Variation in individual airway geometry makes subject-specific models essential to the study of pulmonary airflow and drug delivery. Recent evidence also suggests that early exposure to environmental pollutants has chronic, adverse effects on lung development in the children from the age of 10 to 18 years (Gauderman et al. 2004). Thus, the capability of predicting airflow and particle deposition in the subject specific breathing lungs is highly desirable to understand this correlation and prevent future lung deficits. Furthermore, the physiologic imaging group at the University of Iowa has recently demonstrated a strong interaction between lung geometry and gas density (Chon et al. 2004; Lin and Hoffman, 2005; Lin et al. 2005). The interaction has major implications in determining gas delivery to and clearance from the lung periphery during ventilation imaging via x-ray CT using xenon gas (Xe) or MRI using hyperpolarized helium gas (He). While there is a critical need to understand these density-geometry 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 (3D) computational fluid dynamics (CFD) simulation of airflow for the entire lung geometry remains intractable because of constraints on imaging resolution and computational power. As a result, current 3D CFD simulations of airflow are restricted to 4-5 generations of branching on a fixed mesh and most of them are based on the idealized Weibel lung models. We propose to address the complexity of the human lung - which is dynamic in time and multiscale in nature from trachea to bronchiole to alveolar sac – by developing a comprehensive model for pulmonary air flow that: (a) utilizes subject-specific airway geometries; (b) spans spatial scales from the largest bronchial airways to alveolar sac; and (c) employs a novel CT-data-driven, multiscale approach to provide accurate predictions of ventilation and gas transport in the entire airway tree. This project will establish a novel collaboration between Drs Lin, Hoffman, McLennan, and Tawhai, bringing together complementary expertise in modeling and validating fluid transport in the respiratory system at different scales. The team provides considerable strength in CFD techniques, integrative geometric modeling of pulmonary structures, experimentation and imaging over a range of scales in the pulmonary system, and pulmonary medicine. The ultimate goal of the project is to build a subject-specific digital human lung model for predicting regional ventilation and gas transport in the healthy and disease-state human lungs in a CT and MRI dynamic-data-driven and multiscale setting. The specific aims of the proposal are to:

1. Establish efficient techniques for generating subject-specific computational meshes for CFD analysis, including mesh construction of conducting airways from CT images and synthesized airways beyond the limitation of CT resolution using a volume-filling algorithm;
2. Integrate the custom developed 3D CFD model to the one-dimensional (1D) gas transport model by developing an efficient algorithm to facilitate 3D to 1D coupling (large to small airways) or 1D to 3D coupling (bronchioles to alveolar ducts) for multiscale simulation;
3. Develop and experimentally validate a new predictive model of ventilation distribution by linking 3D CFD models to dynamic imaging of ventilation, via 1D flow models;
4. Make available the coupling algorithms and databases to the research and clinical communities.

This project will also fit within the framework of two of the most significant ongoing research efforts in pulmonary science: the Lung Atlas (Hoffman et al. 2004b) and the International Union of Physiological Sciences (IUPS) Physiome Project (Hunter et al. 2002, Crampin et al. 2004). The Lung Atlas Project led by Dr. Hoffman aims to document airway geometry over four decades of age in healthy and diseased adult humans. The Physiome Project is a worldwide effort to provide a computational framework for understanding human physiology and to develop integrative models at all levels of biological organization, ranging from genes to the whole organism. Dr. Tawhai is the lead scientist in developing Lung Physiome (Tawhai and Ben-Tal, 2004). Dr. Lin will apply CFD techniques with advanced capabilities to achieve realistic representation of pulmonary flow in the deforming airways. The simulation results will be validated by the laboratory experiments conducted by Dr. Hoffman. Simulation results will be interpreted and related to clinical application by Dr. McLennan, who is a Pulmonary, Critical Care and Occupational Medicine faculty and doctor at the University of Iowa General Hospital and the national Chair of The Lung Image Database Consortium (LIDC).