Artificial intelligence in bronchoscopy: a systematic review.

IF 9 1区医学 Q1 RESPIRATORY SYSTEM

European Respiratory Review Pub Date : 2025-05-28 Print Date: 2025-04-01 DOI:10.1183/16000617.0274-2024

Kristoffer Mazanti Cold, Anishan Vamadevan, Christian B Laursen, Flemming Bjerrum, Suveer Singh, Lars Konge

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引用次数: 0

Abstract

Background: Artificial intelligence (AI) systems have been implemented to improve the diagnostic yield and operators' skills within endoscopy. Similar AI systems are now emerging in bronchoscopy. Our objective was to identify and describe AI systems in bronchoscopy.

Methods: A systematic review was performed using MEDLINE, Embase and Scopus databases, focusing on two terms: bronchoscopy and AI. All studies had to evaluate their AI against human ratings. The methodological quality of each study was assessed using the Medical Education Research Study Quality Instrument (MERSQI).

Results: 1196 studies were identified, with 20 passing the eligibility criteria. The studies could be divided into three categories: nine studies in airway anatomy and navigation, seven studies in computer-aided detection and classification of nodules in endobronchial ultrasound, and four studies in rapid on-site evaluation. 16 were assessment studies, with 12 showing equal performance and four showing superior performance of AI compared with human ratings. Four studies within airway anatomy implemented their AI, all favouring AI guidance to no AI guidance. The methodological quality of the studies was moderate (mean MERSQI 12.9 points, out of a maximum 18 points).

Interpretation: 20 studies developed AI systems, with only four examining the implementation of their AI. The four studies were all within airway navigation and favoured AI to no AI in a simulated setting. Future implementation studies are warranted to test for the clinical effect of AI systems within bronchoscopy.

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人工智能在支气管镜检查中的应用综述。

背景：人工智能（AI）系统已被用于提高内窥镜检查的诊断率和操作人员的技能。类似的人工智能系统现在正在支气管镜检查中出现。我们的目标是识别和描述支气管镜检查中的人工智能系统。方法：采用MEDLINE、Embase和Scopus数据库进行系统综述，重点关注支气管镜检查和人工智能两个术语。所有的研究都必须根据人类的评分来评估他们的人工智能。采用医学教育研究质量工具（MERSQI）评估每项研究的方法学质量。结果：共纳入1196项研究，其中20项符合入选标准。研究分为三类：气道解剖与导航研究9项，支气管内超声计算机辅助结节检测与分类研究7项，快速现场评价研究4项。16项是评估研究，其中12项表现相同，4项表现优于人类评级。气道解剖学中的四项研究实施了他们的人工智能，所有研究都倾向于人工智能指导，而不是没有人工智能指导。这些研究的方法学质量为中等（MERSQI平均12.9分，满分18分）。解释：20项研究开发了人工智能系统，只有4项研究检查了人工智能的实施情况。这四项研究都是在气道导航中进行的，并且在模拟环境中倾向于人工智能，而不是没有人工智能。未来的实施研究需要测试人工智能系统在支气管镜检查中的临床效果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

European Respiratory Review Medicine-Pulmonary and Respiratory Medicine

CiteScore

14.40

自引率

1.30%

发文量

审稿时长

24 weeks

期刊介绍： The European Respiratory Review (ERR) is an open-access journal published by the European Respiratory Society (ERS), serving as a vital resource for respiratory professionals by delivering updates on medicine, science, and surgery in the field. ERR features state-of-the-art review articles, editorials, correspondence, and summaries of recent research findings and studies covering a wide range of topics including COPD, asthma, pulmonary hypertension, interstitial lung disease, lung cancer, tuberculosis, and pulmonary infections. Articles are published continuously and compiled into quarterly issues within a single annual volume.