1D network simulations for evaluating regional flow and pressure distributions in healthy and asthmatic human lungs

Abstract

This study aimed to introduce a one-dimensional (1D) computational fluid dynamics (CFD) model for airway resistance and lung compliance to examine the relationship between airway resistance, pressure, and regional flow distribution. We employed five healthy and five asthmatic subjects who had dynamic computed tomography (CT) scans (4D CT) along with two static scans at total lung capacity and functional residual capacity. Fractional air-volume change ([Formula: see text]) from 4D CT was used for a validation of the 1D CFD model. We extracted the diameter ratio from existing data sets of 61 healthy subjects for computing mean and standard deviation (SD) of airway constriction/dilation in CT-resolved airways. The lobar mean (SD) of airway constriction/dilation was used to determine diameters of CT-unresolved airways. A 1D isothermal energy balance equation was solved, and pressure boundary conditions were imposed at the acinar region ( model A) or at the pleural region ( model B). A static compliance model was only applied for model B to link acinar and pleural regions. The values of 1D CFD-derived [Formula: see text] for model B demonstrated better correlation with 4D CT-derived [Formula: see text] than model A. In both inspiration and expiration, asthmatic subjects with airway constriction show much greater pressure drop than healthy subjects without airway constriction. This increased transpulmonary pressures in the asthmatic subjects, leading to an increased workload (hysteresis). The 1D CFD model was found to be useful in investigating flow structure, lung hysteresis, and pressure distribution for healthy and asthmatic subjects. The derived flow distribution could be used for imposing boundary conditions of 3D CFD. NEW & NOTEWORTHY A one-dimensional (1D) computational fluid dynamics (CFD) model for airway resistance and lung compliance was introduced to examine the relationship between airway resistance, pressure, and regional flow distribution. The 1D CFD model investigated differences of flow structure, lung hysteresis, and pressure distribution for healthy and asthmatic subjects. The derived flow distribution could be used for imposing boundary conditions of three-dimensional CFD.

Sound transmission in human thorax through airway insonification: an experimental and computational study with diagnostic applications

“…In the current work, the computational model aims to be more precise in comparison to the standard pulmonary function tests (PFT) by incorporating more region specific information with respect to the change of tissue viscoelastic properties due to pathologies such as PTX, fibrosis and tumors. The current work complements earlier research led by Tawhai et al [ 26 ] and lays down the scope and foundation for a more region-specific and precise assessment of mechanical wave motion inside human lung parenchyma by incorporating a detailed airway structure.…”

“…In the past year or two, researchers have been able to demonstrate commendable success in validation and usage of computational models in order to gain an insight into pulmonary diseases from a clinical point of view. For example, in 2019, the research group led by Tawhai and Lin (Choi et al [ 26 ]) developed a one dimensional CFD model to simulate the flow and pressure distribution of air in a healthy and an asthmatic lung and validated their results experimentally on 5 healthy and 5 asthmatic human subjects. The study determined flow distribution patterns inside healthy and asthmatic lungs and these experimentally validated flow distribution patterns can be used for imposing boundary conditions of three-dimensional CFD.…”

Towards a multi-scale computer modeling workflow for simulation of pulmonary ventilation in advanced COVID-19

“…Utilization of imaging techniques also opened the door for patient specific modeling of airflow and pressure distribution [ 10 , 18 ]. Multi-scale in silico lung models with geometries resolved from CT imaging have proven useful in understanding previous pulmonary diseases like cystic fibrosis, chronic obstructive pulmonary disease (COPD) and asthma [ 18 , 20 , 21 ]. However, there is a need for computer modeling studies on pulmonary ventilation dynamics in COVID-19 patients, given that multi-scale in silico models offer an excellent opportunity to study the effects of region-specific acinar damage on airflow and pressure distributions in COVID-19 lungs.…”

Transport and deposition of hygroscopic particles in asthmatic subjects with and without airway narrowing

“…Later, J. Choi, LeBlanc, et al (2019) and Choi, Yoon, et al (2019) applied a CFD model to examine air flow and deposition of non-growth particles within archetypes representative of the four imaging-based clusters. Although subjects in cluster 3 (without airway constriction) and cluster 4 (with airway constriction) were characteristic of severe asthma, they exhibited different particle deposition patterns with increasing initial particle size.…”