Using AI-assisted Optical Polyp Diagnosis for Diminutive Colorectal Polyps

NCT ID: NCT06059378

Last Updated: 2025-02-19

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: NA
• Total Enrollment: 204 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2023-09-01
• Study Completion Date: 2025-06-30

Brief Summary

This is a prospective study that is the first to implement resect and discard and diagnose and leave strategies in real-time practice using stringent documentation and adjudication by 2 expert endoscopists as the gold standard.

The primary aim of this study is to show the accuracy of intracolonoscopy AI-assisted optical diagnosis (CADx; autonomous or with human input) when the AI-assisted optical diagnosis made by the expert endoscopists is used as the reference standard. The specific aims are:

1. To evaluate the accuracy of intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) by comparing it to the obtained optical histology diagnoses provided by two independent expert endoscopists as the reference standard.

2. To evaluate the agreement between the intracolonoscopy AI-assisted optical polyp diagnosis (autonomous or with human input) and the AI-assisted optical diagnosis performed by two independent expert endoscopists.

3. To determine whether AI-assisted optical polyp diagnosis for diminutive (1-5 mm) polyps can be implemented in routine clinical practice by demonstrating that at least 70% of the approached patients are interested in undergoing AI-assisted optical diagnosis (autonomous or with human input).

4. To evaluate the cost savings resulting from replacing pathology with AI-assisted optical diagnosis.

Detailed Description

All patients who meet the inclusion criteria can be enrolled. Eligible patients will be informed about the study through a consent form that includes information on optical diagnosis (resect and discard, diagnose and leave) and AI/CADx systems. We will ask the patients' willingness to undergo AI-assisted optical diagnosis with endoscopists' input (the first 102 patients) and automomous AI-assisted optical diagnosis (from patient 103 to 204). Subsequently, patients will be asked if they are willing to participate in the study, using AI-assisted optical diagnosis and the "resect and discard" and "diagnose and leave" strategy. If a patient declines to undergo optical diagnosis, they will be asked about the reason for their refusal to participate in the study. The options for their response include:

1. Concerns regarding undergoing an optical diagnosis.

2. Reluctance to participate in research projects in general.

3. Other reasons.

4. Preference not to answer the question.

Patients who agree to participate in the study will undergo standard colonoscopy procedures with AI-assisted optical diagnosis for all diminutive colorectal polyps identified. High-definition colonoscopes with a joint computer-assisted classification (CADx) support (CAD-EYE software EW10-EC02) will be used.

For the first 102 patients (i.e., the CAD-assisted optical diagnosis with endoscopist's input), the endoscopists will use the CAD-EYE blue light imaging (BLI) mode to enhance the visualization of polyp features. During the optical diagnosis using CADx, the most probable diagnosis (neoplastic or hyperplastic) will be displayed on the endoscopy screen. If the serrated pathology subtype is determined as the most probable histology, the endoscopists will make the final decision. They will also indicate whether their optical diagnosis was made with low or high confidence.

For the second group of 102 patients (i.e., autonomous CADx-assisted optical diagnosis), endoscopists will use CADx and BLI mode to perform optical diagnosis. Based on the CADx diagnosis, all 1-5 mm polyps diagnosed as hyperplastic or neoplastic will be resected and discarded, while those located in the rectosigmoid and diagnosed as hyperplastic will be left in the colon. When high-risk histology features are observed using BLI, in any patient, the endoscopists will inform the research assistant to document them, and the polyp will be sent for pathology examination in accordance with the ASGE PIVI guidelines recommendations. All polyps >5mm will be send for pathology evaluation. Polyp size will be measured using virtual scale technology integrated in the computer-assisted system (CAD) to ensure an accurate polyp sizing.18 A research assistant will document the characteristics of the detected polyps (i.e., location, size, morphology, AI-assisted intracolonoscopy and endoscopists optical diagnoses). All identified colorectal polyps will be removed following standard polypectomy practices. The entire colonoscopy procedures will be video recorded for quality assurance purposes. All diminutive polyps will be resected and discarded as part of the resect and discard strategy. Additionally, diminutive polyps located in the rectosigmoid colon will be detected and left in situ (diagnose and leave strategy) if no high-risk features are present.

Conditions

Artificial Intelligence

Study Design

• Allocation Method: NON_RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

AI-assisted classification with endoscopist's input

AI-assisted classification for diminutive polyps during a colonoscopy procedure using the CAD-eye detection and classification system, with input from the endoscopist in the case of serrated polyps, for patients who agree to undergo optical diagnosis of diminutive colorectal polyps.

Group Type: OTHER

Artificial intelligence-assisted classification (CADx)

Intervention Type: DEVICE

CADeye (Fujifilm, Japan) is a joint detection (CADe) and classification (CADx) AI-supported system, which has been developed utilising AI deep learning technology to support endoscopic lesion detection and characterisation in the colon.

Autonomous AI-assisted classification

AI-assisted classification for diminutive polyps during a colonoscopy procedure using the CAD-eye detection and classification system, with no input from the endoscopist, for patients who agree to undergo optical diagnosis of diminutive colorectal polyps.

Group Type: OTHER

Artificial intelligence-assisted classification (CADx)

Intervention Type: DEVICE

CADeye (Fujifilm, Japan) is a joint detection (CADe) and classification (CADx) AI-supported system, which has been developed utilising AI deep learning technology to support endoscopic lesion detection and characterisation in the colon.

Interventions

Artificial intelligence-assisted classification (CADx)

CADeye (Fujifilm, Japan) is a joint detection (CADe) and classification (CADx) AI-supported system, which has been developed utilising AI deep learning technology to support endoscopic lesion detection and characterisation in the colon.

Intervention Type: DEVICE

Other Intervention Names

CAD-eye

Eligibility Criteria

Inclusion Criteria

• Age 45-80 years
• Undergoing an outpatient colonoscopy at the Centre Hospitalier de l'Université de Montréal (CHUM)
• Signed informed consent form

Exclusion Criteria

• Inflammatory Bowel Disease;
• Active colitis;
• Hereditary CRC syndrome;
• Coagulopathy;
• American Society of Anesthesiologists (ASA) status >3

• Minimum Eligible Age: 45 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Daniel Von Renteln

OTHER

Sponsor Role: lead

Responsible Party

Daniel Von Renteln

Gastroenterologist, MD

Responsibility Role: SPONSOR_INVESTIGATOR

Principal Investigators

Daniel von Renteln, MD

Role: PRINCIPAL_INVESTIGATOR

Centre hospitalier de l'Université de Montréal (CHUM)

Locations

Centre Hospitalier de l'Université de Montréal

Montreal, Quebec, Canada

Site Status: RECRUITING

Countries

Canada

Facility Contacts

Julie Fleury

Role: primary

julie.fleury.chum@ssss.gouv.qc.ca

514-890-8000 ext. 30917

Other Identifiers

2024-11557/23.095

Identifier Type: -

Identifier Source: org_study_id