Computational fluid dynamics

Abstract

Variation in the individual airway geometry makes subject-specific models essential for the study of pulmonary air flow and drug delivery. Recent evidence also suggests that early exposure to environmental pollutants has chronic, adverse effects on lung development in children from the age of ten to 18 years [1]. Thus, the capability of predicting air flow and particle deposition in the subjectspecific breathing lungs is highly desirable for understanding the correlation between structure and function and for assessing individual differences in vulnerability to airborne pollutants. Furthermore, it has been demonstrated that a strong interaction exists between lung geometry and gas properties [2]. The interaction has major implications in determining gas delivery to and clearance from the lung periphery during ventilation imaging through X-ray computed tomography (CT) using xenon gas [3]-[5] or magnetic resonance imaging (MRI) using hyperpolarized helium gas [6]-[9]. Although there is a critical need to understand these geometry?property interactions, the current state of knowledge acquired from experiments is still far from revealing the true nature of their interplays. At the same time, three-dimensional (3-D) computational fluid dynamics (CFD) simulation of air flow for the entire lung geometry remains intractable because of constraints on imaging resolution and computational power. As a result, current 3-D CFD simulations of air flow are often restricted to a few generations of branching on a fixed mesh, and most studies are based on idealized Weibel airway models. With advances in imaging and computing technologies, anatomy coupled with functional measures (ventilation and perfusion) can now be obtained via CT imaging [10], [11]. These measures provide the detail needed to interrogate the utility of CFD in providing insights into subject-specific differences in regional lung function and the underlying mechanisms of pathologic developments © 2006 IEEE.