In silico approaches to respiratory nasal flows: A review

Is the mouse nose a miniature version of a rat nose? A computational comparative study

BACKGROUND AND OBJECTIVE

Although the mouse is a widely used animal model in biomedical research, there are few published studies on its nasal aerodynamics, potentially due to its small size. It is not appropriate to assume that mice and rats' nasal structure and airflow characteristics are the same because the ratio of nasal surface area to nasal volume and body weight is much higher in a mouse than in a rat. The aim of this work is to use anatomically accurate image-based computational fluid dynamic modeling to quantitatively reveal the characteristics of mouse nasal airflow and mass transport that haven't been detailed before and find key differences to that of rat nose, which will deepen our understanding of the mouse's physiological functions.

METHODS

We created an anatomically accurate 3D computational nasal model of a B6 mouse using postmortem high-resolution micro-CT scans and simulated the airflow distribution and odor transport patterns under restful breathing conditions. The deposition pattern of airborne particles was also simulated and validated against experimental data. In addition, we calculated the gas chromatograph efficiency of odor transport in the mouse employing the theoretical plate concept and compared it with previous studies involving cat and rat models.

RESULTS

Similar to the published rat model, respiratory and olfactory flow regimes are clearly separated in the mouse nasal cavity. A high-speed dorsal medial (DM) stream was observed, which enhances the delivery speed and efficiency of odor to the ethmoid (olfactory) recess (ER). The DM stream split into axial and secondary paths in the ER. However, the secondary flow in the mouse is less extensive than in the rat. The gas chromatograph efficiency calculations suggest that the rat may possess a moderately higher odorant transport efficiency than that of the mouse due to its more complex ethmoid recess structure and extensive secondary flow. However, the mouse's nasal structure seems to adapt better to varying airflow velocity.

CONCLUSIONS

Due to the inherent structural disparities, the rat and mouse models exhibit moderate differences in airflow and mass transport patterns, potentially impacting their olfaction and other behavioral habits.

Influencing factors of particle deposition in the human nasal cavity

Objective

To review the existing literature on the application of computational fluid dynamics methods to study nasal particle deposition and to summarize and analyze the factors affecting nasal particle deposition in order to provide theoretical references for the development of future transnasal drug delivery devices and the prevention of respiratory-related diseases.

Data Source

PubMed and CNKI databases.

Methods

A search of all current literature (up to and including February 2023) was conducted. Search terms related to the topic of factors influencing nasal particle deposition were identified, and queries were conducted to identify relevant articles.

Results

Both the properties of the particles themselves and the environmental conditions external to the particles can affect particle deposition in the nasal cavity, with particle deposition showing a positive correlation with particle size, particle density, and airflow velocity, with increasing subject age leading to a decrease in deposition, and with the relationship between airflow temperature and humidity still requiring more research to further explore.

Conclusions

With the popularity of computational fluid dynamics, more and more scholars have applied computational fluid dynamics technology to explore the influence of different parameters on particle deposition. By summarizing and analyzing the influence law of various factors on deposition, it can provide a theoretical basis for the future development and application of transnasal drug delivery devices and the prevention of respiratory-related diseases, which makes a significant contribution to the optimization of clinical disease prevention and treatment.

Level of Evidence

NA.

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.

Nanomedicines for intranasal delivery: understanding the nano-bio interactions at the nasal mucus-mucosal barrier

INTRODUCTION

Intranasal administration is an effective drug delivery routes in modern pharmaceutics. However, unlike other in vivo biological barriers, the nasal mucosal barrier is characterized by high turnover and selective permeability, hindering the diffusion of both particulate drug delivery systems and drug molecules. The in vivo fate of administrated nanomedicines is often significantly affected by nano-biointeractions.

AREAS COVERED

The biological barriers that nanomedicines encounter when administered intranasally are introduced, with a discussion on the factors influencing the interaction between nanomedicines and the mucus layer/mucosal barriers. General design strategies for nanomedicines administered via the nasal route are further proposed. Furthermore, the most common methods to investigate the characteristics and the interactions of nanomedicines when in presence of the mucus layer/mucosal barrier are briefly summarized.

