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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
Information provided by (Responsible Party):
Istituto Clinico Humanitas

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.

Condition or disease Intervention/treatment
Colon Cancer Other: AI

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Study Type : Observational
Actual Enrollment : 700 participants
Observational Model: Cohort
Time Perspective: Prospective
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

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Colonoscopy

Group/Cohort Intervention/treatment
Artificial Intelligence colonoscopy
Other: AI
Artificial intellignece colonoscopy

White light colonoscopy

Primary Outcome Measures :
  1. 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

Information from the National Library of Medicine

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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
Study Population
Based on the observed prevalence of adenomas (35%) among patients undergoing colonoscopies at our center within the last 12 months, a sample size of 322 subjects per arm could allow for a 90% power to show the non-inferiority (primary end-point) of the AI-aided arm by excluding that the one-side 95% CI will exclude a difference of 10% in favour of the standard group. Such sample size will also have a 80% power to detect as statistical significant (α=0.05; two-sided test) a 10% absolute increase in the detection rate of adenomas in the AI-aided arm (secondary end-point).

Inclusion Criteria:

All 40-80 years-old subjects undergoing a colonoscopy.

Exclusion Criteria:

  • 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.

Information from the National Library of Medicine

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

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Endoscopy Unit, Humanitas Research Hospital
Rozzano, Milano, Italy, 20089
Sponsors and Collaborators
Istituto Clinico Humanitas
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Principal Investigator: Alessandro Repici, MD Humanitas Research Hospital
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Responsible Party: Istituto Clinico Humanitas
ClinicalTrials.gov Identifier: NCT04079478    
Other Study ID Numbers: 2363
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

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Istituto Clinico Humanitas:
Artificial Intelligence
Additional relevant MeSH terms:
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Neoplasms, Glandular and Epithelial
Neoplasms by Histologic Type