Biomedical and biophysical limits to mathematical modeling of pulmonary system mechanics: a scoping review on aerosol and drug delivery.

Undoubtedly, the construction of the biomechanical geometry systems with the help of computer tomography (CT) and magnetic resonance imaging (MRI) has made a significant advancement in studying in vitro numerical models as accurately as possible. However, some simplifying assumptions in the computational studies of the respiratory system have caused errors and deviations from the in vivo actual state. The most important of these hypotheses is how to generate volume from the point cloud exported from CT or MRI images, not paying attention to the wall thickness and its effect in computational fluid dynamic method, statistical logic of aerosol trap in software; and most importantly, the viscoelastic effect of respiratory tract wall in living tissue pointed in the fluid-structure interaction method. So that applying the viscoelastic dynamic mesh effect in the form of the moving deforming mesh can be very effective in achieving more appropriate response quality. Also, changing the volume fraction of the pulmonary extracellular matrix constituents leads to changes in elastic modulus (storage modulus) and the viscous modulus (loss modulus) of lung tissue. Therefore, in the biomedical computational methods where the model wall is considered flexible, the viscoelastic properties of the texture must be considered correctly

Mechanics of airflow in human inhalation

The mechanics of airflow in the large airways during inspiration affects important physiological functions such as ventilation, olfaction, heat exchange and mass transfer. The behaviour of the airflow is important not only for healthcare applications including diagnosis, intervention planning and assessment, but for inhalation toxicology. This research aims to further the understanding of human nasal physiology through computational modelling. Specifically, the effects of transient inhalation conditions on flow dynamics and transport were characterised and the changes in flow behaviour in response to certain pathologies quantified. The key findings can be summarised as follows: Firstly, the time scales for airflow in the large airways have been identified and the initial flow patterns revealed. Three phases in the temporal behaviour of the flow were identified (flow initiation, quasi-equilibrium and decay). The duration of each phase differs depending on the quantity of interest. Flow in the nose was characterised as transitional, whilst in parts of the descending airways it is turbulent, particularly in the faster moving regions around the jets which may occur in the pharynx, larynx and at the superior end of the trachea. The bulk of the flow is biased to fill only certain regions of the airways, whilst other regions carry little flow, due to features upstream. Analysis of cross-sectional images provided by medical imaging does not necessarily provide a representative view of the area available to the flow. Various scalar species were employed to represent the fate of nanoparticles and gaseous species within the airways. Only species with high diffusion rates exhibited significant absorption at the airway walls. Airway pathologies often cause changes to the geometry of the airway. One such pathology, the goitre, was found to curve the trachea and in some cases cause constriction. Both these geometric changes were found to increase the pressure loss and energy required to drive flow through the trachea. Furthermore, the flow in pathological cases was more disturbed. High resolution simulations have been used to address these topics and the scales simulated have been analysed in terms of the smallest features possible in the flow to determine their fidelity.Open Acces

Investigation On Nasal Airflow Of Malaysian Females Using Cfd

Inabilities of objective measurement methods to obtain various important information regarding human nasal airflow leads to the application of Computational Fluid Dynamics (CFD) to study and analyze the complicated structures of the nasal cavity. This research focuses on detailed investigation of Malaysian female nasal cavities which includes mucous effects, standardized model and disease cases. In this study, mucous layer effects on nasal airflow were studied by thickening the mucous layer from 5 to 50 μm and analysis were carried out with mass flow rate ranging from 7.5 to 20 L/min. Analysis results of non-mucous effects were compared with the thickening mucous layer effects. Based on the results obtained, healthy mucous layer thickness within the range of 5 to 30 μm caused insignificant effects towards the total nasal airflow. Unique and distinctive features of the human nasal cavities require generalization of its geometry and thus, this study creates a standardized female Malaysian nasal cavity. The methodology implemented in this research involves simple programming of averaging pixel values from a set of Computational Tomography (CT) scans. Therefore, it is simpler and requires shorter time compared to other method used in previous research. The average velocity magnitudes calculated from the four individual models match closely with the standardized model with a difference of less than 20%. This proves that the generated model can represent an average and standardized model of an adult Malaysian female. Huge differences from the comparisons with the standardized model of different population shows the need for a standardized model which represents different xx population due to the diversity of the human nasal cavities. In addition to that, Particle Image Velocimetry (PIV) experimental work and acoustic rhinometry measurements were carried out for validation purposes. Good agreement between the computational, calculation, experimental and rhinometry measurements results provides a strong validation of the computational analysis conducted in this research. As an initial step towards implementing virtual surgery in the future, this study analyzed the pre-operation and post-operation CT scans of the two female patients with nasal diseases (sinusitis). CFD analysis for pre and post-operation conditions allow better observation of the infected areas as well as the nasal airflow behavior such as velocity magnitudes in order to assist rhinologist to view the effects of the surgeries carried out. The results and observations obtained from this research bring a step forward in advancement of virtual surgery in the future and will be beneficial in clinical research development

