Airway Gas Flow

Abstract

Local characteristics of airflow and its global distribution in the lung are determined by interaction between resistance to flow through the airways and the compliance of the tissue, with tissue compliance dominating flow distribution in the healthy lung. Current understanding is that conceptualizing the airways of the lung as a system of smooth adjoined cylinders through which air traverses laminarly is insufficient for understanding flow and energy dissipation and is particularly poor for predicting physiologically realistic transport of particles by the airflow. With rapid advances in medical imaging, computer technologies, and computational techniques, computational fluid dynamics is now becoming a viable tool for providing detailed information on the mechanics of airflow in the human respiratory tract. Studies using such techniques have shown that the upper airway (specifically its development of a turbulent laryngeal jet in the trachea), airway geometry, branching and rotation angle, and the pattern of joining of successive bifurcations are important in determining airflow structures. It is now possible to compute airflow in physical domains that are anatomically accurate and subject specific, enabling comparisons among intersubjects, that among subjects of different ages, and that among different species.

In vivo measurement of gas flow in human airways with hyperpolarized gas MRI and compressed sensing

“…A flow rate of 150 mL s À1 during inhalation from a 1 L bag leaves a 6.7-s window for PCV acquisition and the flow is laminar in the trachea for the 3 He gas mixture (R e $ 550). This is closer to normal breathing conditions for the inhaled 129 Xe gas mixture (R e $ 1800), with flow in the trachea approaching the borderline of a turbulent regime (23). Comparing the velocity maps of Figure 1, the apparent difference in image quality is due to the lower velocity to noise ratio (the velocity encoding of 150 cm s À1 was mainly optimized for the flows used in the 3 He experiment).…”

A cubic B-spline-based hybrid registration of lung CT images for a dynamic airway geometric model with large deformation

“…Different from simulation with the fluid-structure interaction technique (Kumar et al 2009, Xia et al 2010, Tawhai and Lin 2010a, 2010b), the image-based CFD with moving airway geometries is only a one-way coupling analysis and, thus, requiring neither coupling with computational solid mechanics nor specifying tissue mechanical properties and tethering forces.…”

A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

“…Furthermore, cells have mechanosensing capabilities that can detect changes of the mechanical force transmitted from the organ level [3], and there is evidence of the response of human bronchial epithelial cells to mechanical force [4]. Computational fluid dynamics (CFD) has been utilized extensively to simulate respiratory flows over the past two decades [5][6]. Since particle deposition and wall shear stress are highly dependent on flow characteristics - which, in turn, are dependent on the geometrical features of the airways and regional ventilation of the lungs - it is clearly desirable to conduct subject-specific CFD modeling.…”