Real-time computer aided colonoscopy versus standard colonoscopy for improving adenoma detection rate: A meta-analysis of randomized-controlled trials.
Adenoma detection rate
Colonoscopy
Convolutional neural networks
Journal
EClinicalMedicine
ISSN: 2589-5370
Titre abrégé: EClinicalMedicine
Pays: England
ID NLM: 101733727
Informations de publication
Date de publication:
Dec 2020
Dec 2020
Historique:
received:
14
07
2020
revised:
04
09
2020
accepted:
28
09
2020
entrez:
9
12
2020
pubmed:
10
12
2020
medline:
10
12
2020
Statut:
epublish
Résumé
Recent prospective randomized controlled trials have evaluated deep convolutional neural network (CNN) based computer aided detection (CADe) of lesions in real-time colonoscopy. We conducted this meta-analysis to compare the adenoma detection rate (ADR) of deep CNN based CADe assisted colonoscopy to standard colonoscopy (SC) from randomized controlled trials (RCTs). Multiple databases were searched (from inception to May 2020) and parallel RCTs that compared deep CNN based CADe assisted colonoscopy to SC were included for this analysis. Using Mantel-Haenzel (M-H) random effects model, pooled risk ratios (RR) and mean difference (MD) were calculated. In between study heterogeneity was assessed by I Six RCTs were included in our final analysis that utilized deep CNN based CADe system in real-time colonoscopy. Total numbers of patients assessed were 4962 (2480 in CADe and 2482 in SC group). CADe based colonoscopy demonstrated statistically higher pooled ADR, RR=1.5 (95% CI 1.3-1.72), Based on our meta-analysis, deep CNN based CADe colonoscopy achieved significantly higher ADR metrics, albeit with increased scope withdrawal time when compared to SC.
Sections du résumé
BACKGROUND
BACKGROUND
Recent prospective randomized controlled trials have evaluated deep convolutional neural network (CNN) based computer aided detection (CADe) of lesions in real-time colonoscopy. We conducted this meta-analysis to compare the adenoma detection rate (ADR) of deep CNN based CADe assisted colonoscopy to standard colonoscopy (SC) from randomized controlled trials (RCTs).
METHODS
METHODS
Multiple databases were searched (from inception to May 2020) and parallel RCTs that compared deep CNN based CADe assisted colonoscopy to SC were included for this analysis. Using Mantel-Haenzel (M-H) random effects model, pooled risk ratios (RR) and mean difference (MD) were calculated. In between study heterogeneity was assessed by I
FINDINGS
RESULTS
Six RCTs were included in our final analysis that utilized deep CNN based CADe system in real-time colonoscopy. Total numbers of patients assessed were 4962 (2480 in CADe and 2482 in SC group). CADe based colonoscopy demonstrated statistically higher pooled ADR, RR=1.5 (95% CI 1.3-1.72),
INTERPRETATION
CONCLUSIONS
Based on our meta-analysis, deep CNN based CADe colonoscopy achieved significantly higher ADR metrics, albeit with increased scope withdrawal time when compared to SC.
Identifiants
pubmed: 33294821
doi: 10.1016/j.eclinm.2020.100622
pii: S2589-5370(20)30366-7
pmc: PMC7691740
doi:
Types de publication
Journal Article
Langues
eng
Pagination
100622Informations de copyright
© 2020 The Author(s).
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