Real-time Diagnosis of Diminutive Colorectal Polyps Using AI

NCT05349110 | Unknown

• 1 other identifier: METC2021-3036
• Study Type: observational
• Target: 105
• Locations: 1 country
• Sites: 2

Brief Summary

Correct endoscopic prediction of the histopathology and differentiation between benign, pre-malignant, and malignant colorectal polyps (optical diagnosis) remains difficult. Artificial intelligence has great potential in image analysis in gastrointestinal endoscopy. Aim of this study is to investigate the real-time diagnostic performance of AI4CRP for the classification of diminutive colorectal polyps, and to compare it with the real-time diagnostic performance of commercially available CADx systems.

Conditions

Colorectal Neoplasms; Colorectal Polyp

Keywords

Artificial intelligence; Computer-aided diagnosis (CADx)

Outcome Measures

Primary Outcomes (8)

• Technical feasibility of real-time use of AI4CRP.

  The technical feasibility of real-time use of AI4CRP in the endoscopy suite regarding a proper reception of the video output from the local endoscopy processor towards AI4CRP (in high definition quality, without any delays in time).

  6 months

• User interface feasibility of real-time use of AI4CRP.

  The user interface feasibility of real-time use of AI4CRP in the endoscopy suite regarding a correct alignment of the user interface of AI4CRP with the video output from the local endoscopy system (resizing image pixels and anonymization).

  6 months

• The diagnostic accuracy of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).

  The real-time diagnostic accuracy of AI4CRP per image modality (HDWL, BLI, LCI, i-scan). Diagnostic accuracy defined as the percentage of correctly optically diagnosed colorectal polyps.

  1 year

• The sensitivity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).

  The real-time sensitivity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).

  1 year

• The specificity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).

  The real-time specificity of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).

  1 year

• The negative predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).

  The real-time negative predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).

  1 year

• The positive predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).

  The real-time positive predictive value of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).

  1 year

• The Area Under ROC Curve (AUC) of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).

  The real-time Area Under ROC Curve (AUC) of AI4CRP per image modality (HDWL, BLI, LCI, i-scan).

  1 year

Secondary Outcomes (21)

• The diagnostic accuracy of AI4CRP per polyp.

  1 year

• The sensitivity of AI4CRP per polyp.

  1 year

• The specificity of AI4CRP per polyp.

  1 year

• The negative predictive value of AI4CRP per polyp.

  1 year

• The positive predictive value of AI4CRP per polyp.

  1 year

Study Arms (1)

Gastroenterology patients

Patient receiving a colonoscopy because of regular care will be considered eligible for inclusion if at least one diminutive colorectal polyp is encountered during the colonoscopy. Patients receive an endoscopic procedure in the context of the Dutch national screening program, because of gastrointestinal symptoms, or because of follow-up of previously diagnosed bowel diseases. Colonoscopies will be executed using Fujifilm endoscopy systems (Fujifilm® Corporation, Tokyo, Japan), using Pentax endoscopy systems (Pentax Medical®, Hamburg, Germany), and using Olympus endoscopy systems (Olympus®, Tokyo, Japan).

Device: Computer-aided diagnosis (CADx) systems

Interventions

Computer-aided diagnosis (CADx) systems DEVICE

* AI4CRP (artificial intelligence for colorectal polyps), a CNN based computer-aided diagnosis system for diagnosis of colorectal polyps (COMET-OPTICAL research group); * CAD EYE, a computer-aided diagnosis system for diagnosis of colorectal polyps (Fujifilm® Corporation, Tokyo, Japan).

Also known as: AI4CRP, artificial intelligence for colorectal polyps (COMET-OPTICAL research group), CAD EYE (Fujifilm® Corporation, Tokyo, Japan)

Gastroenterology patients

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patient receiving a colonoscopy because of regular care will be considered eligible for inclusion if at least one diminutive colorectal polyp is encountered during the colonoscopy. Patients receive an endoscopic procedure in the context of the Dutch national screening program, because of gastrointestinal symptoms, or because of follow-up of previously diagnosed bowel diseases.

You may qualify if:

• Age \>18 years;
• Patients with at least one colorectal polyps encountered during colonoscopy;
• Patients referred for a colonoscopy by the Dutch bowel cancer screening program, patients undergoing a colonoscopy for endoscopic surveillance, or patients undergoing a colonoscopy because of complaints;
• Written informed consent.

You may not qualify if:

• Patients with prior history of inflammatory bowel diseases (IBD) or polyposis syndromes;
• Patients with inadequate bowel preparations after adequate washing, suctioning, and cleaning manoeuvres have been performed by the endoscopist;
• Patients undergoing an emergency colonoscopy;
• Written objection in the patient file for participation in scientific research.

Sponsors & Collaborators

• Maastricht University Medical Center: lead
• Catharina Ziekenhuis Eindhoven: collaborator
• Eindhoven University of Technology: collaborator

Study Sites (2)

Maastricht University Medical Center

Maastricht, Limburg, 6202AZ, Netherlands

RECRUITING

Catharina Ziekenhuis Eindhoven

Eindhoven, North Brabant, 5623 EJ, Netherlands

COMPLETED

MeSH Terms

Conditions

Colorectal Neoplasms

Interventions

Diagnosis, Computer-Assisted; Drug Delivery Systems

Condition Hierarchy (Ancestors)

Intestinal Neoplasms; Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Colonic Diseases; Intestinal Diseases; Rectal Diseases

Intervention Hierarchy (Ancestors)

Diagnosis; Drug Therapy; Therapeutics

Study Officials

• Erik Schoon, Prof Dr MD

  Maastricht Universitair Medisch Centrum

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Quirine van der Zander, Drs MD

CONTACT

031433882241; q.vanderzander@maastrichtuniversity.nl

Erik Schoon, Prof Dr MD

CONTACT

031433882241; erik.schoon@catharinaziekenhuis.nl

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: March 31, 2022
• First Posted: April 27, 2022
• Study Start: August 20, 2021
• Primary Completion: September 1, 2022
• Study Completion: December 1, 2022
• Last Updated: May 5, 2022

Record last verified: 2022-04

Locations

NL (2)