Virtual septoplasty: a method to predict surgical outcomes for patients with nasal airway obstruction.

PURPOSE

A deviated nasal septum is the most common etiology for nasal airway obstruction (NAO), and septoplasty is the most common surgical procedure performed by ear-nose-throat surgeons in adults. However, quantitative criteria are rarely adopted to select patients for surgery, which may explain why up to 50% of patients report persistent or recurrent symptoms of nasal obstruction postoperatively. This study reports a systematic virtual surgery method to identify patients who may benefit from septoplasty.

METHODS

One patient with symptoms of NAO due to a septal deviation was selected to illustrate the virtual surgery concept. Virtual septoplasty was implemented in three steps: (1) determining if septal geometry is abnormal preoperatively, (2) virtually correcting the deviation while preserving the anatomical shape of the septum, and (3) estimating the post-surgical improvement in airflow using computational fluid dynamics. Anatomical and functional changes predicted by the virtual surgery method were compared to a standard septoplasty performed independently from the computational analysis.

RESULTS

A benchmark healthy nasal septum geometry was obtained by averaging the septum dimensions of 47 healthy individuals. A comparison of the nasal septum geometry in the NAO patient with the benchmark geometry identified the precise locations where septal deviation and thickness exceeded the healthy range. Good agreement was found between the virtual surgery predictions and the actual surgical outcomes for both airspace minimal cross-sectional area (0.05 cm pre-surgery, 0.54 cm virtual surgery, 0.50 cm actual surgery) and nasal resistance (0.91 Pa.s/ml pre-surgery, 0.08 Pa.s/ml virtual surgery, 0.08 Pa.s/ml actual surgery).

CONCLUSIONS

Previous virtual surgery methods for NAO were based on manual edits and subjective criteria. The virtual septoplasty method proposed in this study is objective and has the potential to be fully automated. Future implementation of this method in virtual surgery planning software has the potential to improve septoplasty outcomes.