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Correlations between computational fluid dynamics and clinical evaluation of nasal airway obstruction due to septal deviation: An observational study.鼻中隔偏曲所致鼻气道阻塞的计算流体动力学与临床评估的相关性:一项观察性研究。
Clin Otolaryngol. 2019 Jul;44(4):603-611. doi: 10.1111/coa.13344. Epub 2019 May 16.
2
Sensitivity of nasal airflow variables computed via computational fluid dynamics to the computed tomography segmentation threshold.通过计算流体动力学计算的鼻气流变量对计算机断层扫描分割阈值的敏感性。
PLoS One. 2018 Nov 16;13(11):e0207178. doi: 10.1371/journal.pone.0207178. eCollection 2018.
3
Nasal surgery handled by CFD tools.鼻外科手术由 CFD 工具处理。
Int J Numer Method Biomed Eng. 2018 Oct;34(10):e3126. doi: 10.1002/cnm.3126. Epub 2018 Jul 24.
4
DigBody: A new 3D modeling tool for nasal virtual surgery.DigBody:一种用于鼻虚拟手术的新型 3D 建模工具。
Comput Biol Med. 2018 Jul 1;98:118-125. doi: 10.1016/j.compbiomed.2018.05.016. Epub 2018 May 16.
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Virtual Surgery for the Nasal Airway: A Preliminary Report on Decision Support and Technology Acceptance.鼻腔气道虚拟手术:决策支持和技术接受度的初步报告。
JAMA Facial Plast Surg. 2018 Jan 1;20(1):63-69. doi: 10.1001/jamafacial.2017.1554.
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Computational modeling and validation of human nasal airflow under various breathing conditions.不同呼吸条件下人体鼻腔气流的计算建模与验证
J Biomech. 2017 Nov 7;64:59-68. doi: 10.1016/j.jbiomech.2017.08.031. Epub 2017 Sep 5.
7
Robust nondimensional estimators to assess the nasal airflow in health and disease.用于评估健康和疾病状态下鼻气流的稳健无量纲估计器。
Int J Numer Method Biomed Eng. 2018 Jan;34(1). doi: 10.1002/cnm.2906. Epub 2017 Jul 27.
8
New CFD tools to evaluate nasal airflow.用于评估鼻腔气流的新型计算流体动力学工具。
Eur Arch Otorhinolaryngol. 2017 Aug;274(8):3121-3128. doi: 10.1007/s00405-017-4611-y. Epub 2017 May 25.
9
Correlation between Subjective Nasal Patency and Intranasal Airflow Distribution.主观鼻腔通畅度与鼻内气流分布之间的相关性
Otolaryngol Head Neck Surg. 2017 Apr;156(4):741-750. doi: 10.1177/0194599816687751. Epub 2017 Jan 31.
10
Estimates of nasal airflow at the nasal cycle mid-point improve the correlation between objective and subjective measures of nasal patency.在鼻周期中点对鼻气流的估计可改善鼻通畅客观测量与主观测量之间的相关性。
Respir Physiol Neurobiol. 2017 Apr;238:23-32. doi: 10.1016/j.resp.2017.01.004. Epub 2017 Jan 9.

健康成年人鼻气流变量的参考范围。

Normative ranges of nasal airflow variables in healthy adults.

机构信息

Department of Otolaryngology and Communication Sciences, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.

Department of Biomedical Engineering, Marquette University & The Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.

出版信息

Int J Comput Assist Radiol Surg. 2020 Jan;15(1):87-98. doi: 10.1007/s11548-019-02023-y. Epub 2019 Jul 2.

DOI:10.1007/s11548-019-02023-y
PMID:31267334
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6939154/
Abstract

PURPOSE

Virtual surgery planning based on computational fluid dynamics (CFD) simulations of nasal airflow has the potential to improve surgical outcomes for patients with nasal airway obstruction (NAO). Virtual surgery planning requires normative ranges of airflow variables, but few studies to date have quantified inter-individual variability of nasal airflow among healthy subjects. This study reports CFD simulations of nasal airflow in 47 healthy adults.

METHODS

Anatomically accurate three-dimensional nasal models were reconstructed from cone beam computed tomography scans and used for steady-state inspiratory airflow simulations with a bilateral flowrate of 250 ml/s. Normal subjective sensation of nasal patency was confirmed using the nasal obstruction symptom evaluation and visual analog scale. Healthy ranges for several CFD variables known to correlate with subjective nasal patency were computed, including unilateral airflow, nasal resistance, airspace minimal cross-sectional area (mCSA), heat flux (HF), and surface area stimulated by mucosal cooling (defined as the area where HF > 50 W/m). The normative ranges were targeted to contain 95% of the healthy population and computed using a nonparametric method based on order statistics.

RESULTS

A wide range of inter-individual variability in nasal airflow was observed among healthy subjects. Unilateral airflow varied from 60 to 191 ml/s, airflow partitioning ranged from 23.8 to 76.2%, and unilateral mCSA varied from 0.24 to 1.21 cm. These ranges are in good agreement with rhinomanometry and acoustic rhinometry data from the literature. A key innovation of this study are the normative ranges of flow variables associated with mucosal cooling, which recent research suggests is the primary physiological mechanism of nasal airflow sensation. Unilateral HF ranged from 94 to 281 W/m, while the surface area stimulated by cooling ranged from 27.4 to 64.3 cm.

CONCLUSIONS

These normative ranges may serve as targets in future virtual surgery planning for patients with NAO.

摘要

目的

基于计算流体动力学(CFD)模拟的鼻气流虚拟手术规划有可能改善鼻气道阻塞(NAO)患者的手术效果。虚拟手术规划需要气流变量的规范范围,但迄今为止,很少有研究量化健康受试者之间鼻气流的个体间变异性。本研究报告了 47 名健康成年人的鼻气流 CFD 模拟。

方法

使用锥形束计算机断层扫描重建解剖精确的三维鼻模型,并使用双侧流量为 250 ml/s 的稳态吸气气流模拟。通过鼻阻塞症状评估和视觉模拟量表确认正常的鼻腔通畅感。计算了几个与主观鼻腔通畅感相关的 CFD 变量的健康范围,包括单侧气流、鼻腔阻力、空气空间最小横截面积(mCSA)、热通量(HF)和粘膜冷却刺激的表面积(定义为 HF>50 W/m 的区域)。使用基于有序统计的非参数方法计算包含 95%健康人群的规范范围。

结果

在健康受试者中观察到鼻气流的个体间变异性很大。单侧气流从 60 到 191 ml/s 不等,气流分配范围从 23.8 到 76.2%,单侧 mCSA 从 0.24 到 1.21 cm 不等。这些范围与文献中的鼻测压法和声学鼻测法数据吻合良好。本研究的一个关键创新是与粘膜冷却相关的流动变量的规范范围,最近的研究表明,这是鼻气流感觉的主要生理机制。单侧 HF 从 94 到 281 W/m 不等,而冷却刺激的表面积从 27.4 到 64.3 cm 不等。

结论

这些规范范围可作为未来 NAO 患者虚拟手术规划的目标。