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首页> 外文期刊>Journal of Aerosol Science >Deposition of particles in the alveolar airways: Inhalation and breath-hold with pharmaceutical aerosols
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Deposition of particles in the alveolar airways: Inhalation and breath-hold with pharmaceutical aerosols

机译:肺泡气道中的颗粒沉积:药物气雾剂的吸入和屏气

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Previous studies have demonstrated that factors such as airway wall motion, inhalation waveform, and geometric complexity influence the deposition of aerosols in the alveolar airways. However, deposition fraction correlations are not available that account for these factors in determining alveolar deposition. The objective of this study was to generate a new space-filling model of the pulmonary acinus region and implement this model to develop correlations of aerosol deposition that can be used to predict the alveolar dose of inhaled pharmaceutical products. A series of acinar models was constructed containing different numbers of alveolar duct generations based on space-filling 14-hedron elements. Selected ventilation waveforms were quick-and-deep and slow-and-deep inhalation consistent with the use of most pharmaceutical aerosol inhalers. Computational fluid dynamics simulations were used to predict aerosol transport and deposition in the series of acinar models across various orientations with gravity where ventilation was driven by wall motion. Primary findings indicated that increasing the number of alveolar duct generations beyond 3 had a negligible impact on total acinar deposition, and total acinar deposition was not affected by gravity orientation angle. A characteristic model containing three alveolar duct generations (D3) was then used to develop correlations of aerosol deposition in the alveolar airways as a function of particle size and particle residence time in the geometry. An alveolar deposition parameter was determined in which deposition correlated with d(2)t over the first half of inhalation followed by correlation with dt(2), where d is the aerodynamic diameter of the particles and t is the potential particle residence time in the alveolar model. Optimal breath-hold times to allow 95% deposition of inhaled 1, 2, and 3 mu m particles once inside the alveolar region were approximately >10, 2.7, and 1.2 s, respectively. Coupling of the deposition correlations with previous stochastic individual path (SIP) model predictions of tracheobronchial deposition was demonstrated to predict alveolar dose of commercial pharmaceutical products. In conclusion, this study completes an initiative to determine the fate of inhaled pharmaceutical aerosols throughout the respiratory airways using CFD simulations. (C) 2014 Elsevier Ltd. All rights reserved.
机译:先前的研究表明,气道壁运动,吸入波形和几何形状复杂性等因素会影响肺泡气道中气溶胶的沉积。但是,尚无沉积分数相关性,这些相关性决定了确定肺泡沉积的原因。这项研究的目的是生成一个新的肺腺区域的空间填充模型,并实施该模型以开发气溶胶沉积的相关性,该相关性可用于预测吸入药物产品的肺泡剂量。基于空间填充的14面体元素,构建了一系列包含不同数量的肺泡管生成的腺泡模型。选择的通气波形为快速和深度吸入以及缓慢和深度吸入,这与大多数药物气雾剂吸入器的使用一致。计算流体动力学模拟用于预测一系列重力作用下一系列腺泡模型在重力作用下的气溶胶传输和沉积,其中重力由壁运动驱动。主要研究结果表明,增加的肺泡管生成数量超过3对总的腺泡沉积影响可忽略不计,并且总的腺泡沉积不受重力定向角的影响。然后,使用包含三个肺泡导管世代(D3)的特征模型来开发肺泡气道中气溶胶沉积的相关性,作为颗粒大小和颗粒在几何形状中停留时间的函数。确定了一个肺泡沉积参数,其中在吸入的前半段沉积与d(2)t相关,然后与dt(2)相关,其中d是颗粒的空气动力学直径,t是在颗粒中的潜在颗粒停留时间。牙槽模型。一旦进入肺泡区域,允许吸入的1、2和3μm颗粒95%沉积的最佳屏气时间分别约为10 s,2.7 s和1.2 s。沉积相关性与气管支气管沉积的先前随机个体路径(SIP)模型预测的耦合被证明可预测商业药品的肺泡剂量。总之,这项研究完成了一项使用CFD模拟确定整个呼吸道吸入药物气雾的命运的计划。 (C)2014 Elsevier Ltd.保留所有权利。

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