Viruses exacerbating chronic pulmonary disease: the role of immune modulation

Chronic pulmonary diseases are a major cause of morbidity and mortality and their impact is expected to increase in the future. Respiratory viruses are the most common cause of acute respiratory infections and it is increasingly recognized that respiratory viruses are a major cause of acute exacerbations of chronic pulmonary diseases such as asthma, chronic obstructive pulmonary disease and cystic fibrosis. There is now increasing evidence that the host response to virus infection is dysregulated in these diseases and a better understanding of the mechanisms of abnormal immune responses has the potential to lead to the development of new therapies for virus-induced exacerbations. The aim of this article is to review the current knowledge regarding the role of viruses and immune modulation in chronic pulmonary diseases and discuss avenues for future research and therapeutic implications

Numerical and experimental studies of air and particle flow in the realistic human upper airway models

The human upper airway structure provides access of ambient air to the lower respiratory tract, and it as an efficient filter to cleanse inspired air of dust bacteria, and other environmental pollutants. When air passes through airway passages, it constantly changes direction, which may lead to flow separation, recirculation, secondary flow and shear stress variations along the airway surface. Therefore, it is essential to understanding the air transport processes within the upper airway system. The functions are respiratory defence mechanisms that protecting the delicate tissues of the lower airway from the often harsh conditions of the ambient air. While protecting the lower respiratory system, however, the upper airway itself becomes susceptible to various lesions and infections from filtration of environmental pollutants. Inhaled particle pollutants have been implicated as a potential cause of respiratory diseases. In contrast, inhalation of drug particles deposited directly to the lung periphery results in rapid absorption across bronchopulmonary mucosal membranes and reduction of the adverse reactions in the therapy of asthma and other respiratory disorders. For this purpose, it is desirable that the particles should not deposit in the upper airways before reaching the lung periphery. Therefore, accurate prediction of local and regional pattern of inhaled particle deposition in the human upper airway should provide useful information to clinical researchers in assessing the pathogenic potential and possibly lead to innovation in inhalation therapies. With the development of the increasing computer power and advancement of modeling software, computational fluid dynamics (CFD) technique to study dilute gas-particle flow problems is gradually becoming an attractive investigative tool. This research will provide a more complete picture of the detailed physical processes within the human upper airway system. Owing to the significant advancements in computer technologies, it will allow us to efficiently construct a full-scaled model integrating the various functional biological elements including the nasal, oral, laryngeal and more generations of the bifurcation of the human upper airway system through imagining methodologies. A significant advantage of this human model is that the differences in airway morphology and ventilation parameters that exist between healthy and diseased airways, and other factors, can be accommodated. This model will provide extensive experimental and numerical studies to probe significant insights to the particle deposition characte ristics within the complex airway passages and better understanding of any important phenomena associated with the fluid-particle flow. It will also lead to an improved understanding of fluid/particle transport under realistic physiological conditions. New concepts and numerical models to capture the main features observed in the experimental program and innovative techniques will be formulated. The ability to numerically model and a better physical understanding of the complex phenomena associated with the fluid dynamics and biological processes will be one of the major medical contributions especially targeting drug delivery and health risk analysis. Its biomedical engineering significance lies in the fact that this will enable us to accurately evaluate potential biological effects by the inhaled drug particles, facilitating new drug research and development

