Abstract In silico methods can be used to estimate regional deposition of inhaled aerosols in regions of the lung that are inaccessible by direct measurements. Knowledge of deposited dose is important for assessing the efficacy of inhaled pharmaceutical aerosols or the impact from exposure to environmental pollutants. Although patient-specific geometries of the upper airways are widely used nowadays, insufficient imaging resolution precludes the reconstruction of 3D models of the deeper lung generations. In the present study, the 3D model of the deep lung (DLM) we have previously developed is utilised to examine the effects of breathing profile, breathhold and gravity orientation on deposition in the deep airways. The objective is to assess whether a small number of DLMs could be utilised to provide deposition predictions in the entire peripheral lung, with the ultimate goal being the integration of DLM with imaging-derived models of the upper airways for whole-lung deposition predictions. It is found that deposition in the respiratory region during deep breathing increases remarkably compared to quiet breathing since particles avoid retention in the conducting generations. Significant increases in deposition are recorded when breathhold is employed, with approximately 70% rise in total deposition of 1–2 μ m particles. Our findings indicate that the breathing maneuver can be used to target different deposition sites in the deep lung: deep inhalation followed by breathhold should be employed to achieve higher deposition in the respiratory region, whereas quiet inhalation followed by breathhold is recommended when targeting the deep conducting airways. Small differences in deposition during quiet inhalation are observed when the DLM is placed in seven different orientations relative to gravity. These differences are further reduced when realistic angle distributions are utilised for each of the five lung lobes and angle-weighted deposition fractions are compared. Our findings suggest that a small number of DLMs along with the distribution of gravity angles of an upper airway model could be employed to provide deposition estimates in the deep lung.

中文翻译：

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气溶胶沉积的全肺模拟：深肺模型

摘要 计算机模拟方法可用于估计直接测量无法到达的肺部区域中吸入气溶胶的区域沉积。了解沉积剂量对于评估吸入药物气雾剂的功效或暴露于环境污染物的影响很重要。虽然现在广泛使用上呼吸道的特定于患者的几何形状，但成像分辨率不足妨碍了更深肺代的 3D 模型的重建。在本研究中，我们之前开发的深肺 (DLM) 3D 模型用于检查呼吸剖面、屏气和重力方向对深呼吸道沉积的影响。目的是评估是否可以利用少量 DLM 来提供整个外周肺的沉积预测，最终目标是将 DLM 与上呼吸道的成像衍生模型相结合，以进行全肺沉积预测。发现与安静呼吸相比，深呼吸期间呼吸区域中的沉积显着增加，因为颗粒避免保留在传导代中。当采用屏气呼吸时，沉积量显着增加，1-2 μm 颗粒的总沉积量增加约 70%。我们的研究结果表明，呼吸动作可用于针对深肺中的不同沉积部位：应采用深吸气，然后屏气，以在呼吸区域实现更高的沉积，而针对深层传导气道时，建议安静吸入然后屏气。当 DLM 相对于重力以七个不同的方向放置时，在安静吸入期间观察到沉积的微小差异。当对五个肺叶中的每一个使用真实的角度分布并比较角度加权沉积分数时，这些差异会进一步减少。我们的研究结果表明，可以使用少量 DLM 以及上呼吸道模型的重力角分布来提供深肺中的沉积估计。当对五个肺叶中的每一个使用真实的角度分布并比较角度加权沉积分数时，这些差异会进一步减少。我们的研究结果表明，可以使用少量 DLM 以及上呼吸道模型的重力角分布来提供深肺中的沉积估计。当对五个肺叶中的每一个使用真实的角度分布并比较角度加权沉积分数时，这些差异会进一步减少。我们的研究结果表明，可以使用少量 DLM 以及上呼吸道模型的重力角分布来提供深肺中的沉积估计。