EXPERT OPINION

Detailed investigation of nanomedicine-mucus/mucosal interactions and exploration of their mechanisms provide solutions for designing better intranasal nanomedicines. Designing and applying nanomedicines with mucus interaction properties or non-mucosal interactions should be customized according to the therapeutic need, considering the target of the drug, i.e. brain, lung or nose. Then how to improve the precise targeting efficiency of nanomedicines becomes a difficult task for further research.

Scale resolving simulations of the effect of glottis motion and the laryngeal jet on flow dynamics during respiration

BACKGROUND AND OBJECTIVE

The movement of the respiratory walls has a significant impact on airflow through the respiratory tract. The majority of computational fluid dynamics (CFD) studies assume a static geometry which may not provide a realistic flow field. Furthermore, many studies use Reynolds Averaged Navier-Stokes (RANS) turbulence models that do not resolve turbulence structure. Combining the application of advanced scale-resolving turbulence models with moving respiratory walls using CFD will provide detailed insights into respiratory flow structures.

METHODS

This study simulated a complete breathing cycle involving inhalation and exhalation in a nasal cavity to trachea geometry that incorporated moving glottis walls. A second breathing cycle was simulated with static glottis walls for comparison. A recently developed hybrid RANS-LES turbulence model, the Stress-Blended Eddy Simulation (SBES), was incorporated to resolve turbulent flow structures in fine detail for both transient simulations. Transient results were compared with steady-state RANS simulations for the same respiratory geometry.

RESULTS

Glottis motion caused substantial effects on flow structure through the complete breathing cycle. Significant flow structure and velocity variations were observed due to glottal motion, primarily in the larynx and trachea. Resolved turbulence structures using SBES showed an intense mixing section in the glottis region during inhalation and in the nasopharynx during expiration, which was not present in the RANS simulations.

CONCLUSION

Transient simulations of a realistic breathing cycle uncovered flow structures absent in simulations with a constant flow rate. Furthermore, the incorporation of glottis motion impacted airflow characteristics that suggest rigid respiratory walls do not accurately describe respiratory flow. Future research in respiratory airflow should be conducted using transient scale-resolving models in conjunction with moving respiratory walls to capture flow structures in detail.

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.

On the comparison between pre- and post-surgery nasal anatomies via computational fluid dynamics

Nasal breathing difficulties (NBD) are widespread and difficult to diagnose; the failure rate of their surgical corrections is high. Computational fluid dynamics (CFD) enables diagnosis of NBD and surgery planning, by comparing a pre-operative (pre-op) situation with the outcome of virtual surgery (post-op). An equivalent comparison is involved when considering distinct anatomies in the search for the functionally normal nose. Currently, this comparison is carried out in more than one way, under the implicit assumption that results are unchanged, which reflects our limited understanding of the driver of the respiratory function. The study describes how to set up a meaningful comparison. A pre-op anatomy, derived via segmentation from a CT scan, is compared with a post-op anatomy obtained via virtual surgery. State-of-the-art numerical simulations for a steady inspiration carry out the comparison under three types of global constraints, derived from the field of turbulent flow control: a constant pressure drop (CPG) between external ambient and throat, a constant flow rate (CFR) through the airways and a constant power input (CPI) from the lungs can be enforced. A significant difference in the quantities of interest is observed depending on the type of comparison. Global quantities (flow rate, pressure drop and nasal resistance) as well as local ones are affected. The type of flow forcing affects the outcome of the comparison between pre-op and post-op anatomies. Among the three available options, we argue that CPG is the least adequate. Arguments favouring either CFR or CPI are presented.