Flow characterization inside airways with unsteady breathing patterns

Flow through human airways is characterized by unsteady flows, with flow separations at airway bifurcations. The oscillatory nature of airflow, unequal durations of inhalation time (IT), and exhalation time (ET) can facilitate gas exchange in higher generations of the human airway. Normal respiratory rate (RR) in adults ranges between 10-15 breaths per minute (bpm). RR varies in exercise conditions, mechanical ventilation strategies such as high-frequency oscillatory ventilation (HFOV), metabolic activities and pathological state to facilitate alveolar gas exchange. Previous studies characterized flows at steady inhalation and exhalation through airways. The individual effects of varying inhalation duration and breathing flow rate on flow through airways remains unknown. Our study focuses on various unsteady breathing patterns inside idealized airway models. The goal of this study is to characterize the effects of unsteady internal airflow through idealized airway geometries. Various scenarios of unsteady breathing patterns were simulated in ANSYS software (ANSYS, Inc., Canonsburg, PA, USA) to characterize the fluid dynamics involved in such an unsteady airflow mechanism. The first study includes unsteady breathing patterns such as normal, moderate, and high-frequency ventilation were investigated with variation in inhalation time (IT) to breathing time (BT) ratio. The second study includes abnormal breathing patterns such as tachypnea (~ 1.5x increase in RR), bradypnea (~ 1.5x decrease in RR), hyperpnea (deep breathing with abnormally large peak flow rate), and hypopnea (shallow breathing with abnormally low peak flow rate); and final study includes single nostril inhalation as in yoga pranayama breathing techniques. Simulations were performed for each breathing pattern as in internal airflow studies. Our results showed that secondary flow was an effective transport mechanism for flow inside idealized human airways. Airway local geometry plays a key role in flow distribution in higher generations. Discrepancy in the oscillatory flow relation Re/Wo^2 = 2L/D (L = stroke length; D = trachea diameter) was observed for IT/BT does not equal 50%, as L changed with IT/BT. We developed a modified dimensionless stroke length term including IT/BT. While viscous forces and convective acceleration were dominant for lower Wo, unsteady acceleration was dominant for higher Wo. Time to peak jet length during inhalation increased with an increase in breathing time. Single nostril and double nostril inhalation showed equal ventilation at higher generations in an idealized airway geometry

Statistical Shape Modelling and Segmentation of the Respiratory Airway

The human respiratory airway consists of the upper (nasal cavity, pharynx) and the lower (trachea, bronchi) respiratory tracts. Accurate segmentation of these two airway tracts can lead to better diagnosis and interpretation of airway-specific diseases, and lead to improvement in the localization of abnormal metabolic or pathological sites found within and/or surrounding the respiratory regions. Due to the complexity and the variability displayed in the anatomical structure of the upper respiratory airway along with the challenges in distinguishing the nasal cavity from non-respiratory regions such as the paranasal sinuses, it is difficult for existing algorithms to accurately segment the upper airway without manual intervention. This thesis presents an implicit non-parametric framework for constructing a statistical shape model (SSM) of the upper and lower respiratory tract, capable of distinct shape generation and be adapted for segmentation. An SSM of the nasal cavity was successfully constructed using 50 nasal CT scans. The performance of the SSM was evaluated for compactness, specificity and generality. An averaged distance error of 1.47 mm was measured for the generality assessment. The constructed SSM was further adapted with a modified locally constrained random walk algorithm to segment the nasal cavity. The proposed algorithm was evaluated on 30 CT images and outperformed comparative state-of-the-art and conventional algorithms. For the lower airway, a separate algorithm was proposed to automatically segment the trachea and bronchi, and was designed to tolerate the image characteristics inherent in low-contrast CT images. The algorithm was evaluated on 20 clinical low-contrast CT from PET-CT patient studies and demonstrated better performance (87.1±2.8 DSC and distance error of 0.37±0.08 mm) in segmentation results against comparative state-of-the-art algorithms

Delivery of RNAi Therapeutics to the Airways—From Bench to Bedside

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Unsteady-State Pressure and Flow Characteristics of the Human Nose: Pre- and Post-Nasal Turbinectomy

This research obtained quantitative data for pressure drop across the human nose during breathing. Quantitative and visual analyses of the transition between laminar and turbulent flow was also conducted. Controlling the flow of water through 2X scale models; pre- and post-turbinectomy, yielded a pressure versus flow rate curve, which demonstrated the transition between linear and quadratic flow. A hysteresis was observed which is concurrent with clinical observations. These findings suggest that the assumption of quasi-steady flow is invalid

