Combined, medical imaging data and respiratory computer simulations may facilitate novel insight into pulmonary disease phenotypes, including the relationship between its structure and function. This integration may enable improved classification and treatment of severe asthma. Severe asthma (15% of asthmatics) is particularly challenging to treat, as these patients do not respond well to inhaled therapeutics. Asthma modeling is achieved by creating patient-specific central airways and employing segmental volume defect percentages (SVDP), measured from hyperpolarized 3He MRI and CT images, as boundary conditions to the gas flow models. Predicted and measured SVDP distributions are achieved when the prescribed resistances are increased systematically. Because of differences in airway morphology and regional function, airway resistances and flow structures varied between the asthmatic subjects. Specifically, while mean SVDP was similar between the severe asthmatics (4.30±5.22 versus 3.54±5.98%), one subject exhibited abnormal flow structures, high near wall flow gradients, and enhanced conducting airway resistances (17.3E-3 versus 1.1E-3 cmH2O-s/mL) in comparison to the other severe asthmatic subject. By coupling medical imaging data with computer simulations, we provide detailed insight into pathological flow characteristics and airway mechanics in asthmatics, beyond what could be inferred independently.