Abstract

BackgroundInterpretation of capsule endoscopy images or movies is operator-dependent and time-consuming. As a result, computer-aided diagnosis (CAD) has been applied to enhance the efficacy and accuracy of the review process. Two previous meta-analyses reported the diagnostic performance of CAD models for gastrointestinal ulcers or hemorrhage in capsule endoscopy. However, insufficient systematic reviews have been conducted, which cannot determine the real diagnostic validity of CAD models.ObjectiveTo evaluate the diagnostic test accuracy of CAD models for gastrointestinal ulcers or hemorrhage using wireless capsule endoscopic images.MethodsWe conducted core databases searching for studies based on CAD models for the diagnosis of ulcers or hemorrhage using capsule endoscopy and presenting data on diagnostic performance. Systematic review and diagnostic test accuracy meta-analysis were performed.ResultsOverall, 39 studies were included. The pooled area under the curve, sensitivity, specificity, and diagnostic odds ratio of CAD models for the diagnosis of ulcers (or erosions) were .97 (95% confidence interval, .95–.98), .93 (.89–.95), .92 (.89–.94), and 138 (79–243), respectively. The pooled area under the curve, sensitivity, specificity, and diagnostic odds ratio of CAD models for the diagnosis of hemorrhage (or angioectasia) were .99 (.98–.99), .96 (.94–0.97), .97 (.95–.99), and 888 (343–2303), respectively. Subgroup analyses showed robust results. Meta-regression showed that published year, number of training images, and target disease (ulcers vs erosions, hemorrhage vs angioectasia) was found to be the source of heterogeneity. No publication bias was detected.ConclusionsCAD models showed high performance for the optical diagnosis of gastrointestinal ulcer and hemorrhage in wireless capsule endoscopy.

Highlights

  • Wireless capsule endoscopy (WCE) allows the investigation of gastrointestinal mucosal lesions in a noninvasive manner

  • We conducted core databases searching for studies based on computer-aided diagnosis (CAD) models for the diagnosis of ulcers or hemorrhage using capsule endoscopy and presenting data on diagnostic performance

  • Meta-regression showed that published year, number of training images, and target disease was found to be the source of heterogeneity

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Summary

Introduction

Wireless capsule endoscopy (WCE) allows the investigation of gastrointestinal mucosal lesions in a noninvasive manner. The main benefit of the application of artificial intelligence would be the reduction of the laborious reading time and miss rate of important findings in WCE. Another advantage would be the highly accurate diagnostic performance, which is comparable to that of an endoscopist [6]. These artificial intelligence models are expected to aid in the automatic detection of important lesions in WCE images, making it possible to perform automatic reading and interpretation of the entire examination. Insufficient systematic reviews have been conducted, which cannot determine the real diagnostic validity of CAD models

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