Interest of Artificial Intelligence in Cancer Screening Colonoscopy (IA COLO)

University Hospital of Bordeaux

Status: Completed

Conditions: Deep Learning; Intestinal Polyps; Colorectal Neoplasms; Colonoscopy

Treatments: Device: screening colonoscopy

Study type: Interventional

Funder types: Other

Identifiers

NCT04921488

CHUBX 2020/46

Details and patient eligibility

About

Artificial Intelligence (AI) to predict the histology of polyps per colonoscopy, offers a promising solution to reduce variation in colonoscopy performance. This new and innovative non-invasive technology will improve the quality of screening colonoscopies, and reduce the costs of colorectal cancer screening. The aim of the study is to performed a cross-sectional, multi-center study evaluating the diagnostic performance of the CAD EYE automatic characterization system for the histology of colonic polyps in colorectal cancer screening colonoscopy.

Full description

Deep learning to predict the histology of polyps per colonoscopy, offers a promising solution to reduce variation in colonoscopy performance. Meanwhile, the concept of 'optical biopsy' where in vivo classification of polyps based on enhanced imaging replaces histopathology has not been incorporated into routine practice, largely limited by inter-observer variability and generally meeting accepted standards only in expert settings. Real-time decision support software has been developed to detect and characterise polyps, whilst also offering feedback on the technical quality of inspection.

This study will evaluate the performance of the CAD EYE automatic characterization system for the histology compared to histological analysis. And secondary aims : the diagnostic performance of the CAD EYE automated detection device compared to a standardized video recording with blind independent review.

Procedure: The screening colonoscopy will be performed by an investigator. The automatic detection and characterization system will be activated at the time of descent of the colonoscopy (after caecal intubation), with video recording (image without CAD EYE and image with CAD EYE). The investigator performing the colonoscopy will be blinded by the results of the CAD EYE.

Follow-up: no specific follow-up is planned after colposcopy

Enrollment: 194 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients over 18 years of age with indication for colonoscopy as part of a screening colonoscopy, after a positive immunological test, and/or for personal or family history of colon cancer (before 60 years), personal history of colonic adenoma.
• Patient with at least one polyp detected, resect and removed during colonoscopy, for histological analysis

Exclusion criteria

• Guardianship or protection,
• pregnancy,
• not fluent in French or illiterate,
• lack of health care

Trial design

Primary purpose: Diagnostic

Allocation: N/A

Interventional model: Single Group Assignment

Masking: None (Open label)

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194 participants in 1 patient group

Patients with indication for colonoscopy

Experimental group

Description:

The screening colonoscopy will be performed by an investigator. The automatic detection and characterization system will be activated at the time of descent of the colonoscopy (after caecal intubation), with video recording (image without CAD EYE and image with CAD EYE). The investigator performing the colonoscopy will be blinded by the results of the CAD EYE.

Treatment:

Device: screening colonoscopy