Computational modeling of airflow in a human nasal cavity

Abstract

Nasal obstructions restrict the flow of air through the nasal passage, and a failure to accurately identify these obstructions can lead to long-term discomfort in the patients. There is a need to develop new methods to diagnose nasal obstructions because the current subjective and objective methods do not always strongly correlate, resulting in the medical and surgical procedures being sub-optimal and thus reducing patient comfort. The advancement in computing and imaging technology enables the application of novel methods like Computational Fluid Dynamics (CFD) and 3D imaging to diagnose nasal obstructions. This project aims to understand the effect of tidal breathing in the nasal cavity and investigate the possibility of using CFD as a tool in diagnosing nasal obstructions. In-vitro experiments were performed on the 3D-printed model of the nasal cavity to evaluate the nasal resistance and pressure distribution inside the nasal passage. The approach of modeling the nasal cavity flow by a quasi-steady assumption was analyzed by comparing the steady-state solution with results from tidal breathing simulation. The in-vitro pressure distribution and nasal resistance were similar to the results obtained from tidal breathing CFD simulations. It validates the CFD methodology established in this project and indicates that CFD as a tool can be used as an objective method to diagnose nasal obstructions. Although the nasal resistance is accurately calculated from the steady-state solution, the flow characteristics during the exhalation differ significantly compared to tidal breathing simulations. It highlights that the quasi-steady assumption is inappropriate to study the detailed flow structures inside the nasal cavity. The conclusions derived from this project suggest that the post-processing capabilities of CFD can aid doctors in acquiring valuable insights regarding nasal airflow. In the future, CFD simulations can help understand the effect of various surgical procedures by performing virtual surgery on the obstructed cavity of the patient.