基于CFD的气道病毒浓度分析的评价

Yoshiki Yanagita, Kaishan Feng, Yuko Miyamura, Adi Azriff Basri, Mohammad Zuber, Siti Rohani, Abdul Aziz, Kamarul Arifin Ahmad, Masaaki Tamagawa
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引用次数: 0

摘要

当前,新冠肺炎疫情在全球蔓延。当病毒通过呼吸直接附着在气道粘膜上时,一些人在感染的第一阶段可能会产生病毒的炎症反应。气道由鼻腔、鼻窦(上颌窦、筛窦、额窦和蝶窦)和肺组成。在感染阶段,位于鼻腔的鼻窦往往表现出特别高的病毒浓度。因此,定量评估包括鼻窦在内的鼻腔中病毒可能粘附的区域是很重要的。在本研究中,通过CFD包括浓度分析,预测了病毒在鼻腔内可能粘附的区域。方法采用Itk-SNAP软件对二维ct图像数据进行鼻腔成像。鼻腔连续性方程的计算采用了Navier-Stokes方程和输运方程。并计算浓度在鼻腔4个部位的输运情况。结果发现,筛窦内浓度与初始浓度之比约为0.6。发现筛窦是病毒最容易粘附的区域,通过计算病毒浓度可以预测病毒粘附的区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of Virus Concentration Analysis in the Airway by CFD
Currently, Covid-19 is an epidemic all over the world. When virus directly adhere to mucous membrane of airway by breath, some humans maybe get inflammatory responses by viruses in the first stage of infection. The airway is composed of the nasal cavity, sinuses (Maxillary Sinus, Ethmoid Sinus, Frontal Sinus and Sphenoidal Sinus) and lungs. In the infection stage, the sinuses located in the nasal cavity tend to exhibit particularly high virus concentrations. Therefore, it is important to evaluate quantitatively the areas where viruses are likely to be adhered in the nasal cavity including sinuses. In this study, by CFD including concentration analysis the areas where viruses are likely to be adhered in the nasal cavity are predicted. As for the methods, the nasal cavity was made from 2D-CT image data by Itk-SNAP. For this computation in the nasal cavity continuity equation, Navier-Stokes equation and transport equation are used. And the transport of concentration was computed in the divided 4 parts of nasal cavity. As a result, it was found that the ratio of the concentration to the initial concentration in Ethmoid Sinus is approximately 0.6. It was found that Ethmoid Sinus is the areas where viruses are likely to be adhered and the areas can be predicted by computing the concentration.
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