Planning human upper airway surgery using computational fluid dynamics.

The study advances the idea of using computational fluid dynamics in the process of planning surgical treatment modalities for patients with obstructive airway disorders. It is hypothesized that the a priori knowledge of the functional outcome of surgical intervention on the flow and airway resistance can guide the surgeon in choosing an effective surgical strategy. Computed tomography images spanning the respiratory tract of an adult patient with a combined glottic and subglottic stenosis are used to reconstruct three-dimensional geometrical models of the airway. Computational fluid dynamics is used to obtain airway flow patterns during inspiration and expiration in these models. Numerical predictions about flow velocity, pressure distribution on the airway lumen, wall shear stress, and airway resistance are obtained so that the relevance of each individual stenotic level is quantified. Four different virtual surgeries in different combinations are assessed in order to remedy the constricted airway. The virtual surgery based airway models are evaluated by comparisons with the pre-treatment flow modeling results. The predicted numerical data revealed that the removal of the constriction at the level of the vocal folds will have the most significant effect on the airway resistance. The flow simulations offer a quantitative method of evaluating the airway resistance in patients with combined glottic and subglottic stenoses. Predictions of airway resistances and other numerical calculations from different virtual surgeries give additional inputs for the surgeon, in deciding the most appropriate surgery on a case-by-case basis.