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Background: Chronic rhinosinusitis (CRS) is a prevalent and disruptivedisease. Medical management including nasal steroid sprays is the primarytreatment modality. Computational fluid dynamics (CFD) has been used tocharacterize sinonasal airflow and intranasal drug delivery; however, variationin simulation methods indicates a need for large scale CFD model validation.  Methods: Anatomic reconstructions of pre and post-operative CT scans of 3functional endoscopic sinus surgery patients were created in Mimics(TM). Fluidanalysis and drug particle deposition modeling were conducted using CFD methodswith Fluent(TM) in 18 cases. Models were 3D printed and in vitro studies wereperformed using Tc99-labeled Nasacort(TM). Gamma scintigraphy signals andCFD-modeled spray mass were post-processed in a superimposed grid and compared.Statistical analysis using overlap coefficients (OCs) evaluated similaritiesbetween computational and experimental distributions and Kendall's tau rankcorrelation coefficient was employed to test independence.  Results: OCs revealed strong agreement in percent deposition and gridprofiles between CFD models and experimental results (mean [range] forsagittal, axial, and coronal grids were 0.69 [0.57], 0.61 [0.49], and 0.78[0.44], respectively). Kendall's tau values showed strong agreement (average0.73) between distributions, which were statistically significant (p < 0.05)apart from a single coronal grid in one model and two sagittal grids ofanother.  Conclusions: CFD modeling demonstrates statistical agreement with in vitroexperimental results. This validation study is one of the largest of its kindand supports the applicability of CFD in accurately modeling nasal spray drugdelivery and using computational methods to investigate means of improvingclinical drug delivery.

Validation of Sinus Drug Delivery Computational Fluid Dynamics (CFD) Modeling with In Vitro Gamma Scintigraphy