Fibres in the nasal cavity: A pilot study of the recovery, background, and transfer in smothering scenarios

In cases where the suspected cause of death is smothering, fibre traces recovered from the nasal cavity are hypothesised to refute or support this proposition. In order to carry out such evaluations, an efficient recovery method must first be established. This pilot study tested five different recovery methods on 3D printed models of nasal cavities. Among which, the use of the transparent AccuTrans® polyvinyl Siloxane casts demonstrated the best recovery efficiency with a median of 90% of deposited fibres recovered. The efficacy of this method was then verified on cadavers. Apart from a reliable recovery method, an understanding of the background population of fibres in nasal cavities, as well as the mechanisms of the transfer from the purported smothering textile to the nasal cavity is essential to evaluate the findings in these cases of suspected smothering. Samplings of the nasal cavities of 20 cadavers were thus carried out to gather data on the background population of fibres. Results showed that nasal cavities are not void of fibres, but the quantities are expected to be low, with a mean of 3.8 fibres per cavity recovered. Information on generic fibre class, colour, and length of these background fibres were also obtained with the use of low and high-power microscopy. The frequencies found in this population of fibres closely align with data from other population studies where black cotton was the most common. Finally, transfer experiments using the 3D printed models fitted with a respiratory pump to simulate breathing were carried out, along with testing on live volunteers in-vivo. The results demonstrated a verifiable transfer of fibres into the nasal cavity in smothering scenarios. Textiles of various shedding capacities were used in these tests and the findings suggest an influence of this variable on the quantities of fibres transferred.

Automatic three-dimensional nasal and pharyngeal airway subregions identification via Vision Transformer

OBJECTIVES

Upper airway assessment requires a fully-automated segmentation system for complete or sub-regional identification. This study aimed to develop a novel Deep Learning (DL) model for accurate segmentation of the upper airway and achieve entire and subregional identification.

METHODS

Fifty cone-beam computed tomography (CBCT) scans, including 24,502 slices, were labelled as the ground truth by one orthodontist and two otorhinolaryngologists. A novel model, a lightweight multitask network based on the Swin Transformer and U-Net, was built for automatic segmentation of the entire upper airway and subregions. Segmentation performance was evaluated using Precision, Recall, Dice similarity coefficient (DSC) and Intersection over union (IoU). The clinical implications of the precision errors were quantitatively analysed, and comparisons between the AI model and Dolphin software were conducted.

RESULTS

Our model achieved good performance with a precision of 85.88-94.25%, recall of 93.74-98.44%, DSC of 90.95-96.29%, IoU of 83.68-92.85% in the overall and subregions of three-dimensional (3D) upper airway, and a precision of 91.22-97.51%, recall of 90.70-97.62%, DSC of 90.92-97.55%, and IoU of 83.41-95.29% in the subregions of two-dimensional (2D) crosssections. Discrepancies in volume and area caused by precision errors did not affect clinical outcomes. Both our AI model and the Dolphin software provided clinically acceptable consistency for pharyngeal airway assessments.

CONCLUSION

The novel DL model not only achieved segmentation of the entire upper airway, including the nasal cavity and subregion identification, but also performed exceptionally well, making it well suited for 3D upper airway assessment from the nasal cavity to the hypopharynx, especially for intricate structures.

CLINICAL SIGNIFICANCE

This system provides insights into the aetiology, risk, severity, treatment effect, and prognosis of dentoskeletal deformities and obstructive sleep apnea. It achieves rapid assessment of the entire upper airway and its subregions, making airway management-an integral part of orthodontic treatment, orthognathic surgery, and ENT surgery-easier.

Large eddy simulation of droplet transport and deposition in the human respiratory tract to evaluate inhalation risk

As evidenced by the worldwide pandemic, respiratory infectious diseases and their airborne transmission must be studied to safeguard public health. This study focuses on the emission and transport of speech-generated droplets, which can pose risk of infection depending on the loudness of the speech, its duration and the initial angle of exhalation. We have numerically investigated the transport of these droplets into the human respiratory tract by way of a natural breathing cycle in order to predict the infection probability of three strains of SARS-CoV-2 on a person who is listening at a one-meter distance. Numerical methods were used to set the boundary conditions of the speaking and breathing models and large eddy simulation (LES) was used for the unsteady simulation of approximately 10 breathing cycles. Four different mouth angles when speaking were contrasted to evaluate real conditions of human communication and the possibility of infection. Breathed virions were counted using two different approaches: the breathing zone of influence and direction deposition on the tissue. Our results show that infection probability drastically changes based on the mouth angle and the breathing zone of influence overpredicts the inhalation risk in all cases. We conclude that to portray real conditions, the probability of infection should be based on direct tissue deposition results to avoid overprediction and that several mouth angles must be considered in future analyses.

