Artificial Intelligence-Aid Colonoscopy Vs. Conventional Colonoscopy for Polyp and Adenoma Detection: A Systematic Review of 7 Discordant Meta-Analyses

Abstract

Objectives: Multiple meta-analyses which investigated the comparative efficacy and safety of artificial intelligence (AI)-aid colonoscopy (AIC) vs. conventional colonoscopy (CC) in the detection of polyp and adenoma have been published. However, a definitive conclusion has not yet been generated. This systematic review selected from discordant meta-analyses to draw a definitive conclusion about whether AIC is better than CC for the detection of polyp and adenoma.Methods: We comprehensively searched potentially eligible literature in PubMed, Embase, Cochrane library, and China National Knowledgement Infrastructure (CNKI) databases from their inceptions until to April 2021. Assessment of Multiple Systematic Reviews (AMSTAR) instrument was used to assess the methodological quality. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist was used to assess the reporting quality. Two investigators independently used the Jadad decision algorithm to select high-quality meta-analyses which summarized the best available evidence.Results: Seven meta-analyses met our selection criteria finally. AMSTAR score ranged from 8 to 10, and PRISMA score ranged from 23 to 26. According to the Jadad decision algorithm, two high-quality meta-analyses were selected. These two meta-analyses suggested that AIC was superior to CC for colonoscopy outcomes, especially for polyp detection rate (PDR) and adenoma detection rate (ADR).Conclusion: Based on the best available evidence, we conclude that AIC should be preferentially selected for the route screening of colorectal lesions because it has potential value of increasing the polyp and adenoma detection. However, the continued improvement of AIC in differentiating the shape and pathology of colorectal lesions is needed.

Improvement of adenoma detection rate by two computer-aided colonic polyp detection systems in high adenoma detectors: a randomized multicenter trial

“…Recent metaanalyses provide abundant evidence demonstrating the value of a computer-aided polyp detection (CADe) system by increasing the ADR and reducing missed adenomas [7,8,9,10]. Despite the impressive results, many studies have been criticized for having a low baseline ADR, raising the question of whether similar results would have been obtained had the baseline ADR been higher [6,7,8,9]. Furthermore, previous meta-analyses concluded that CADe could aid in detecting only diminutive polyps while not increasing the detection of advanced adenoma [11,12].…”

“…Advancements in artificial intelligence technology over the past decade have opened up new possibilities for overcoming human error during colonoscopy procedures [6]. Recent metaanalyses provide abundant evidence demonstrating the value of a computer-aided polyp detection (CADe) system by increasing the ADR and reducing missed adenomas [7,8,9,10].…”

Influence of Artificial Intelligence on the Adenoma Detection Rate throughout the Day

“…The latest technology is using real-time artificial intelligence systems to detect and/or characterize polyps [5]. This new technology has already been shown to increase the ADR as well as the adenomas detected per patient [6]. This is achieved mostly by the detection of small and diminutive adenomas.…”

Artificial intelligence and the push for small adenomas: all we need?

“…They all show a more or less significant increase in detection of small adenomas. The same results are summarized over and over again in no less than 16 meta-analyses [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35], plus a protocol for a further one [36], as well as a meta-analysis of some of these meta-analyses [37]! "The question relates to the ultimate clinical relevance of increasing ADR from high to even higher levels …, we still do not know whether we have a cutoff ADR level, above which there is no further improvement in cancer prevention.…”