Effect of computer-aided colonoscopy on adenoma miss rates and polyp detection: A systematic review and meta-analysis.
adenoma detection rate
adenoma miss rate
artificial intelligence
colorectal cancer
computer-aided colonoscopy
computer-aided detection
polyp detection rate
Journal
Journal of gastroenterology and hepatology
ISSN: 1440-1746
Titre abrégé: J Gastroenterol Hepatol
Pays: Australia
ID NLM: 8607909
Informations de publication
Date de publication:
Feb 2023
Feb 2023
Historique:
revised:
16
10
2022
received:
21
04
2022
accepted:
31
10
2022
pubmed:
10
11
2022
medline:
10
2
2023
entrez:
9
11
2022
Statut:
ppublish
Résumé
Multiple computer-aided techniques utilizing artificial intelligence (AI) have been created to improve the detection of polyps during colonoscopy and thereby reduce the incidence of colorectal cancer. While adenoma detection rates (ADR) and polyp detection rates (PDR) are important colonoscopy quality indicators, adenoma miss rates (AMR) may better quantify missed lesions, which can ultimately lead to interval colorectal cancer. The purpose of this systematic review and meta-analysis was to determine the efficacy of computer-aided colonoscopy (CAC) with respect to AMR, ADR, and PDR in randomized controlled trials. A comprehensive, systematic literature search was performed across multiple databases in September of 2022 to identify randomized, controlled trials that compared CAC with traditional colonoscopy. Primary outcomes were AMR, ADR, and PDR. Fourteen studies totaling 10 928 patients were included in the final analysis. There was a 65% reduction in the adenoma miss rate with CAC (OR, 0.35; 95% CI, 0.25-0.49, P < 0.001, I The results of the present study demonstrate the promise of CAC in improving AMR, ADR, PDR across a spectrum of size and morphological lesion characteristics.
Sections du résumé
BACKGROUND AND AIM
OBJECTIVE
Multiple computer-aided techniques utilizing artificial intelligence (AI) have been created to improve the detection of polyps during colonoscopy and thereby reduce the incidence of colorectal cancer. While adenoma detection rates (ADR) and polyp detection rates (PDR) are important colonoscopy quality indicators, adenoma miss rates (AMR) may better quantify missed lesions, which can ultimately lead to interval colorectal cancer. The purpose of this systematic review and meta-analysis was to determine the efficacy of computer-aided colonoscopy (CAC) with respect to AMR, ADR, and PDR in randomized controlled trials.
METHODS
METHODS
A comprehensive, systematic literature search was performed across multiple databases in September of 2022 to identify randomized, controlled trials that compared CAC with traditional colonoscopy. Primary outcomes were AMR, ADR, and PDR.
RESULTS
RESULTS
Fourteen studies totaling 10 928 patients were included in the final analysis. There was a 65% reduction in the adenoma miss rate with CAC (OR, 0.35; 95% CI, 0.25-0.49, P < 0.001, I
CONCLUSIONS
CONCLUSIONS
The results of the present study demonstrate the promise of CAC in improving AMR, ADR, PDR across a spectrum of size and morphological lesion characteristics.
Types de publication
Meta-Analysis
Systematic Review
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
162-176Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2022 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.
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