Artificial intelligence for reducing missed detection of adenomas and polyps in colonoscopy: A systematic review and meta-analysis

Abstract

Background: Colorectal cancer has a high incidence and mortality rate, and the effectiveness of routine colonoscopy largely depends on the endoscopist's expertise. In recent years, computer-aided detection (CADe) systems have been increasingly integrated into colonoscopy to improve detection accuracy. However, while most studies have focused on adenoma detection rate (ADR) as the primary outcome, the more sensitive adenoma miss rate (AMR) has been less frequently analyzed.

Aim: To evaluate the effectiveness of CADe in colonoscopy and assess the advantages of AMR over ADR.

Methods: A comprehensive literature search was conducted in PubMed, Embase, and the Cochrane Central Register of Controlled Trials using predefined search strategies to identify relevant studies published up to August 2, 2024. Statistical analyses were performed to compare outcomes between groups, and potential publication bias was assessed using funnel plots. The quality of the included studies was evaluated using the Cochrane Risk of Bias tool and the Grading of Recommendations, Assessment, Development, and Evaluation approach.

Results: Five studies comprising 1624 patients met the inclusion criteria. AMR was significantly lower in the CADe-assisted group than in the routine colonoscopy group (147/927, 15.9% vs 345/960, 35.9%; P < 0.01). However, CADe did not provide a significant advantage in detecting advanced adenomas or lesions measuring 6-9 mm or ≥ 10 mm. The polyp miss rate (PMR) was also lower in the CADe-assisted group [odds ratio (OR), 0.35; 95% confidence interval (CI): 0.23-0.52; P < 0.01]. While the overall ADR did not differ significantly between groups, the ADR during the first-pass examination was higher in the CADe-assisted group (OR, 1.37; 95%CI: 1.10-1.69; P = 0.004). The level of evidence for the included randomized controlled trials was graded as moderate.

Conclusion: CADe can significantly reduce AMR and PMR while improving ADR during initial detection, demonstrating its potential to enhance colonoscopy performance. These findings highlight the value of CADe in improving the detection of colorectal neoplasms, particularly small and histologically distinct adenomas.

Keywords: Artificial intelligence; Colonoscopy; Computer-aided detection; Neoplasms; Prevention and control.

Figure 1

Study flow chart. CENTRAL: Cochrane Central Register of Controlled Trials; CADe: Computer-aided detection.

Figure 2

Study quality and assessment chart.

Figure 3

Forrest plots and funnel plot. A: Forrest plot showing adenoma miss rate for colonoscopy with vs without computer-aided detection (CADe) assistance for the included studies; B: Funnel plot showing associated publication bias; C: Sensitivity analysis of adenoma miss rate for colonoscopy with vs without CADe assistance for the included studies. CADe: Computer-aided detection; OR: Odds ratio.

Figure 4

Forrest plots showing adenoma miss rate for colonoscopy with vs without computer-aided detection assistance. A: Sessile serrated lesions for the included studies; B: Advanced adenomas for the included studies; C: Size for the included studies; D: Location for the included studies. CADe: Computer-aided detection.

Figure 5

Forrest plot showing polyps miss rate for colonoscopy with vs without computer-aided detection assistance for the included studies. CADe: Computer-aided detection.

Figure 6

Forrest plots showing adenoma detection rate for colonoscopy with vs without computer-aided detection assistance. A: The included studies; B: The first pass for the included studies. CADe: Computer-aided detection.

Figure 7

Forrest plot showing adenomas per colonoscopy for colonoscopy with vs without computer-aided detection assistance for the included studies. CADe: Computer-aided detection.

Figure 8

Withdrawal time for colonoscopy with vs without computer-aided detection assistance on first pass for the included studies. A: Forrest plot; B: Sensitivity analysis. CADe: Computer-aided detection.

Figure 9

Forrest plot showing withdrawal time for colonoscopy with vs without computer-aided detection assistance on second pass for the included studies. CADe: Computer-aided detection.