Effectiveness of artificial intelligence-assisted colonoscopy in detecting and diagnosing colorectal tumors: a systematic review and network meta-analysis

作者：Shufa Tan, Pengfei Zeng, Shuang Liu, Yunyi Yang, Shikai Chen, Wei Zhang, Xiaoming Li, D Z Liu, Yuwei Li, Xu Chen · 发表于：International Journal of Colorectal Disease · 年份：2025 · DOI：10.1007/s00384-025-04949-z · 被引用次数：6 · 研究领域：Colorectal Cancer Screening and Detection、AI in cancer detection、COVID-19 diagnosis using AI

BACKGROUND: The emergence of artificial intelligence (AI) has greatly promoted the development of the field of medical image analysis, but the potential benefits of AI-assisted colonoscopy and diagnosis (CADe/CADx) for the detection rate of colorectal adenomas and the histological diagnosis of polyps are still controversial and unknown. METHODS: We conducted a search on PubMed, Web of Science, Embase, and Cochrane, and the last search time was August 2024. We collected adenoma detection rate (ADR), polyp detection rate (PDR), and sessile serrated lesion detection rate (SSL). Paired analysis and network meta-analysis (NMA) were performed using R Studio. StataSE15.0 software was used for statistical analysis to calculate the sensitivity and specificity of CADx and conventional colonoscopy. RESULTS: We included a total of 64 studies, including 52 RCT studies and 12 clinical studies, with a total of 50,834 patients undergoing colonoscopy. The results showed that different adjuvant interventions had significant differences in the detection rate of adenoma compared with routine colonoscopy ADR [RR = 1.20, 95% CI (1.14, 1.26), P < 0.001], and the results were statistically significant. Among different CADe models and advanced optical imaging techniques, ENDOANGEL model-assisted colonoscopy is the most effective method for detecting colorectal adenomas and polyps (97.8%), and Endocuff-AI model-assisted colonoscopy is the most effective method for detecting sessile serrated lesions (9...