Departamento de Energía, Universidad de Oviedo, and GRUBIPU-ISPA, Gijón, Spain.
Hospital Universitario Central de Asturias, Oviedo, Spain.
J Breath Res. 2023 Jul 21;17(4). doi: 10.1088/1752-7163/ace6c7.
Understanding particle deposition in the human lung is crucial for the assessment of environmental pollutants and the design of new drug delivery systems. Traditionally, research has been carried out by experimental analysis, but this generally requires expensive equipment and exposure of volunteers to radiation, resulting in limited data. To overcome these drawbacks, there is an emphasis on the development of numerical models capable of accurate predictive analysis. The most advanced of these computer simulations are based on three-dimensional computational fluid dynamics. Solving the flow equations in a complete, fully resolved lung airway model is currently not feasible due to the computational resources required. In the present work, a simplified lung model is presented and validated for accurate prediction of particle deposition. Simulations are performed for an 8-path approximation to a full lung airway model. A novel boundary condition method is used to ensure accurate results in truncated flow branches. Simulations are performed at a steady inhalation flow rate of 18 l min, corresponding to a low activity breathing rate, while the effects of particle size and density are investigated. Comparison of the simulation results with available experimental data shows that reasonably accurate results can be obtained at a small fraction of the cost of a full airway model. The simulations clearly evaluate the effect of both particle size and particle density. Most importantly, the results show an improvement over a previously documented single-path model, both in terms of accuracy and the ability to obtain regional deposition rates. The present model represents an improvement over previously used simplified models, including single-path models. The multi-path reduced airway approach described can be used by researchers for general and patient-specific analyses of particle deposition and for the design of effective drug delivery systems.
了解粒子在人体肺部的沉积对于评估环境污染物和设计新的药物输送系统至关重要。传统上，研究是通过实验分析进行的，但这通常需要昂贵的设备和志愿者暴露在辐射下，导致数据有限。为了克服这些缺点，人们越来越重视开发能够进行准确预测分析的数值模型。其中最先进的计算机模拟是基于三维计算流体动力学的。由于所需的计算资源，目前在完整的、完全解析的肺气道模型中求解流动方程是不可行的。在本工作中，提出并验证了一种简化的肺部模型，用于准确预测粒子沉积。对全肺气道模型的 8 路径近似进行了模拟。使用一种新的边界条件方法来确保在截断的流动分支中获得准确的结果。模拟在 18 l min 的稳定吸入流速下进行，相当于低活动呼吸率，同时研究了粒子大小和密度的影响。将模拟结果与现有实验数据进行比较表明，在气道全模型成本的一小部分上可以获得相当准确的结果。模拟结果清楚地评估了粒子大小和密度的影响。最重要的是，结果表明与以前记录的单路径模型相比，无论是在准确性还是获取局部沉积率的能力方面都有所改进。与以前使用的简化模型相比，本模型有所改进，包括单路径模型。所描述的多路径简化气道方法可被研究人员用于粒子沉积的一般和患者特定分析以及有效药物输送系统的设计。
