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干粉吸入器产生的药用气雾剂沉积模式:欧拉-拉格朗日预测与验证

Pharmaceutical aerosols deposition patterns from a Dry Powder Inhaler: Euler Lagrangian prediction and validation.

作者信息

Ravi Kannan Ravishekar, Przekwas A J, Singh Narender, Delvadia Renishkumar, Tian Geng, Walenga Ross

机构信息

CFD Research Corporation, 701 McMillian Way NW, Suite D, Huntsville, AL 35806, USA.

CFD Research Corporation, 701 McMillian Way NW, Suite D, Huntsville, AL 35806, USA.

出版信息

Med Eng Phys. 2017 Apr;42:35-47. doi: 10.1016/j.medengphy.2016.11.007. Epub 2016 Dec 16.

Abstract

This study uses Computational Fluid Dynamics (CFD) to predict, analyze and validate the deposition patterns in a human lung for a Budesonide drug delivered from the Novolizer Dry Powder Inhaler device. We used a test case of known deposition patterns to validate our computational Euler Lagrangian-based deposition predictions. Two different lung models are used: (i) a basic ring-less trachea model and (ii) an advanced Human Zygote5 model. Unlike earlier attempts, the current simulations do not include the device in the computational domain. This greatly reduces the computational effort. To mimic the device, we model the inlet particle jet stream from the device as a spray entering the mouth in a conical fashion. Deposition studies in the various lung regions were performed. We were able to computationally predict and then demonstrate the enhanced deposition in the tracheal and first generation rings/ridges. The enhanced vorticity creation due to the ring structure and the geometrical design contributes to larger deposition in the Zygote5 model. These are in accord with existing data, unlike the ring-less model. Our validated results indicate the need to (i) introduce the ridges in the experimental casts and the CFD surface meshes to be anatomically consistent and obtain physiologically consistent depositions; (ii) introduce a factor to account for the recirculating lighter particles in empirical models.

摘要

本研究使用计算流体动力学(CFD)来预测、分析和验证从诺沃利泽干粉吸入器装置递送的布地奈德药物在人肺中的沉积模式。我们使用已知沉积模式的测试案例来验证基于欧拉-拉格朗日计算的沉积预测。使用了两种不同的肺模型:(i)基本的无环气管模型和(ii)先进的人类合子5模型。与早期尝试不同,当前模拟在计算域中不包括该装置。这大大减少了计算量。为了模拟该装置,我们将来自该装置的入口颗粒射流建模为以锥形方式进入口腔的喷雾。对各个肺区域进行了沉积研究。我们能够通过计算预测并随后证明在气管和第一代环/嵴中的沉积增强。由于环结构和几何设计导致的涡度增加有助于在合子5模型中实现更大的沉积。与无环模型不同,这些结果与现有数据一致。我们经过验证的结果表明需要:(i)在实验模型和CFD表面网格中引入嵴,以在解剖学上保持一致并获得生理上一致的沉积;(ii)在经验模型中引入一个因素来考虑较轻颗粒的再循环。

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