Assessing nasal airway resistance and symmetry: An approach to global perspective through computational fluid dynamics.

This study aimed to explore the variability in nasal airflow patterns among different sexes and populations using computational fluid dynamics (CFD). We focused on evaluating the universality and applicability of dimensionless parameters R (bilateral nasal resistance) and ϕ (nasal flow asymmetry), initially established in a Caucasian Spanish cohort, across a broader spectrum of human populations to assess normal breathing function in healthy airways. In this retrospective study, CT scans from Cambodia (20 males, 20 females), Russia (20 males, 18 females), and Spain (19 males, 19 females) were analyzed. A standardized CFD workflow was implemented to calculate R-ϕ parameters from these scans. Statistical analyses were conducted to assess and compare these parameters across different sexes and populations, emphasizing their distribution and variances. Our results indicated no significant sex-based differences in the R parameter across the populations. However, moderate sexual dimorphism in the ϕ parameter was observed in the Cambodian group. Notably, no geographical differences were found in either R or ϕ parameters, suggesting consistent nasal airflow characteristics across the diverse human groups studied. The study also emphasized the importance of using dimensionless variables to effectively analyze the relationships between form and function in nasal airflow. The observed consistency of R-ϕ parameters across various populations highlights their potential as reliable indicators in both medical practice and further CFD research, particularly in diverse human populations. Our findings suggest the potential applicability of dimensionless CFD parameters in analyzing nasal airflow, highlighting their utility across diverse demographic and geographic contexts. This research advances our understanding of nasal airflow dynamics and underscores the need for additional studies to validate these parameters in broader population cohorts. The approach of employing dimensionless parameters paves the way for future research that eliminates confounding size effects, enabling more accurate comparisons across different populations and sexes. The implications of this study are significant for the advancement of personalized medicine and the development of diagnostic tools that accommodate individual variations in nasal airflow.