Suppr超能文献

使用可调谐二极管激光光谱法评估人体鼻窦腔空气体积及其在鼻窦炎诊断中的应用。

Assessment of human sinus cavity air volume using tunable diode laser spectroscopy, with application to sinusitis diagnostics.

作者信息

Huang Jing, Zhang Hao, Li Tianqi, Lin Huiying, Svanberg Katarina, Svanberg Sune

机构信息

Center for Optics and Electromagnetic Research, South China Normal University, University City Campus, Guangzhou, 510006, China.

Lund Laser Center, Lund University, SE-221 00, Lund, Sweden.

出版信息

J Biophotonics. 2015 Nov;8(11-12):985-92. doi: 10.1002/jbio.201500110. Epub 2015 May 20.

Abstract

Sinusitis is a very common disease and improved diagnostic tools are desirable also in view of reducing over-prescription of antibiotics. A non-intrusive optical technique called GASMAS (GAs in Scattering Media Absorption Spectroscopy), which has a true potential of being developed into an important complement to other means of detection, was utilized in this work. Water vapor in the frontal sinuses, related to the free gas volume, was studied at around 937 nm in healthy volunteers. The results show a good stability of the GASMAS signals over extended times for the frontal sinuses for all volunteers, showing promising applicability to detect anomalies due to sinusitis. Measurements were also performed following the application of a decongestion spray. No noticeable signal change was observed, which is consistent with the fact that the water vapor concentration is given by the temperature only, and is not influenced by changes in cavity ventilation. Evaluated GASMAS data recorded on 6 consecutive days show signal stability for the left and right frontal sinus in one of the test volunteers.

摘要

鼻窦炎是一种非常常见的疾病,鉴于减少抗生素的过度处方,改进诊断工具是很有必要的。本研究采用了一种名为GASMAS(散射介质中气体吸收光谱)的非侵入性光学技术,该技术具有发展成为其他检测手段重要补充的真正潜力。在健康志愿者中,研究了额窦中与自由气体体积相关的水蒸气,波长约为937nm。结果表明,所有志愿者额窦的GASMAS信号在较长时间内具有良好的稳定性,显示出在检测鼻窦炎引起的异常方面具有广阔的应用前景。在使用减充血喷雾剂后也进行了测量。未观察到明显的信号变化,这与水蒸气浓度仅由温度决定且不受腔室通气变化影响的事实一致。对一名测试志愿者连续6天记录的GASMAS数据进行评估,结果显示其左右额窦信号稳定。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验