Structural and functional changes of nasal cavity and maxillary sinus in patients with skeletal class III malocclusion 1 year after bimaxillary surgery

PURPOSE

This study aimed to analyse changes in the nasal cavity and maxillary sinus structure and function in patients with skeletal class III malocclusion 1 year after bimaxillary surgery.

MATERIALS AND METHODS

In this study, cone-beam computed tomography (CBCT) images of 20 patients (10 men and 10 women; mean age 24.3 ± 3.4 years) with skeletal class III malocclusion who underwent Le Fort I osteotomy and bilateral sagittal split osteotomy were obtained before and 1 year after the surgery. CBCT data were stored opened with element 3D (E3D) to establish a nasal airway model (the paranasal sinus includes only the maxillary sinus). Ansys (ANSYS) software is used for simulation and analysis.

RESULTS

The maxillary sinus and nasal cavity volumes decreased significantly 1 year after the surgery. After surgery, the volume of nasal cavity decreased by 13.5%, and the average volume of maxillary sinus decreased by 7.8%. There was no significant difference in the degree of deviation of the septum and nasal cavity resistance, and air distribution in the maxillary sinus did not change. The nasal cavity wall shear stress change was similar to that before surgery.

CONCLUSIONS

The maxillary sinus volume and nasal cavity volume of patients with skeletal class III malocclusion changed significantly after bimaxillary surgery, but there was no significant change in nasal ventilation function 1 year after surgery.

Wet surface wall model for latent heat exchange during evaporation

Air conditioning is a dual heat and mass transfer process, and the human nasal cavity achieves this through the mucosal wall surface, which is supplied with an energy source through the sub-epithelial network of capillaries. Computational studies of air conditioning in the nasal cavity have included temperature and humidity, but most studies solved these flow parameters separately, and in some cases, a constant mucosal surface temperature was used. Recent developments demonstrated that both heat and mass transfer need to be modeled. This work expands on existing modeling efforts in accounting for the nasal cavity's dual heat and mass transfer process by introducing a new subwall model, given in the Supplementary Materials. The model was applied to a pipe geometry, and a human nasal cavity was recreated from CT-scans, and six inhalation conditions were studied. The results showed that when the energy transfer from the latent heat of evaporation is included, there is a cooling effect on the mucosal surface temperature.

The role of normal nasal morphological variations from race and gender differences on respiratory physiology

This study identifies anatomical and airflow-induced relationships based on nasal morphological variations due to inter- and intra-racial differences and gender. Subject-specific nasal airway reconstruction was created from computed tomography images in 16 subjects: 4 subjects from each ethnic group (Black, East Asian, Caucasian, and Latino) comprising of 2 males and 2 females. Volume, surface area and nasal index were calculated, as well as airflow rate and nasal resistance after computational fluid dynamics simulations in the nasal airway. Results showed that nasal airspace surface area (p = 0.0499) and volume (p = 0.0281) were significantly greater in males than in females. Nasal volume was greatest in East Asians (Median = 20.38cm³, Interquartile Range [IQR] = 4.58 cm³), Latinos had the greatest surface area (Median = 219.70cm², IQR = 29.56cm²). On average, East Asian and Black females had larger nasal index than their male counterparts. Caucasians had the highest median nasal resistance (0.050 Pa.s/mL, IQR = 0.025 Pa.s/mL). Results indicate that there exist anatomical variabilities based on race and gender. However, these variabilities may not significantly influence nasal function.

