The Virtual Nose: Assessment of Static Nasal Airway Obstruction Using Computational Simulations and 3D-Printed Models

Computational Fluid Dynamics and Its Potential Applications for the ENT Clinician

This article is an examination of computational fluid dynamics in the field of otolaryngology, specifically rhinology. The historical development and subsequent application of computational fluid dynamics continues to enhance our understanding of various sinonasal conditions and surgical planning in the field today. This article aims to provide a description of computational fluid dynamics, the methods for its application, and the clinical relevance of its results. Consideration of recent research and data in computational fluid dynamics demonstrates its use in nonhistological disease pathology exploration, accompanied by a large potential for surgical guidance applications. Additionally, this article defines in lay terms the variables analyzed in the computational fluid dynamic process, including velocity, wall shear stress, area, resistance, and heat flux.

Computational Rhinology: Unraveling Discrepancies between In Silico and In Vivo Nasal Airflow Assessments for Enhanced Clinical Decision Support

Computational rhinology is a specialized branch of biomechanics leveraging engineering techniques for mathematical modelling and simulation to complement the medical field of rhinology. Computational rhinology has already contributed significantly to advancing our understanding of the nasal function, including airflow patterns, mucosal cooling, particle deposition, and drug delivery, and is foreseen as a crucial element in, e.g., the development of virtual surgery as a clinical, patient-specific decision support tool. The current paper delves into the field of computational rhinology from a nasal airflow perspective, highlighting the use of computational fluid dynamics to enhance diagnostics and treatment of breathing disorders. This paper consists of three distinct parts-an introduction to and review of the field of computational rhinology, a review of the published literature on in vitro and in silico studies of nasal airflow, and the presentation and analysis of previously unpublished high-fidelity CFD simulation data of in silico rhinomanometry. While the two first parts of this paper summarize the current status and challenges in the application of computational tools in rhinology, the last part addresses the gross disagreement commonly observed when comparing in silico and in vivo rhinomanometry results. It is concluded that this discrepancy cannot readily be explained by CFD model deficiencies caused by poor choice of turbulence model, insufficient spatial or temporal resolution, or neglecting transient effects. Hence, alternative explanations such as nasal cavity compliance or drag effects due to nasal hair should be investigated.