Multiscale modeling of healthy and diseased human airways

The human respiratory system is a series of organs responsible for taking in oxygen and expelling carbon dioxide. The human lung is the main organ for gas exchange in the human respiratory system and starts from the trachea and ends at the alveoli. During our lifetime different factors might influence the functionality of lung such as; respiratory disease and aging. Complex morphology of the lung causes difficulty in diagnosis and visual interpretation of respiratory disease and age-related changes. In addition, pulmonary function tests are not very sensitive measures of lung disease specifically in early stages of respiratory diseases and we can not repeat the tests to confirm decisive assumption. Moreover, respiratory diseases lead to lung failure, where patients often need mechanical ventilation (MV) devices to assist them in breathing. Many important decisions have to be made once it is determined that a patient needs MV and specialists have to setup proper MV protocols to reduce ventilator induced lung injury (VILI). Hence, computational techniques provide attractive and cost-effective alternative to repeating experimental tests. The main purposes of this dissertation are first developing computational models at different scales and integrating them to investigate influence of life threatening respiratory disease and aging on breathing condition and lung failure. Second, optimizing ventilator protocols specifically for older patients to reduce VILI.