Modeling the effect of tumor compression on airflow dynamics in trachea using contact simulation and CFD analysis

Abstract

Malignant central airway obstruction can cause severe breathing difficulty in a patient that requires surgical intervention or stent implantation to alleviate it. A predictive model to identify the onset of this event as the central airway is progressively compressed by tumor growth will be helpful for clinicians to plan for medical intervention. We present such a model to simulate tumor compression of the trachea and the resulting change in airflow dynamics to estimate the level of stenosis that will cause severe breathing difficulties. A patient-specific model of trachea was generated from acquired Computed Tomography (CT) scans for the simulations. The compression of this trachea due to tumor growth is modeled using nonlinear contact simulations of ellipsoidal tumors with the trachea. Computational fluid dynamics (CFD) is employed to simulate the turbulent airflow during inhalation in the stenosed trachea. From the CFD simulated flow fields, the power loss due to airflow through the domain is calculated. The results show that when the obstruction in the trachea reaches 50%, compared to the undeformed model, the power loss can rise to more than 66%. A measure of breathing difficulty can be derived by correlating it with the power loss. Thus, medical intervention can be predicted based on the degree of stenosis if the induced power loss exceeds a threshold that causes severe breathing discomfort.