Modeling pressure relationships of inspired air into the human lung bifurcations through simulations

Abstract

ABSTRACTApplied pressure on human lung wall has great importance on setting up protective ventilatory strategies, therefore, estimating pressure relationships in terms of specific parameters would provide invaluable information specifically during mechanical ventilation (MV). A three-dimensional model from a healthy human lung MRI is analyzed by computational fluid dynamic (CFD), and results for pressure are curve fitted to estimate relationships that associate pressure to breathing time, cross section and generation numbers of intended locations. Among all possible functions, it is observed that exponential and polynomial pressure functions present most accurate results for normal breathing (NB) and MV, respectively. For validation, pressure-location curves from CFD and results from this study are compared and good correlations are found. Also, estimated pressure values are used to calculate pressure drop and airway resistance to the induced air into the lung bifurcations. It is concluded that maximum pressure drop appeared in generation number 2 and medium sized airways show higher resistance to air flow and that resistance decreased as cross sectional area increased through the model. Results from this study are in good agreement with previous studies and provide potentials for further studies on influence of air pressure on human lung tissue and reducing lung injuries during MV.