A preoperative predictive study of advantages of airway changes after maxillomandibular advancement surgery using computational fluid dynamics analysis

Abstract

The purpose of this study was to develop a simulation approach for predicting maxillomandibular advancement-induced airway changes using computational fluid dynamics. Eight patients with jaw deformities who underwent maxillomandibular advancement and genioglossus advancement surgery were included in this study. Computed tomography scans and rhinomanometric readings were performed both preoperatively and postoperatively. Computational fluid dynamics models were created, and airflow simulations were performed using computational fluid dynamics software; the preferable number of computational mesh points was at least 10 million cells. The results for the right and left nares, including simulation and postoperative measurements, were qualitatively consistent, and surgery reduced airflow pressure loss. Geometry prediction simulation results were qualitatively consistent with the postoperative stereolithography data and postoperative simulation results. Simulations were performed with either the right or left naris blocked, and the predicted values were similar to those found clinically. In addition, geometry prediction simulation results were qualitatively consistent with the postoperative stereolithography data and postoperative simulation results. These findings suggest that geometry prediction simulation facilitates the preoperative prediction of the postoperative structural outcome.