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| 人工智能在气管导管定位中的应用进展 |
| Progress of artificial intelligence applications in endotracheal tube positioning |
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| DOI：10.12089/jca.2025.12.014 |
| 中文关键词: 气管导管定位 人工智能 气管插管评估 深度学习 |
| 英文关键词: Endotracheal tube positioning Artificial intelligence Endotracheal intubation assessment Deep learning |
| 基金项目:国家自然科学基金联合基金项目（U20A2018）；北京卫健委高层次公共卫生技术人才建设项目培养计划（领军人才03-10） |
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| 中文摘要: |
| 气管插管作为临床麻醉、急救及重症监护中的关键操作，其成功率直接影响患者生命安全和手术效果。其中，气管导管的正确定位是决定插管成功的核心。然而，传统插管技术高度依赖操作者临床经验，存在主观性强、标准化程度低及操作难度大等问题，易引发插管失败或导管异位等不良事件。此外，成年患者与婴幼儿患者的呼吸系统结构存在显著差异，使得插管定位方法各异。近年来，人工智能（AI）技术在气道管理中的应用为插管定位提供了创新性解决方案。基于大数据分析和深度学习算法，AI技术可有效规避人为操作误差，提高气管导管定位的客观性和准确性。本文系统综述近5年AI在气道导管定位的研究进展，深入剖析AI于插管评估和定位实践中的应用技术路径。同时，通过多维度分析当前AI在临床应用中面临的技术瓶颈与挑战，结合行业发展趋势对其未来发展方向进行探讨，为推动AI在气道管理中的临床应用提供参考。 |
| 英文摘要: |
| Endotracheal intubation is a critical procedure in clinical anesthesia, emergency care, and intensive care, with its success rate directly impacting patient safety and surgical outcomes. Among the key factors, the accurate positioning of the endotracheal tube is central to the success of intubation. However, traditional intubation techniques heavily rely on the operators' experience, presenting challenges such as high subjectivity, low standardization, and technical difficulty, which may lead to failed intubation or misplacement of the tube. In addition, there are significant differences in the respiratory system structure between adults and children, making intubation positioning methods different. In recent years, the application of artificial intelligence (AI) technology in airway management has provided innovative solutions for intubation positioning. Leveraging big data analytics and deep learning algorithms, AI can effectively mitigate human error, enhancing the objectivity and accuracy of endotracheal tube placement. This review systematically summarizes the research progress over the past five years on the application of AI in endotracheal tube positioning for both adults and children. It provides a detailed examination of the technical approaches through which AI has been integrated into clinical practices of intubation guidance and position assessment. Furthermore, by exploring the current technical bottlenecks and limitations in clinical practice, this article offers a forward-looking perspective on future development trends, aiming to support the advancement of AI-assisted clinical airway management. |
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