Artificial intelligence can increase the detection rate of colorectal polyps and adenomas: a systematic review and meta-analysis

Abstract

Colonoscopy is an important method to diagnose polyps, especially adenomatous polyps. However, the rate of missed diagnoses is relatively high. In this study, we aimed to determine whether artificial intelligence (AI) improves the polyp detection rate (PDR) and adenoma detection rate (ADR) with colonoscopy. We performed a systematic search in PubMed, Cochrane Library, Embase, and Web of Science databases; the search included entries in the databases up to and including 29 February 2020. Five articles that involved a total of 4311 patients fulfilled the selection criteria. The results of these studies showed that both PDR and ADR increased with the assistance of AI compared with those in control groups {pooled odds ratio (OR) = 1.91 [95% confidence interval (CI) 1.68–2.16] and 1.75 (95% CI 1.52–2.01), respectively}. Good bowel preparation reduced the impact of AI, but significant differences were still apparent in PDR and ADR [pooled OR = 1.69 (95% CI 1.32–2.16) and 1.36 (95% CI 1.04–1.78), respectively]. The characteristics of polyps and adenomas also influenced the results. The average number of polyps and adenomas detected varied significantly by location, and small polyps and adenomas were more likely to be missed. However, the effect of the morphology of polyps and AI-assisted detection needs further studies. In conclusion, AI increases the detection rates of polyps and adenomas in colonoscopy. Without AI assistance, detection rates can be improved with better bowel preparation and training for small polyp and adenoma detection.

Artificial intelligence (AI) real-time detection vs. routine colonoscopy for colorectal neoplasia: a meta-analysis and trial sequential analysis

“…AI has established its utility with numerous luminal and extra-luminal applications in gastroenterology. Recent pooled studies have established its superior detection capabilities [30][31][32][33][34], and our study echoes the superior ADR and PDR rates of AI systems. Additionally, we included all prior studies to date and completed an in-depth subgroup analysis to parse out information based on colonic segments, size, and shape not described in other pooled studies.…”

Effect of artificial intelligence-aided colonoscopy for adenoma and polyp detection: a meta-analysis of randomized clinical trials

“…BPPS is an effective and reliable bowel preparation scale that reflects the cleanliness of the colon during colonoscopy [36]. The meta-analysis of Li et al found that better bowel preparation can increase the detection rate based on cases without AI assistance [37]. However, despite adequate bowel preparation, residual colonic fluid can still lead to visual disruption and mucosal visibility compromise [38].…”

The effectiveness of real-time computer-aided and quality control systems in colorectal adenoma and polyp detection during colonoscopies: a meta-analysis

“…Li and colleagues published a meta-analysis in 2021 that employed a total of five studies with 4311 patients that fulfilled the selection criteria; their results showed that the ADR and PDR with the assistance of AI had a pooled OR of 1.91 (95% CI=1.68–2.16) and 1.75 (95% CI=1.52–2.01), respectively. They found that the morphology of adenomas and polyps in colonoscopy impacted detection rates and the characteristics likely influenced the results 28 . Hassan and colleagues included five RCTs with 4356 patients.…”