CAD EYE Detection of Remaining Lesions After EMR

Instituto Ecuatoriano de Enfermedades Digestivas

Status: Enrolling

Conditions: Colorectal Dysplasia; Colorectal Neoplasms

Treatments: Diagnostic Test: EMR with CAD-Eye™; Diagnostic Test: Follow-up colonoscopy with CAD-Eye™; Diagnostic Test: EMR without CAD-Eye™

Study type: Interventional

Funder types: Other

Identifiers

NCT05542030

IECED-08202022

Details and patient eligibility

About

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.

Full 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 91.7% 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.

Enrollment: 60 estimated patients

Sex: All

Ages: 18 to 90 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients referred to our center with an indication of colonoscopy and EMR for the treatment of lesions suspicious of high-grade dysplasia and early invasive cancer.
• Patients who authorize EMR and colonoscopy.
• Signed informed consent

Exclusion criteria

• Any clinical condition which makes EMR inviable.
• Poor bowel preparation score defined as the total Boston bowel preparation score (BBPS) <6 and the right-segment score <2
• Patients with more than one previous EMR
• Lost on a three-month follow-up after EMR
• Pregnancy or nursing

Trial design

Primary purpose: Diagnostic

Allocation: Non-Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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60 participants in 2 patient groups

Endoscopic mucosal resection + CAD-Eye™

Experimental group

Description:

This group constitutes patients with lesions suggestive of high-grade dysplasia or early invasive cancer approached with endoscopic mucosal resection, subjected to colonoscopy + CAD-Eye™ system evaluation for the detection of remaining malignant tissue. For this group, the investigators used as a complement tool an AI system (CAD-Eye™) for the detection of remaining lesions immediately after EMR and in a three-month follow-up.

Treatment:

Diagnostic Test: EMR with CAD-Eye™

Diagnostic Test: Follow-up colonoscopy with CAD-Eye™

Endoscopic mucosal resection without CAD Eye

Active Comparator group

Description:

This group constitutes patients with lesions suggestive of high-grade dysplasia or early invasive cancer approached with endoscopic mucosal resection and subjected to colonoscopy. The detection of remaining lesions immediately after EMR is based on the visual impression of the expert. For this group, the investigators used as a complement tool an AI system (CAD-Eye™) only for the evaluation of the post-procedure scar to detect remaining lesions in the three-month follow-up.

Treatment:

Diagnostic Test: EMR without CAD-Eye™

Diagnostic Test: Follow-up colonoscopy with CAD-Eye™