Zhou Yunanji, Qiu Xinyi, Yuan Ting, Wang Qian, Du Lei, Wang Lihua, Ding Zhaohui
Qi Huang Chinese Medicine Academy, Jiangxi University of Chinese Medicine, Nanchang, China.
School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang, China.
Front Med (Lausanne). 2025 Aug 13;12:1618588. doi: 10.3389/fmed.2025.1618588. eCollection 2025.
Mass spectrometry (MS)-based breath analysis has emerged as a promising non-invasive approach for diagnosing and monitoring respiratory diseases through the identification of volatile organic compounds (VOCs). This study conducted a comprehensive bibliometric analysis of 467 publications (2003-2024) to map global research trends, influential contributors, and thematic hotspots in this field. Results showed a sustained annual growth rate of 11.03%, with the United States, the United Kingdom, the Netherlands, and China leading in publication output and institutional collaborations. Key research areas included VOC profiling for COPD, asthma, lung cancer, and COVID-19, as well as advances in real-time MS techniques and machine learning-based data interpretation. Co-citation analysis revealed a shift toward precision medicine and multi-omics integration, underscoring the field's transition from discovery to clinical translation. Despite challenges in standardization and reproducibility, MS-based breathomics holds transformative potential for respiratory diagnostics. This study provides a roadmap for future research priorities, emphasizing the need for interdisciplinary collaboration, composite biomarker validation, and artificial intelligence integration.
基于质谱（MS）的呼气分析已成为一种很有前景的非侵入性方法，可通过识别挥发性有机化合物（VOCs）来诊断和监测呼吸系统疾病。本研究对467篇出版物（2003 - 2024年）进行了全面的文献计量分析，以描绘该领域的全球研究趋势、有影响力的贡献者和主题热点。结果显示年增长率持续为11.03%，美国、英国、荷兰和中国在出版物产出和机构合作方面领先。关键研究领域包括慢性阻塞性肺疾病（COPD）、哮喘、肺癌和新冠肺炎的VOC分析，以及实时MS技术和基于机器学习的数据解读方面的进展。共被引分析揭示了向精准医学和多组学整合的转变，突显了该领域从发现到临床转化的过渡。尽管在标准化和可重复性方面存在挑战，但基于MS的呼吸组学在呼吸诊断方面具有变革潜力。本研究为未来的研究重点提供了路线图，强调了跨学科合作、复合生物标志物验证和人工智能整合的必要性。
