Computational modelling of nasal respiratory flow

An adjoint-based approach for the surgical correction of nasal septal deviations

Deviations of the septal wall are widespread anatomic anomalies of the human nose; they vary significantly in shape and location, and often cause the obstruction of the nasal airways. When severe, septal deviations need to be surgically corrected by ear-nose-throat (ENT) specialists. Septoplasty, however, has a low success rate, owing to the lack of suitable standardized clinical tools for assessing type and severity of obstructions, and for surgery planning. Moreover, the restoration of a perfectly straight septal wall is often impossible and possibly unnecessary. This paper introduces a procedure, based on advanced patient-specific Computational Fluid Dynamics (CFD) simulations, to support ENT surgeons in septoplasty planning. The method hinges upon the theory of adjoint-based optimization, and minimizes a cost function that indirectly accounts for viscous losses. A sensitivity map is computed on the mucosal wall to provide the surgeon with a simple quantification of how much tissue removal at each location would contribute to easing the obstruction. The optimization procedure is applied to three representative nasal anatomies, reconstructed from CT scans of patients affected by complex septal deviations. The computed sensitivity consistently identifies all the anomalies correctly. Virtual surgery, i.e. morphing of the anatomies according to the computed sensitivity, confirms that the characteristics of the nasal airflow improve significantly after small anatomy changes derived from adjoint-based optimization.

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.

Validation and Sensitivity analysis for a nasal spray deposition computational model

Validating numerical models against experimental models of nasal spray deposition is challenging since many aspects must be considered. That being said, it is a critical step in the product development process of nasal spray devices. This work presents the validation process of a nasal deposition model, which demonstrates a high degree of consistency of the numerical model with experimental data when the nasal cavity is segmented into two regions but not into three. Furthermore, by modelling the flow as stationary, the computational cost is drastically reduced while maintaining quality of particle deposition results. Thanks to this reduction, a sensitivity analysis of the numerical model could be performed, consisting of 96 simulations. The objective was to quantify the impact of four inputs: the spray half cone angle, mean spray exit velocity, breakup length from the nozzle exit and the diameter of the nozzle spray device, on the three quantities of interest: the percentage of the accumulated number of particles deposited on the anterior, middle and posterior sections of the nasal cavity. The results of the sensitivity analysis demonstrated that the deposition on anterior and middle sections are sensitive to injection angle and breakup length, and the deposition on posterior section is only, but highly, sensitive to the injection velocity.

Research Active Posterior Rhinomanometry Tomography Method for Nasal Breathing Determining Violations

This study analyzes the existing methods for studying nasal breathing. The aspects of verifying the results of rhinomanometric diagnostics according to the data of spiral computed tomography are considered, and the methodological features of dynamic posterior active rhinomanometry and the main indicators of respiration are also analyzed. The possibilities of testing respiratory olfactory disorders are considered, the analysis of errors in rhinomanometric measurements is carried out. In the conclusions, practical recommendations are given that have been developed for the design and operation of tools for functional diagnostics of nasal breathing disorders. It is advisable, according to the data of dynamic rhinomanometry, to assess the functioning of the nasal valve by the shape of the air flow rate signals during forced breathing and the structures of the soft palate by the residual nasopharyngeal pressure drop. It is imperative to take into account not only the maximum coefficient of aerodynamic nose drag, but also the values of the pressure drop and air flow rate in the area of transition to the turbulent quadratic flow regime. From the point of view of the physiology of the nasal response, it is necessary to look at the dynamic change to the current mode, given the hour of the forced response, so that it will ensure the maximum possible acidity in the legend. When planning functional rhinosurgical operations, it is necessary to apply the calculation method using computed tomography, which makes it possible to predict the functional result of surgery.

Use of computational fluid dynamics (CFD) to model observed nasal nitric oxide levels in human subjects

BACKGROUND

Upper airway nitric oxide (NO) is physiologically important in airway regulation and defense, and nasal NO (nNO) levels typically exceed those in exhaled breath (fractional exhaled NO [FeNO]). Elevated concentrations of NO sampled from the nose, in turn, reflect even higher concentrations in the paranasal sinuses, suggesting a "reservoir" role for the latter. However, the dynamics of NO flux within the sinonasal compartment are poorly understood.

METHODS

Data from 10 human subjects who had previously undergone both real-time nNO sampling and computed tomography (CT) scanning of the sinuses were analyzed using computational fluid dynamics (CFD) methods. Modeled and observed nNO values during the initial 2-s transient ("spike") during nasal exhalation were then compared.

