Toward Personalized Nasal Surgery Using Computational Fluid Dynamics

Abstract

To evaluate whether virtual surgery performed on 3-dimensional (3D) nasal airway models can predict postsurgical, biophysical parameters obtained by computational fluid dynamics (CFD). Presurgery and postsurgery computed tomographic scans of a patient undergoing septoplasty and right inferior turbinate reduction (ITR) were used to generate 3D models of the nasal airway. Prior to obtaining the postsurgery scan, the presurgery model was digitally altered to generate 3 virtual surgery models: (1) right ITR only, (2) septoplasty only, and (3) septoplasty with right ITR. The results of the virtual surgery CFD analyses were compared with postsurgical CFD outcome measures including nasal resistance, unilateral airflow allocation, and regional airflow distribution. Postsurgery CFD analysis and all virtual surgery models predicted similar reductions in overall nasal resistance, as well as more balanced airflow distribution between sides, primarily in the middle region, when compared with the presurgery state. In contrast, virtual ITR alone produced little change in either nasal resistance or regional airflow allocation. We present an innovative approach for assessing functional outcomes of nasal surgery using CFD techniques. This preliminary study suggests that virtual nasal surgery has the potential to be a predictive tool that will enable surgeons to perform personalized nasal surgery using computer simulation techniques. Further investigation involving correlation of patient-reported measures with CFD outcome measures in multiple individuals is under way.