Suppr超能文献

与睡眠呼吸障碍相关的咽气流模式。

Patterns in pharyngeal airflow associated with sleep-disordered breathing.

机构信息

Stanford University School of Medicine, Department of Otolaryngology and Division of Sleep Medicine, Atherton, CA 94027, USA.

出版信息

Sleep Med. 2011 Dec;12(10):966-74. doi: 10.1016/j.sleep.2011.08.004. Epub 2011 Oct 28.

Abstract

OBJECTIVE

To establish the feasibility of a noninvasive method to identify pharyngeal airflow characteristics in sleep-disordered breathing.

METHODS

Four patients with sleep-disordered breathing who underwent surgery or used positive airway pressure devices and four normal healthy controls were studied. Three-dimensional CT imaging and computational fluid dynamics modeling with standard steady-state numerical formulation were used to characterize pharyngeal airflow behavior in normals and pre-and post-treatment in patients. Dynamic flow simulations using an unsteady approach were performed in one patient.

RESULTS

The pre-treatment pharyngeal airway below the minimum cross-sectional area obstruction site showed airflow separation. This generated recirculation airflow regions and enhanced turbulence zones where vortices developed. This interaction induced large fluctuations in airflow variables and increased aerodynamic forces acting on the pharyngeal wall. At post-treatment, for the same volumetric flow rate, airflow field instabilities vanished and airflow characteristics improved. Mean maximum airflow velocity during inspiration reduced from 18.3±5.7 m/s pre-treatment to 6.3±4.5 m/s post-treatment (P=0.002), leading to a reduction in maximum wall shear stress from 4.8±1.7 Pa pre-treatment to 0.9±1.0 Pa post-treatment (P=0.01). The airway resistance improved from 4.3±1.4 Pa/L/min at pre-treatment to 0.7±0.7 Pa/L/min at post-treatment (P=0.004). Post-treatment airflow characteristics were not different from normal controls (all P ≥ 0.39).

CONCLUSION

This study demonstrates that pharyngeal airflow variables may be derived from CT imaging and computational fluid dynamics modeling, resulting in high quality visualizations of airflow characteristics of axial velocity, static pressure, and wall shear stress in sleep-disordered breathing.

摘要

目的

建立一种非侵入性方法,以识别睡眠呼吸障碍中的咽气流特征。

方法

研究了 4 名接受过手术或使用正压气道装置治疗的睡眠呼吸障碍患者和 4 名正常健康对照者。使用三维 CT 成像和基于标准稳态数值公式的计算流体动力学模型,对正常人和患者治疗前后的咽气流行为进行了特征描述。对 1 名患者进行了使用非稳态方法的动态流动模拟。

结果

在最小截面积阻塞部位下方的预治疗咽气道出现气流分离。这会产生回流气流区域和增强的湍流区域,涡流在此处发展。这种相互作用导致气流变量的大幅波动,并增加了作用在咽壁上的空气动力。在治疗后,对于相同的体积流量,气流场的不稳定性消失,气流特征得到改善。吸气时的平均最大气流速度从治疗前的 18.3±5.7 m/s 降低到治疗后的 6.3±4.5 m/s(P=0.002),从而使最大壁面剪切应力从治疗前的 4.8±1.7 Pa 降低到治疗后的 0.9±1.0 Pa(P=0.01)。气道阻力从治疗前的 4.3±1.4 Pa/L/min 改善到治疗后的 0.7±0.7 Pa/L/min(P=0.004)。治疗后的气流特征与正常对照组无差异(所有 P≥0.39)。

结论

本研究表明,咽气流变量可从 CT 成像和计算流体动力学模型中获得,从而对睡眠呼吸障碍中的轴向速度、静压和壁面剪切应力的气流特征进行高质量可视化。

相似文献

1
Patterns in pharyngeal airflow associated with sleep-disordered breathing.与睡眠呼吸障碍相关的咽气流模式。
Sleep Med. 2011 Dec;12(10):966-74. doi: 10.1016/j.sleep.2011.08.004. Epub 2011 Oct 28.

引用本文的文献

本文引用的文献

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验