RESULTS

Examining the initial 2-s transient spike for each subject (as well as the pooled group), there was a statistically significant correlation between modeled and observed nNO levels, with r values ranging from 0.43 to 0.89 (p values ranging from <0.05 to <0.0001). Model performance varied between subjects, with weaker correlations evident in those with high background (FeNO) levels. In addition, the CFD simulation suggests that ethmoid sinuses (>60%) and diffusion process (>54%) contributed most to total nasal NO emissions.

CONCLUSION

Analysis of this dataset confirms that CFD is a valuable modeling tool for nNO dynamics, and highlights the importance of the ethmoid sinuses, as well as the role of diffusion as an initiating step in sinonasal NO flux. Future model iterations may apply more generally if baseline FeNO is taken into account.

In-silico investigation of airflow and micro-particle deposition in human nasal airway pre- and post-virtual transnasal sphenoidotomy surgery

Sphenoid sinus, located posterior to the nasal cavity, is difficult to reach for a surgery. Several operation procedures are available for sphenoidotomy, including endoscopic surgeries. Although the endoscopic sinus surgery is minimally invasive with low post-operative side effects, further optimization is required. Transnasal sphenoidotomy is a low invasive alternative to transethmoidal sphenoidotomy, but it still needs to be studied to understand its effects on the airflow pattern and the particle deposition. In this work, we simulated airflow and the micro-particle deposition in the nasal airway of a middle-aged man to investigate the change in particle deposition in the sphenoid sinus after virtual transnasal sphenoidotomy surgery. The results demonstrated that after transnasal sphenoidotomy, particle deposition in the targeted sphenoid sinus was an order of magnitude lower than that observed after virtual transethmoidal sphenoidotomy surgery. In addition, the diameter of the particles for the peak deposition fraction in the targeted sinus was shifted to smaller diameters after the transnasal sphenoidotomy surgery compared with that in the post-transethmoidal condition. These results suggest that the endoscopic transnasal sphenoidotomy can be a better procedure for sphenoid surgeries as it decreases the chance of bacterial contaminations and consequently lowers the surgical side effects and recovery time.

Large eddy simulation of cough jet dynamics, droplet transport, and inhalability over a ten minute exposure

High fidelity simulations of expiratory events such as coughing provide the opportunity to predict the fate of the droplets from the turbulent jet cloud produced from a cough. It is well established that droplets carrying infectious pathogens with diameters of 1 - 5   μ m remain suspended in the air for several hours and transported by the air currents over considerable distances (e.g., in meters). This study used a highly resolved mesh to capture the multiphase turbulent buoyant cloud with suspended droplets produced by a cough. The cough droplets' dispersion was subjected to thermal gradients and evaporation and allowed to disperse between two humans standing 2 m apart. A nasal cavity anatomy was included inside the second human to determine the inhaled droplets. Three diameter ranges characterized the droplet cloud, < 5   μ m , which made up 93% of all droplets by number; 5 to 100 μm comprised 3%, and > 100   μ m comprising 4%. The results demonstrated the temporal evolution of the cough event, where a jet is first formed, followed by a thermally driven puff cloud with the latter primarily composed of droplets under 5 μm diameter, moving with a vortex string structure. After the initial cough, the data were interpolated onto a more coarse mesh to allow the simulation to cover ten minutes, equivalent to 150 breathing cycles. We observe that the critical diameter size susceptible to inhalation was 0.5   μ m , although most inhaled droplets after 10 min by the second human were approximately 0.8   μ m . These observations offer insight into the risk of airborne transmission and numerical metrics for modeling and risk assessment.

N95 respirator mask breathing leads to excessive carbon dioxide inhalation and reduced heat transfer in a human nasal cavity

Face masks and respirators are used to filter inhaled air, which may contain airborne droplets and high particulate matter (PM) concentrations. The respirators act as a barrier to the inhaled and exhaled air, which may change the nasal airflow characteristics and air-conditioning function of the nose. This study aims to investigate the nasal airflow dynamics during respiration with and without an N95 respirator driven by airflow through the nasal cavity to assess the effect of the respirator on breathing conditions during respiration. To achieve the objective of this study, transient computational fluid dynamics simulations have been utilized. The nasal geometry was reconstructed from high-resolution Computed Tomography scans of a healthy 25-year-old female subject. The species transport method was used to analyze the airflow, temperature, carbon dioxide (CO₂), moisture content (H₂O), and temperature distribution within the nasal cavity with and without an N95 respirator during eight consecutive respiration cycles with a tidal volume of 500 ml. The results demonstrated that a respirator caused excessive CO₂ inhalation by approximately 7 × greater per breath compared with normal breathing. Furthermore, heat and mass transfer in the nasal cavity was reduced, which influences the perception of nasal patency. It is suggested that wearers of high-efficiency masks that have minimal porosity and low air exchange for CO₂ regulation should consider the amount of time they wear the mask.