Viewing Study NCT05542030



Ignite Creation Date: 2024-05-06 @ 6:05 PM
Last Modification Date: 2024-10-26 @ 2:41 PM
Study NCT ID: NCT05542030
Status: RECRUITING
Last Update Posted: 2023-09-28
First Post: 2022-09-05

Brief Title: CAD EYE Detection of Remaining Lesions After EMR
Sponsor: Instituto Ecuatoriano de Enfermedades Digestivas
Organization: Instituto Ecuatoriano de Enfermedades Digestivas

Study Overview

Official Title: Accuracy of CAD Eye in the Detection of Colonic Remaining Lesions After Endoscopic Mucosal Resection a Pilot Study
Status: RECRUITING
Status Verified Date: 2023-09
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: None
Brief Summary: In the last decade many innovative systems have been developed to support and improve the diagnosis accuracy during endoscopic studies CAD-Eye Fujifilm Tokyo Japan is a computer-assisted diagnostic CADx system that uses artificial intelligence for the detection and characterization of polyps during colonoscopy However the accuracy of CAD-Eye in the recognition of remaining lesions after endoscopic mucosal resection EMR has not been broadly evaluated

Finally based on the importance of complete resection of the colonic mucosal lesions namely suspicious high-grade dysplasia or early invasive cancer the investigators aimed to assess the accuracy of CAD-Eye in the detection of remaining lesions after the procedure
Detailed Description: Nowadays the increased polyp and adenoma detection rate and its early treatment have reduced considerably colorectal cancer-related mortality For lesions suspicious of high-grade dysplasia or early invasive cancer the endoscopic mucosal resection EMR along with snare polypectomy is now considered one of the established standard treatments However there are many difficult-to-treat lesions such as the large and fibrotic ones which can lead to incomplete resections

Based on the above many newly diagnostic techniques guided by artificial intelligence AI currently proposed to improve the polyp detection rate during colonoscopy can be applied for the detection of remaining lesions after endoscopic treatment

CAD-Eye is CADx for polyp detection and characterization It improves polyp visualization by using techniques such as blue-laser imaging BLI-LASER blue-light imaging BLI-LED and linked-color imaging LCI This device aimed to improve real-time polyp detection helping experts identify multiple polyps simultaneously and common inadvertently missed lesions flat lesions polyps in difficult areas

CAD-Eye had demonstrated in previous studies an accuracy of 89 to 917 in polyp detection However few studies had demonstrated its performance in the detection of remaining lesions after EMR The investigators aimed to take advantage of this system in the detection of remaining lesions immediately after EMR and in its endoscopic control after three months

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