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Interaction between a deformable elastic body and an internal or external fluid flow alters the flow pattern. This dissertation describes the effects of elasticity on flow in physiological scenarios. The first part of the thesis describes the influence of soft tissue compliance on flow in the upper airways of pediatric Down syndrome (DS) patients and adolescent Polycystic-Ovarian syndrome patients with obstructive sleep apnea (OSA). Computational fluid dynamics (CFD) of airflow is performed in pre and post-operative geometries of the DS pediatric airway to evaluate effectiveness of a surgery and address the importance of including the subject-specific tissue compliance. A tube law approach and a novel image analysis method are then presented to evaluate the circumferential variation in airway compliance for DS patients. An iterative finite element method is then described to non-invasively estimate patient-specific mechanical properties of the upper airway in these patients. The estimated mechanical properties for a single patient are applied to simulate airway obstruction during inspiratory airflow, before and after surgery. Sensitivity to different flow variables is analyzed and an operating map is created to establish the relationship between tissue elasticity and volumetric airflow. The necessity for performing fluid-structure interaction (FSI) in PCOS subjects with OSA is illustrated through a series of strain maps of upper airway tissue. An inverse methodology based on FSI simulations is described to characterize the soft-palate stiffness in these subjects. Differences in pre and post-operative airflow patterns and tissue motion in a PCOS patient are described using computational modeling and compared with the same for a healthy individual.The second part of the study describes computational FSI modeling of aortic blood flow in Turner syndrome (TS). A continuous measurement tool is developed to automatically compute the longitudinal variation in maximum aortic diameter. Patient-specific, three-dimensional geometric analysis of the aorta is then performed to evaluate localized changes in aorta morphology. A quasi-steady FSI modeling approach is described to estimate hemodynamic and biomechanical functional indices of cardiovascular disease in TS. Patterns of swirling flow, wall shear stress, aorta wall pressure, vessel wall displacement and mechanical stresses are compared for healthy and diseased aortas. The proposed computational technique is then applied to determine longitudinal changes in functional variables for multiple patients. The influence of including the aortic sinus is then addressed to obtain improved predictions of the spatial locations that are most vulnerable to progressive dilatation and vessel wall tear. FSI simulations of aortic blood flow with subject-specific flow boundary conditions and vessel wall stiffness derived from imaging is performed for individualized risk stratification in TS. A FSI methodology employing improved outflow conditions is then presented for TS patients and subjects diagnosed with aortic dissection. A longitudinal comparison of functional measures is presented for 2 TS subjects including the aortic root geometry, using a decoupled FSI methodology. Temporal variations in flow-induced shear and mechanical stress are then assessed using transient blood flow simulations. Finally, the influence of vessel wall thickness and blood rheology on functional indices is estimated in different aortic anomalies observed in TS. |
