Ignite Creation Date:
2024-05-06 @ 4:15 PM
Last Modification Date:
2024-10-26 @ 2:06 PM
Study NCT ID:
NCT04921488
Status:
COMPLETED
Last Update Posted:
2023-03-13
First Post:
2021-06-04
Brief Title:
Interest of Artificial Intelligence in Cancer Screening Colonoscopy
Sponsor:
University Hospital Bordeaux
Organization:
University Hospital Bordeaux
Study Overview
Official Title:
Cross-sectional Multi-center Study Comparing Diagnostic Performance Between the CAD EYE System and the Physician on Histological Prediction of Colonic Polyps in Screening of Colorectal Cancer by Colonoscopy
Status:
COMPLETED
Status Verified Date:
2023-03
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
IA COLO
Brief Summary:
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
Detailed 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
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
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None