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CAD EYE Detection of Remaining Lesions After EMR

Recruiting
18 - 90 years of age
Both
Phase N/A

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Overview

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.

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.

Eligibility

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

Study details

Colorectal Dysplasia, Colorectal Neoplasms

NCT05542030

Instituto Ecuatoriano de Enfermedades Digestivas

25 January 2024

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