital|
|Responsible Party:||Istituto Clinico Humanitas|
|Other Study ID Numbers:||
|First Posted:||September 6, 2019 Key Record Dates|
|Last Update Posted:||February 12, 2020|
|Last Verified:||February 2020|
|Individual Participant Data (IPD) Sharing Statement:|
|Plan to Share IPD:||No|
|Studies a U.S. FDA-regulated Drug Product:||No|
|Studies a U.S. FDA-regulated Device Product:||No|
Neoplasms, Glandular and Epithelial
Neoplasms by Histologic Type