Combining experimental and computational techniques to understand and improve dry powder inhalers

INTRODUCTION

: Dry Powder Inhalers (DPIs) continue to be developed to deliver an expanding range of drugs to treat an ever-increasing range of medical conditions; with each drug and device combination needing a specifically designed inhaler. Fast regulatory approval is essential to be first to market, ensuring commercial profitability.

AREAS COVERED

: In vitro deposition, particle image velocimetry, and computational modelling using the physiological geometry and representative anatomy can be combined to give complementary information to determine the suitability of a proposed inhaler design and to optimise its formulation performance. In combination they allow the entire range of questions to be addressed cost-effectively and rapidly.

EXPERT OPINION

: Experimental techniques and computational methods are improving rapidly, but each needs a skilled user to maximize results obtained from these techniques. Multidisciplinary teams are therefore key to making optimal use of these methods and such qualified teams can provide enormous benefits to pharmaceutical companies to improve device efficacy and thus time to market. There is already a move to integrate the benefits of Industry 4.0 into inhaler design and usage, a trend that will accelerate.

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.

Can computational fluid dynamic models help us in the treatment of chronic rhinosinusitis

PURPOSE OF REVIEW

The aim of this study was to review the recent literature (January 2017-July 2020) on computational fluid dynamics (CFD) studies relating to chronic rhinosinusitis (CRS), including airflow within the pre and postoperative sinonasal cavity, virtual surgery, topical drug and saline delivery (sprays, nebulizers and rinses) and olfaction.

RECENT FINDINGS

Novel CFD-specific parameters (heat flux and wall shear stress) are highly correlated with patient perception of nasal patency. Increased ostial size markedly improves sinus ventilation and drug delivery. New virtual surgery tools allow surgeons to optimize interventions. Sinus deposition of nasal sprays is more effective with smaller, low-inertia particles, outside of the range produced by many commercially available products. Saline irrigation effectiveness is improved using greater volume, with liquid entering sinuses via 'flooding' of ostia rather than direct jet entry.

SUMMARY

CFD has provided new insights into sinonasal airflow, air-conditioning function, the nasal cycle, novel measures of nasal patency and the impact of polyps and sinus surgery on olfaction. The deposition efficiency of topical medications on sinus mucosa can be markedly improved through parametric CFD experiments by optimising nasal spray particle size and velocity, nozzle angle and insertion location, while saline irrigation effectiveness can be optimized by modelling squeeze bottle volume and head position. More sophisticated CFD models (inhalation and exhalation, spray particle and saline irrigation) will increasingly provide translational benefits in the clinical management of CRS.

Comparison of micron- and nano-particle transport in the human nasal cavity with a focus on the olfactory region

Intranasal administration of drugs serves as a promising, noninvasive option for the treatment of various disorders of the central nervous system and upper respiratory tract. Predictive, ie, realistic and accurate, particle tracking in the human nasal cavities is an essential step to achieve these goals. The major factors affecting aerosol transport and deposition are the inhalation flowrate, the particle characteristics, and the nasal airway geometry. In vivo and in vitro studies using nasal cavity casts provide realistic images regarding particle-deposition pattern. Computational Fluid-Particle Dynamics (CF-PD) studies can offer a flexible, detailed and cost effective solution to the problem of direct drug delivery. The open-source software OpenFOAM was employed to conduct, after model validation, laminar and turbulent fluid-particle dynamics simulations for representative nasal cavities. Specifically, micron particles and nanoparticles were both individually tracked for different steady airflow rates to determine sectional deposition efficiencies. For micron particles, inertial forces were found to be the dominating factor, resulting in higher deposition for larger particles, mainly due to impaction. In contrast, diffusional effects are more important for nanoparticles. With a focus on the olfactory region, the detailed analysis of sectional deposition concentrations, considering a wide range of particle diameters, provide new physical insight to the particle dynamics inside human nasal cavities. The laminar/turbulent Euler-Lagrange modelling approach for simulating the fate of nanoparticles form a foundation for future studies focusing on targeted drug delivery. A major application would be direct nanodrug delivery to the olfactory region to achieve large local concentrations for possible migration across the blood-brain-barrier.