The AID Study: Artificial Intelligence for Colorectal Adenoma Detection (AID)

February 11, 2020 updated by: Istituto Clinico Humanitas

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.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Actual)

700

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Italy
    • Milano
      • Rozzano, Milano, Italy, 20089
        • Endoscopy Unit, Humanitas Research Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

40 years to 80 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

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).

Description

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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Control
White light colonoscopy
AI
Artificial Intelligence colonoscopy
Other: AI
Artificial intellignece colonoscopy

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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
3 Months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Istituto Clinico Humanitas

Investigators

  • Principal Investigator: Alessandro Repici, MD, HUMANITAS Research Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

September 25, 2019

Primary Completion (Actual)

December 31, 2019

Study Completion (Actual)

December 31, 2019

Study Registration Dates

First Submitted

September 3, 2019

First Submitted That Met QC Criteria

September 3, 2019

First Posted (Actual)

September 6, 2019

Study Record Updates

Last Update Posted (Actual)

February 12, 2020

Last Update Submitted That Met QC Criteria

February 11, 2020

Last Verified

February 1, 2020

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2363

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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