School of Chemical Engineering, Oklahoma State University, Stillwater, OK 74078, USA.
School of Chemical Engineering, Oklahoma State University, Stillwater, OK 74078, USA.
Comput Biol Med. 2020 Jan;116:103532. doi: 10.1016/j.compbiomed.2019.103532. Epub 2019 Nov 9.
Computational Fluid-Particle Dynamics (CFPD) models have been employed to predict lung aerosol dynamics for decades, estimating the delivery efficiency of inhaled drugs into the tracheobronchial tree. However, existing CFPD models assume the glottis is static during the breathing cycle. Failing to capture the dynamic motion of the glottis may introduce significant errors in drug deposition estimations.
A novel CFPD model was developed with the capability of modeling the glottis motion using the dynamic mesh method. To explore the causal relationships between the glottis motion and the inhaled drug particle dynamics, simulations were performed to compare static and different dynamic glottis models in a subject-specific mouth-to-trachea geometry under idealized sinusoidal and realistic breathing waveforms. By defining the movement of each node in the glottis region using a generalized glottis motion function (GGMF) validated with clinical data, the abduction and adduction of the glottis were accurately described. Transient transport characteristics of inhaled particle-laden airflows were investigated and analyzed, including the glottis motion effect on the inhaled particles with the aerodynamic diameters from 0.1 to 10 μm.
Numerical results indicate that the static glottis assumption deviates the total deposition fraction predictions by more than 8% in relative differences. Compared with the CFPD models with the static glottis assumption, the dynamic glottis model can more realistically predict the complexity of the secondary flows near the vocal fold and the resultant particle depositions. Inter-subject variabilities of the glottis motion patterns were observed, and their influences on particle transport dynamics are not uniform. Parametric analyses also demonstrate that the maximum deformation ratio of the glottis is a key feature to describe whether the glottis motion can enhance or reduce particle depositions in the mouth-to-trachea region, over the static glottis model.
The glottis motion shows a significant influence on the accuracy of predicting inhaled particle dynamics, and it should be integrated into CFPD simulations validated by subject-specific glottis motion data from clinical studies in the future. Furthermore, the proposed dynamic glottis model has been demonstrated to be a computationally effective method to recover the physiologically realistic motions of the glottis, and ready to be added into the next-generation holistic virtual lung modeling approach.
计算流体-颗粒动力学 (CFPD) 模型已被用于预测肺部气溶胶动力学数十年，以估计吸入药物在气管支气管树中的输送效率。然而，现有的 CFPD 模型假设声门在呼吸周期内是静态的。未能捕捉声门的动态运动可能会导致药物沉积估计产生重大误差。
开发了一种新的 CFPD 模型，该模型具有使用动态网格方法建模声门运动的能力。为了探索声门运动与吸入药物颗粒动力学之间的因果关系，在理想正弦和真实呼吸波形下，对特定于受试者的口腔到气管几何形状中的静态和不同动态声门模型进行了模拟。通过使用经过临床数据验证的广义声门运动函数 (GGMF) 定义声门区域中每个节点的运动，准确描述了声门的外展和内收。研究和分析了吸入颗粒载气流的瞬态输运特性，包括声门运动对气动直径为 0.1 至 10μm 的吸入颗粒的影响。
数值结果表明，静态声门假设使总沉积分数预测的相对差异超过 8%。与静态声门假设的 CFPD 模型相比，动态声门模型可以更真实地预测声带附近二次流的复杂性以及由此产生的颗粒沉积。观察到声门运动模式的个体间变异性，并且它们对颗粒输运动力学的影响并不均匀。参数分析还表明，声门的最大变形比是描述声门运动是否可以增强或减少口腔到气管区域内颗粒沉积的关键特征，超过静态声门模型。
声门运动对预测吸入颗粒动力学的准确性有显著影响，未来应将其整合到通过临床研究中特定于受试者的声门运动数据验证的 CFPD 模拟中。此外，所提出的动态声门模型已被证明是一种恢复声门生理现实运动的计算有效方法，并且准备添加到下一代整体虚拟肺建模方法中。
