Clin Endosc.  2022 May;55(3):355-364. 10.5946/ce.2021.228.

Does computer-aided diagnostic endoscopy improve the detection of commonly missed polyps? A meta-analysis

Affiliations
  • 1Institute of Global Health Innovation, Imperial College, London, UK
  • 2Department of Surgery and Cancer, Imperial College NHS Healthcare Trust, London, UK
  • 3Department of Gastroenterology, Chelsea and Westminster NHS Healthcare Trust, London, UK

Abstract

Background/Aims
Colonoscopy is the gold standard diagnostic method for colorectal neoplasia, allowing detection and resection of adenomatous polyps; however, significant proportions of adenomas are missed. Computer-aided detection (CADe) systems in endoscopy are currently available to help identify lesions. Diminutive (≤5 mm) and nonpedunculated polyps are most commonly missed. This meta-analysis aimed to assess whether CADe systems can improve the real-time detection of these commonly missed lesions.
Methods
A comprehensive literature search was performed. Randomized controlled trials evaluating CADe systems categorized by morphology and lesion size were included. The mean number of polyps and adenomas per patient was derived. Independent proportions and their differences were calculated using DerSimonian and Laird random-effects modeling.
Results
Seven studies, including 2,595 CADe-assisted colonoscopies and 2,622 conventional colonoscopies, were analyzed. CADe-assisted colonoscopy demonstrated an 80% increase in the mean number of diminutive adenomas detected per patient compared with conventional colonoscopy (0.31 vs. 0.17; effect size, 0.13; 95% confidence interval [CI], 0.09–0.18); it also demonstrated a 91.7% increase in the mean number of nonpedunculated adenomas detected per patient (0.32 vs. 0.19; effect size, 0.05; 95% CI, 0.02–0.07).
Conclusions
CADe-assisted endoscopy significantly improved the detection of most commonly missed adenomas. Although this method is a potentially exciting technology, limitations still apply to current data, prompting the need for further real-time studies.

Keyword

Colonoscopy; Computer-aided detection; Artificial intelligence; Colorectal neoplasms

Figure

  • Fig. 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram of study selection.

  • Fig. 2. Pooled analysis of the mean number of diminutive adenomas per patient between the computer-aided detection and conventional colonoscopy groups. Effect sizes (ES) are shown with 95% confidence intervals (CI). A random-effects model was used.

  • Fig. 3. Pooled analysis of the mean number of nonpedunculated adenomas per patient between the computer-aided detection and conventional colonoscopy groups. Effect sizes (ES) are shown with 95% confidence intervals (CI). A random-effects model was used.


Cited by  1 articles

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