The EYE Study Enhancing the Diagnostic Yield of Standard Colonoscopy by Artificial Intelligence Aided Endoscopy (EYE)

August 5, 2024 updated by: Istituto Clinico Humanitas

The EYE Study: Enhancing the Diagnostic Yield of Standard Colonoscopy by Artificial Intelligence Aided Endoscopy

Colorectal cancer (CRC) remains one of the leading causes of mortality among neoplastic diseases in the world[1] . Adequate colonoscopy based CRC screening programs have proved to be the key to reduce the risk of mortality, by early diagnosis of existing CRC and detection of pre-cancerous lesions[2-4] . Nevertheless, long-term effectiveness of colonoscopy is influenced by a range of variables that make it far from a perfect tool[5]. The effectiveness of a colonoscopy mainly depends on its quality, which in turn is dependent on the skill and expertise of the endoscopist. In fact, several studies have shown a significant adenoma miss rate of 24%-35%, especially in patients with diminutive adenomas[6,7] . These data are in line with interval cancers incidence (I-CRC), defined as the percentage of cancers diagnosed after a screening program and before the intended surveillance duration, of approximately 3%-5% [8,9].

The development of the artificial intelligence (AI) applications in the medical field has grown in interest in the past decade. Its performance on increasing automatic polyp and adenoma detection has shown promising results in order to achieve an higher ADR[10]. The use of computer aided diagnosis (CAD) for detection of polyps had initially been studied in ex vivo studies but in the last few years, with the advancement in computer aided technology and emergence of deep learning algorithms, use of AI during colonoscopy has been achieved and more studies have been undertaken [10].

Recently Fujifilm (Tokyo, Japan) has developed a new technology known as "CAD-EYE" aiming to support both colonic polyp detection and characterization during colonoscopy. This technology is now available in Europe, being compatible with the latest generation of Fujifilm endoscopes (ELUXEO Fujifilm Co.).

However, the clinical impact of CAD-EYE system in improving the adenoma detection have yet to be assessed

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Actual)

1120

Phase

  • Not Applicable

Contacts and Locations

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

Study Contact

Study Locations

    • Milano
      • Rozzano, Milano, Italy, 20089
        • Department of Gastroenterology, 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

45 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

- patients aged 45 or older undergoing average risk colonoscopy (screening) or follow-up colonoscopy for previous history of polyps (surveillance interval of 3 years or greater).

Exclusion Criteria:

  • subjects with personal history of CRC, or IBD.
  • subjects affected with Lynch syndrome or Familiar Adenomatous Polyposis.
  • 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

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: WL+AI
Colonoscopy in white light and artificial intelligence
Artificial intelligence
Experimental: WL
Colonoscopy in white light
Artificial intelligence

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Adenoma per colonoscopy (APC)
Time Frame: 9 Months
APC, defined as the total number of histologically confirmed adenomas and carcinomas detected in the colonoscopy divided by the total number of colonoscopies.
9 Months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Positive predictive value (PPV)
Time Frame: 9 Months
PPV, defined as the total number of histologically confirmed adenomas and carcinomas detected during the colonoscopy, divided by the total number of excisions in the colonoscopy.
9 Months

Collaborators and Investigators

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

Sponsor

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)

January 1, 2022

Primary Completion (Actual)

December 31, 2022

Study Completion (Actual)

October 10, 2023

Study Registration Dates

First Submitted

November 18, 2021

First Submitted That Met QC Criteria

November 18, 2021

First Posted (Actual)

December 1, 2021

Study Record Updates

Last Update Posted (Actual)

August 6, 2024

Last Update Submitted That Met QC Criteria

August 5, 2024

Last Verified

July 1, 2024

More Information

Terms related to this study

Other Study ID Numbers

  • 3000

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.