Numerical studies of fluid-particle dynamics in human respiratory system

 This thesis investigates particle inhalation and its deposition in the human respiratory system for therapeutic and toxicology studies. Computational Fluid Dynamics (CFD) techniques including the Lagrangian approach to simulate gas-particle flows based on the domain airflow are used. The Lagrangian approach is used as it tracks each individual particle and determines its fate (e.g deposition location, or escape from computational domain). This has advantages over a Eulerian approach for respiratory inhalation flows as the volume fraction of the second phase can be neglected and a disperse phase for one-way coupling can be used. However, the very first step is to simulate and detail airflow structures. For the external airflow structures, the heat released from the human body has a significant effect on the airflow micro-environment around it in an indoor environment, which suggests that the transport and inhalation characteristics of aerosol particulates may also be affected since they are entrained by the air and their movement is dependent on the airflow field. Emphasis was put on the effect of human body heat on particle tracks. It was found that body heat causes a significant rising airflow on the downstream side of the body, which transports particles from a lower level into the breathing zone. The importance of body heat decreases with increasing indoor wind speed. Since the rising airflow exists only on the downstream side of an occupant, the occupant-wind orientation plays an important role in particle inhalation. The effect of body heat has to be taken into account when an occupant had his or her back to the wind, and the effect of body heat could be neglected when the occupant is facing the wind. A CFD model that integrates the three aspects of contaminant exposure by including the external room, human occupant with realistic facial features, and the internal nasal-trachea airway is presented. The results from the simulations visualize the flow patterns at different contaminant concentrations. As the particles are inhaled, they are transported through the respiratory airways, where some are deposited onto surrounding mucus walls while others may navigate through the complex geometry and even reach the lung airways, causing deleterious health effects. The studies in this thesis demonstrated that the transport and deposition of micron sized particles are dominated by its inertial property while submicron and nano sized particles are influenced by diffusion mechanisms. Studies based on an isolated model of the human nasal cavity or tracheobronchial airway tree rely on idealised inlet boundary condition imposed at the nostril or where, were a blunt, parabolic or uniform profile is applied. It is apparent that an integrated model made up of: i) room and ventilation, ii) aspiration efficiency, iii) and particle deposition efficiencies in the respiratory airway is needed. This leads to a more complete and holistic set of results, which can greatly contribute towards new knowledge in identifying preventative measures for health risk exposure assessment. With regards to the internal airflow structures and particle inhalation, ultrafine particle deposition sites in the human nasal cavity regions often omit the paranasal sinus regions. Because of the highly diffusive nature of nanoparticles, it is conjectured that deposition by diffusion may occur in the paranasal sinuses, which may affect the residual deposition fraction that leaves the nasal cavity. Thus a nasal-sinus model was created for analysis. In general there was little flow passing through the paranasal sinuses. However, flow patterns revealed that some streamlines reached the upper nasal cavity near the olfactory regions. These flow paths promote particle deposition in the sphenoid and ethmoid sinuses. Some differences were discovered in the deposition fractions and patterns for 5 and 10nm particles between the nasal-sinus and the nasal cavity models. This difference is amplified when the flow rate is decreased and at a flow rate of 4L/min the maximum difference was 17%. It is suggested that future evaluations of nanoparticle deposition should consider some deposition occurring in the paranasal sinuses especially if flow rates are of concern. Inhaled particles with pharmacological agents (e.g. histamine, methacholine) are introduced into the nasal cavity for targeted delivery. Effective nasal drug delivery is highly dependent on the delivery of the drug from the nasal spray device. Atomization of liquid spray occurs through the internal atomizer that can produce many forms of spray patterns and two of these, hollow-cone and full-cone sprays, are evaluated in this study to determine which spray pattern produced greater deposition in the middle regions of the nasal cavity. Past studies of spray particle deposition have ignored the device within the nasal cavity. Experimental measurements from a Particle Droplet Image Analyzer (PDIA) were taken in order to gain confidence to validate the initial particle conditions for the computational models.. Subsequent airflow patterns and its effects on particle deposition, with and without a spray device, are compared. Contours and streamlines of the flow field revealed that the presence of a spray device in the nasal vestibule produced higher levels of disturbed flow, which helped the dispersion of the sprayed particles. Particle deposition was found to be high in the anterior regions of the nasal cavity due to its inertia. Evaluation of the two spray types found that hollow spray cones produced more deposition in the middle regions of the nasal cavity