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什么是正常的鼻腔气流?对22名健康成年人的计算研究。

What is normal nasal airflow? A computational study of 22 healthy adults.

作者信息

Zhao Kai, Jiang Jianbo

机构信息

Monell Chemical Senses Center, Philadelphia, PA; Department of Otolaryngology, Thomas Jefferson University, Philadelphia, PA.

出版信息

Int Forum Allergy Rhinol. 2014 Jun;4(6):435-46. doi: 10.1002/alr.21319. Epub 2014 Mar 24.

Abstract

BACKGROUND

Nasal airflow is essential for the functioning of the human nose. Given individual variation in nasal anatomy, there is yet no consensus what constitutes normal nasal airflow patterns. We attempt to obtain such information that is essential to differentiate disease-related conditions.

METHODS

Computational fluid dynamics (CFD) simulated nasal airflow in 22 healthy subjects during resting breathing. Streamline patterns, airflow distributions, velocity profiles, pressure, wall stress, turbulence, and vortical flow characteristics under quasi-steady state were analyzed. Patency ratings, acoustically measured minimum cross-sectional area (MCA), and rhinomanometric nasal resistance (NR) were examined for potential correlations with morphological and airflow-related variables.

RESULTS

Common features across subjects included: >50% total pressure drop reached near the inferior turbinate head; wall shear stress, NR, turbulence energy, and vorticity were lower in the turbinate than in the nasal valve region. However, location of the major flow path and coronal velocity distributions varied greatly across individuals. Surprisingly, on average, more flow passed through the middle than the inferior meatus and correlated with better patency ratings (r = -0.65, p < 0.01). This middle flow percentage combined with peak postvestibule nasal heat loss and MCA accounted for >70% of the variance in subjective patency ratings and predicted patency categories with 86% success. Nasal index correlated with forming of the anterior dorsal vortex. Expected for resting breathing, the functional impact for local and total turbulence, vorticity, and helicity was limited. As validation, rhinomanometric NR significantly correlated with CFD simulations (r = 0.53, p < 0.01).

CONCLUSION

Significant variations of nasal airflow found among healthy subjects; Key features may have clinically relevant applications.

摘要

背景

鼻气流对人类鼻子的功能至关重要。鉴于鼻腔解剖结构存在个体差异,对于什么构成正常鼻气流模式尚无共识。我们试图获取对于区分疾病相关状况至关重要的此类信息。

方法

计算流体动力学(CFD)模拟了22名健康受试者静息呼吸时的鼻气流。分析了准稳态下的流线模式、气流分布、速度剖面、压力、壁面应力、湍流和涡旋流特征。检查了通畅评级、声学测量的最小横截面积(MCA)和鼻阻力测量法测得的鼻阻力(NR)与形态学和气流相关变量之间的潜在相关性。

结果

受试者的共同特征包括:在下鼻甲头部附近总压降达到>50%;鼻甲处的壁面剪应力、NR、湍流能量和涡度低于鼻瓣区。然而,主要流动路径的位置和冠状速度分布在个体间差异很大。令人惊讶的是,平均而言,通过中鼻道的气流比下鼻道更多,且与更好的通畅评级相关(r = -0.65,p < 0.01)。这个中鼻道气流百分比与前庭后鼻热损失峰值和MCA相结合,解释了主观通畅评级中>70%的方差,并以86%的成功率预测了通畅类别。鼻指数与前背涡的形成相关。对于静息呼吸而言,局部和整体湍流、涡度和螺旋度的功能影响有限。作为验证,鼻阻力测量法测得的NR与CFD模拟显著相关(r = 0.53,p < 0.01)。

结论

健康受试者中发现鼻气流存在显著差异;关键特征可能具有临床相关应用。

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