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用于气流和气溶胶剂量学的肺内混合计算机模型的实用性。

The utility of hybrid in silico models of airflow and aerosol dosimetry in the lung.

机构信息

Department of Bioengineering, Northeastern University, Boston, MA 02115.

出版信息

J Biomech. 2024 May;168:112126. doi: 10.1016/j.jbiomech.2024.112126. Epub 2024 Apr 27.

DOI:10.1016/j.jbiomech.2024.112126
PMID:38718595
Abstract

The development and application of multi-scale models of the lung has significantly increased in recent years. These hybrid models merge realistic representations of the larger airways with lower-dimensional descriptions of the bronchioles and respiratory airways. Due to recent advancements, it is possible to calculate airflow and dosimetry throughout the entire lung, enabling model validation with human or animal data. Here, we present a hybrid modeling pipeline and corresponding characteristic airflow and particle deposition hotspots. Next, we discuss the limitations of current hybrid models, including the need to update lower-dimensional deposition function descriptions to better represent realistic airway geometries. Future directions should include modeling diseased lungs and use of machine learning to predict whole lung dosimetry maps for a wider population.

摘要

近年来,肺部多尺度模型的开发和应用显著增加。这些混合模型将较大气道的真实表示与细支气管和呼吸气道的低维描述相结合。由于最近的进展,现在可以计算整个肺部的气流和剂量分布,从而可以使用人体或动物数据对模型进行验证。在这里,我们提出了一种混合建模管道和相应的特征气流和颗粒沉积热点。接下来,我们讨论了当前混合模型的局限性,包括需要更新低维沉积函数描述以更好地表示真实的气道几何形状。未来的方向应包括对患病肺部的建模以及使用机器学习来预测更广泛人群的整个肺部剂量图。

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