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Meta-Analysis
. 2024 Mar 1;15(3):e00671.
doi: 10.14309/ctg.0000000000000671.

Artificial Intelligence-Assisted Colonoscopy in Real-World Clinical Practice: A Systematic Review and Meta-Analysis

Mike Tzuhen Wei  1 , Shmuel Fay  2   3 , Diana Yung  4 , Uri Ladabaum  1 , Uri Kopylov  2   3
Affiliations
Meta-Analysis

Artificial Intelligence-Assisted Colonoscopy in Real-World Clinical Practice: A Systematic Review and Meta-Analysis

Mike Tzuhen Wei et al. Clin Transl Gastroenterol. .

Abstract

Introduction: Artificial intelligence (AI) could minimize the operator-dependent variation in colonoscopy quality. Computer-aided detection (CADe) has improved adenoma detection rate (ADR) and adenomas per colonoscopy (APC) in randomized controlled trials. There is a need to assess the impact of CADe in real-world settings.

Methods: We searched MEDLINE, EMBASE, and Web of Science for nonrandomized real-world studies of CADe in colonoscopy. Random-effects meta-analyses were performed to examine the effect of CADe on ADR and APC. The study is registered under PROSPERO (CRD42023424037). There was no funding for this study.

Results: Twelve of 1,314 studies met inclusion criteria. Overall, ADR was statistically significantly higher with vs without CADe (36.3% vs 35.8%, risk ratio [RR] 1.13, 95% confidence interval [CI] 1.01-1.28). This difference remained significant in subgroup analyses evaluating 6 prospective (37.3% vs 35.2%, RR 1.15, 95% CI 1.01-1.32) but not 6 retrospective (35.7% vs 36.2%, RR 1.12, 95% CI 0.92-1.36) studies. Among 6 studies with APC data, APC rate ratio with vs without CADe was 1.12 (95% CI 0.95-1.33). In 4 studies with GI Genius (Medtronic), there was no difference in ADR with vs without CADe (RR 0.96, 95% CI 0.85-1.07).

Discussion: ADR, but not APC, was slightly higher with vs without CADe among all available real-world studies. This difference was attributed to the results of prospective but not retrospective studies. The discrepancies between these findings and those of randomized controlled trials call for future research on the true impact of current AI technology on colonoscopy quality and the subtleties of human-AI interactions.

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Conflict of interest statement

Guarantor of the article: Uri Kopylov, MD.

Specific author contributions: M.T.W.: planning the study, screening studies, extracting data, analyzing and interpreting data, and drafting the manuscript. This author approves the final draft submitted. S.F.: planning the study, screening studies, extracting data, analyzing and interpreting data, and drafting the manuscript. This author approves the final draft submitted. D.Y.: planning the study, analyzing and interpreting data, and drafting the manuscript. This author approves the final draft submitted. U.L.: planning the study, analyzing and interpreting data, and drafting the manuscript. This author approves the final draft submitted. U.K.: planning the study, analyzing and interpreting data, and drafting the manuscript. This author approves the final draft submitted.

Financial support: None to report.

Potential competing interests: M.T.W.: consultant for Capsovision, Neptune Medical, AgilTX. S.F.: none. D.Y.: none. U.L.: consultant for Neptune Medical, Medtronic, Medial EarlySign, Freenome, Guardant, and Kohler Ventures; Advisory Board for Universial Dx, Vivante. U.K.: advisory and speaker fees–Abbvie, BMS, Celtrion, Takeda, Janssen, Medtronic, and Pfizer, research support—Janssen, Medtronic, and Takeda.

Figures

Figure 1.
Figure 1.
Study selection. Flowchart of the study selection process.
Figure 2.
Figure 2.
Pooled ADR risk ratio of all studies including abstracts. ADR, adenoma detection rate; CADe, computer-assisted detection.
Figure 3.
Figure 3.
Pooled rate ratio for APC with vs without CADe. APC, Adenoma per colonoscopy; CADe, computer-assisted detection.
Figure 4.
Figure 4.
Pooled ADR risk ratio of full studies evaluating only GI Genius. ADR, adenoma detection rate; CADe, computer-assisted detection.
See this image and copyright information in PMC

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