Department of Gastroenterology, The Second Xiangya Hospital.
Research Center of Digestive Disease, Central South University, Changsha, Hunan, P. R. China.
Eur J Gastroenterol Hepatol. 2021 Aug 1;33(8):1041-1048. doi: 10.1097/MEG.0000000000001906.
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.
结肠镜检查是诊断息肉，尤其是腺瘤性息肉的重要方法。然而，其漏诊率相对较高。本研究旨在确定人工智能（AI）是否可以提高结肠镜检查的息肉检出率（PDR）和腺瘤检出率（ADR）。我们在 PubMed、Cochrane 图书馆、Embase 和 Web of Science 数据库中进行了系统检索；检索范围包括截至 2020 年 2 月 29 日数据库中的所有条目。共有 5 项研究符合纳入标准，共涉及 4311 例患者。这些研究结果表明，与对照组相比，AI 辅助可提高 PDR 和 ADR [汇总比值比（OR）=1.91（95%置信区间[CI] 1.68-2.16）和 1.75（95% CI 1.52-2.01）]。肠道准备良好可降低 AI 的影响，但 PDR 和 ADR 仍有显著差异[汇总 OR = 1.69（95% CI 1.32-2.16）和 1.36（95% CI 1.04-1.78）]。息肉和腺瘤的特征也会影响结果。平均检出息肉和腺瘤的数量因位置而异，且小息肉和腺瘤更易漏诊。然而，息肉形态的特点和 AI 辅助检测的效果仍需要进一步研究。总之，AI 可提高结肠镜检查中息肉和腺瘤的检出率。如果没有 AI 辅助，通过改善肠道准备和加强对小息肉和腺瘤的检测培训，可提高检出率。
