Autonomous Artificial Intelligence Versus AI Assisted Human Optical Diagnosis

NCT06543862 | Not Yet Recruiting

• 1 other identifier: 2025-12306
• Study Type: interventional
• Target: 540
• Locations: 1 country
• Sites: 1

Brief Summary

Computer-aided image-enhanced endoscopy can predict the nature of colorectal polyps with over 90% accuracy. This technology uses artificial intelligence (AI) to analyze video recordings of polyps, learning to make diagnoses in real-time. This means that doctors can get immediate predictions about small polyps during the procedure, reducing the need for separate pathology exams and saving costs, ultimately improving patient care. Human and AI interactions are complex and a framework to reap synergistic effects CADx systems when used by humans to harness optimal performance needs to be established. AI solutions in medicine are usually developed to be used as assistive devices, however, then they rely on humans to correct AI errors. Optical polyp diagnosis is a complex task. Non experts usually achieve diagnostic accuracy in 70-80%. CADx systems have a similar diagnostic accuracy when used autonomously. Clinical evaluation of CADx systems showed that CADx assisted OD performs equally to the operator performance when using non CADx assisted OD. To harness a benefit of clinical CADx implementation we would have to find a way that synergies between human and CADx come into play to eliminate cases in which CADx assisted and/ or human OD results in low diagnostic accuracy and also addresses the problem of serrated polyp recognition.

Conditions

Colonic Polyp; Artificial Intelligence

Keywords

optical diagnosis, artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Accuracy of optical diagnosis, for polyps 1-5mm, compared with an agreed upon CADx-assisted diagnosis

  Accuracy of optical diagnosis, for polyps 1-5mm, compared with an agreed upon CADx-assisted diagnosis , when histopathology results are used as the reference

  up to 100 weeks

Secondary Outcomes (6)

• Accuracy of optical diagnosis, for polyps 1-10mm, compared with an agreed upon CADx-assisted diagnosis

  up to 100 weeks

• Test characteristics, including recall, specificity, positive and negative predictive values (PPV/NPV), and particularly the NPV of rectosigmoid neoplastic polyps.

  up to 100 weeks

• Agreement of surveillance interval recommendations of AI-A and AI-H compared with the pathology-based recommendations

  up to 100 weeks

• Proportion of patients for whom an immediate surveillance recommendation can be directly provided for each approach, and how often histopathology-based polyp examination would have been avoided.

  up to 100 weeks

• Variability of OD (AI-A and AI-H) across participating endoscopists.

  up to 100 weeks

Study Arms (1)

All participants

OTHER

The endoscopist will make an optical diagnosis (OD) prediction for all small polyps (up to 10 mm) in white light (WL). Then, the endoscopist will make another OD prediction using image enhanced endoscopy (IEE) modes. After that, CADx will be activated in the IEE mode and a CADx prediction will be documented. Finally, after seeing the CADx prediction, the endoscopist will make a final prediction, which can agree or disagree with the autonomous CADx one. Polyps will be resected and sent to a pathology lab, where a pathologic diagnosis (blinded to the endoscopist's predictions) will be rendered.

Other: CADx (AI) system

Interventions

CADx (AI) system OTHER

The CADx system will be used to predict the histopathology of the polyp detected.

All participants

Eligibility Criteria

• Age: 45 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Indication for full colonoscopy.

You may not qualify if:

• Known inflammatory bowel disease
• Active colitis
• coagulopathy
• familial polyposis syndrome
• poor general health, defined as an American Society of Anesthesiologists class \>3
• emergency colonoscopy

Sponsors & Collaborators

• Centre hospitalier de l'Université de Montréal (CHUM): lead

Study Sites (1)

Ghislaine Ahoua

Montreal, Quebec, Canada

Location

MeSH Terms

Conditions

Colonic Polyps

Interventions

Drug Delivery Systems

Condition Hierarchy (Ancestors)

Intestinal Polyps; Polyps; Pathological Conditions, Anatomical; Pathological Conditions, Signs and Symptoms

Intervention Hierarchy (Ancestors)

Drug Therapy; Therapeutics

Study Officials

• Daniel von Renteln, MD

  University of Montreal Medical Center (CHUM)

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Daniel von Renteln, MD

CONTACT

514 890-8000; daniel.von.renteln.med@ssss.gouv.qc.ca

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: July 30, 2024
• First Posted: August 9, 2024
• Study Start: November 15, 2024
• Primary Completion: November 15, 2024
• Study Completion: November 15, 2024
• Last Updated: November 15, 2024

Record last verified: 2024-11

Locations

CA (1)