Affiliation:
1. Gastroenterology Department, Hospital da Senhora da Oliveira – Guimarães, Guimarães
2. Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga
3. ICVS/3B’s, PT Government Associate Laboratory, Guimarães/Braga, Portugal
Abstract
Colon capsule endoscopy (CCE) is a well-known method for the detection of colorectal lesions. Nevertheless, there are no studies reporting the accuracy of TOP 100, a CCE software tool, for the automatic detection of colorectal lesions in CCE. We aimed to evaluate the performance of TOP 100 in detecting colorectal lesions in patients submitted to CCE for incomplete colonoscopy compared with classic reading. A retrospective cohort study including adult patients submitted to CCE (PillCam COLON 2; Medtronic) for incomplete colonoscopy. Blinded for each other’s evaluation, one experienced reader analyzed the TOP 100 images and the other performed classic reading to identify colorectal lesions. Detection of colorectal lesions, namely polyps, angioectasia, blood, diverticula, erosions/ulcers, neoplasia, and subepithelial lesions was assessed and TOP 100 performance was evaluated compared with the gold standard (classic reading). A total of 188 CCEs were included. Prevalence of colorectal lesions, polyps, angioectasia, blood, diverticula, erosions/ulcers, neoplasia, and subepithelial lesions were 77.7, 54.3, 8.5, 1.6, 50.0, 0.5, 0.5, and 1.1%, respectively. TOP 100 had a sensitivity of 92.5%, specificity of 69.1%, negative predictive value of 72.5%, positive predictive value of 91.2%, and accuracy of 87.2% for detecting colorectal lesions. TOP 100 had a sensitivity of 89.2%, specificity of 84.9%, negative predictive value of 86.9%, positive predictive value of 87.5%, and accuracy of 87.2% in detecting polyps. All colorectal lesions other than polyps were identified with 100% accuracy by TOP 100. TOP 100 has been shown to be a simple and useful tool in assisting the reader in the prompt identification of colorectal lesions in CCE.
Publisher
Ovid Technologies (Wolters Kluwer Health)