# Forward Computational Modeling of Respiratory Airflow
###### Abstract  
The simulation of gas flow in the bronchial tree using computational fluid dynamics (CFD) has become a useful tool for the analysis of gas flow mechanics, structural deformation, ventilation, and particle deposition for drug delivery during spontaneous and assisted breathing. CFD allows for new hypotheses to be tested in silico, and detailed results generated without performing expensive experimental procedures that could be potentially harmful to patients. Such computational techniques are also useful for analyzing structure-function relationships in healthy and diseased lungs, assessing regional ventilation at various time points over the course of clinical treatment, or elucidating the changes in airflow patterns over the life span. CFD has also allowed for the development and use of image-based (i.e., patient-specific) models of three-dimensional (3D) airway trees with realistic boundary conditions to achieve more meaningful and personalized data that may be useful for planning effective treatment protocols. This focused review will present a summary of the techniques used in generating realistic 3D airway tree models, the limitations of such models, and the methodologies used for CFD airflow simulation. We will discuss mathematical and image-based geometric models, as well as the various boundary conditions that may be imposed on these geometric models. The results from simulations utilizing mathematical and image-based geometric models of the airway tree will also be discussed in terms of similarities to actual gas flow in the human lung. a 2024 14 11591 1199 11.111.111.11.  
such as imaging resolution, the imposition of physiologic boundary conditions, turbulence in the upper airways, and the limitations of the existing computational resources [5]. In 1963, [PERSON] conceptualized the human airway tree with 23 dichotomously branching airway generations comprised of conducting and respiratory zones [6]. The conducting zones (trachea to terminal bronchioles) comprised the first 16 generations, while the respiratory zone comprises 7 generations. Both zones make up more than 65,536 distinct airway segments in the human lung, which become progressively smaller in dimension further from the trachea. Advection and diffusion serve as the two primary modes of gas transport in the lungs, and thus are incorporated into CFD simulations of respiratory air flow. The dominant mode of transport in the conducting zone is advection (i.e., bulk flow), for which there is minimal-to-no gas exchange. However in the respiratory zone, the dominant mode of transport is diffusion, via the movement of oxygen (O\({}_{2}\)) and carbon dioxide (CO\({}_{2}\)) down their concentration gradients across the blood-gas barrier [1]. In the adult human, the volume of the conducting zone averages about 150 mL, while the respiratory zone has a volume of about 2.5 to 3 L at functional residual capacity [7]. During spontaneous breathing, the volume change of the respiratory zone is significant, while that of the conducting zone is minimal, whereas in assisted breathing, both volumes change considerably, especially when high positive pressures are utilized [8]. The goal of CFD for simulation of respiratory phenomena is to mimic the behavior of gas flow (in the conducting airway and respiratory zones) and/or pulmonary blood flow during inspiratory and expiratory cycles, whether such breathing is spontaneous or assisted. During spontaneous breathing, inspiration is initiated by the contraction of the diaphragm and external intercostal muscles, resulting in the expansion of the thoracic cavity. This expansion results in a decrease in alveolar pressure, and an increase in the pressure gradient between the distal lung and atmosphere, accordingly, air flows into the lungs via advection. Under normal breathing conditions, expiration results from the passive elastic recoil of the lung tissues and chest wall.