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空鼻综合征两种典型鼻腔结构气流场的数值模拟:一项计算流体动力学研究

Numerical simulation of airflow fields in two typical nasal structures of empty nose syndrome: a computational fluid dynamics study.

作者信息

Di Meng-Yang, Jiang Zhe, Gao Zhi-Qiang, Li Zhi, An Yi-Ran, Lv Wei

机构信息

Department of Otolaryngology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.

Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing, China.

出版信息

PLoS One. 2013 Dec 18;8(12):e84243. doi: 10.1371/journal.pone.0084243. eCollection 2013.

DOI:10.1371/journal.pone.0084243
PMID:24367645
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3867489/
Abstract

BACKGROUND

The pathogenesis of empty nose syndrome (ENS) has not been elucidated so far. Though postulated, there remains a lack of experimental evidence about the roles of nasal aerodynamics on the development of ENS.

OBJECTIVE

To investigate the nasal aerodynamic features of ENS andto explore the role of aerodynamic changes on the pathogenesis of ENS.

METHODS

Seven sinonasal models were numerically constructed, based on the high resolution computed tomography images of seven healthy male adults. Bilateral radical inferior/middle turbinectomy were numerically performed to mimic the typical nasal structures of ENS-inferior turbinate (ENS-IT) and ENS-middle turbinate (ENS-MT). A steady laminar model was applied in calculation. Velocity, pressure, streamlines, air flux and wall shear stress were numerically investigated. Each parameter of normal structures was compared with those of the corresponding pathological models of ENS-IT and ENS-MT, respectively.

RESULTS

ENS-MT: Streamlines, air flux distribution, and wall shear stress distribution were generally similar to those of the normal structures; nasal resistances decreased. Velocities decreased locally, while increased around the sphenopalatine ganglion by 0.20 ± 0.17 m/s and 0.22 ± 0.10 m/s during inspiration and expiration, respectively. ENS-IT: Streamlines were less organized with new vortexes shown near the bottom wall. The airflow rates passing through the nasal olfactory area decreased by 26.27% ± 8.68% and 13.18% ± 7.59% during inspiration and expiration, respectively. Wall shear stresses, nasal resistances and local velocities all decreased.

CONCLUSION

Our CFD simulation study suggests that the changes in nasal aerodynamics may play an essential role in the pathogenesis of ENS. An increased velocity around the sphenopalatine ganglion in the ENS-MT models could be responsible for headache in patients with ENS-MT. However, these results need to be validated in further studies with a larger sample size and more complicated calculating models.

摘要

背景

迄今为止,空鼻综合征(ENS)的发病机制尚未阐明。尽管有相关推测,但关于鼻空气动力学在ENS发展中的作用仍缺乏实验证据。

目的

研究ENS的鼻空气动力学特征,并探讨空气动力学变化在ENS发病机制中的作用。

方法

基于7名健康成年男性的高分辨率计算机断层扫描图像,数值构建了7个鼻窦模型。通过数值模拟双侧下/中鼻甲根治切除术,以模拟ENS下鼻甲(ENS-IT)和ENS中鼻甲(ENS-MT)的典型鼻腔结构。计算采用稳定层流模型。对速度、压力、流线、气流量和壁面剪应力进行了数值研究。将正常结构的每个参数分别与ENS-IT和ENS-MT相应病理模型的参数进行比较。

结果

ENS-MT:流线、气流量分布和壁面剪应力分布与正常结构总体相似;鼻阻力降低。吸气和呼气时,速度局部降低,而蝶腭神经节周围速度分别增加0.20±0.17 m/s和0.22±0.10 m/s。ENS-IT:流线组织性较差,底壁附近出现新的涡流。吸气和呼气时,通过鼻腔嗅觉区域的气流速率分别降低26.27%±8.68%和13.18%±7.59%。壁面剪应力、鼻阻力和局部速度均降低。

结论

我们的计算流体动力学模拟研究表明,鼻空气动力学变化可能在ENS发病机制中起重要作用。ENS-MT模型中蝶腭神经节周围速度增加可能是ENS-MT患者头痛的原因。然而,这些结果需要在更大样本量和更复杂计算模型的进一步研究中得到验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/af9a24fe6976/pone.0084243.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/34c5052d2500/pone.0084243.g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/a1d5242918a6/pone.0084243.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/e297fe3de675/pone.0084243.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/6c93af6492ca/pone.0084243.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/97b0e3768d8a/pone.0084243.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/af9a24fe6976/pone.0084243.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/34c5052d2500/pone.0084243.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/079fade8c690/pone.0084243.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/a1d5242918a6/pone.0084243.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/e297fe3de675/pone.0084243.g005.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/97b0e3768d8a/pone.0084243.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4b8/3867489/af9a24fe6976/pone.0084243.g008.jpg

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