COMPUTATIONAL FLUID DYNAMICS

COMPUTATIONAL FLUID DYNAMICS

INTRODUCTION

Breathing is a vital function to sustain life. Human respires by exchanging gasses i.e. by expelling carbon dioxide and taking oxygen in from the surroundings. The respiratory tract of human consists of respiratory and conducting areas. The conducting area is further composed of nasopharynx, nasal cavity, bronchi and respiratory bronchioles. The respiratory area is situated distant to the alveoli where swift exchange of solute occurs. When breathing conditions are normal the lungs constantly fills and deflates. However, under abnormal conditions, this mechanism gets disturbed.  In this case treatments are given via routines like oral or local. Most drugs used to target are for patients of diseases like emphysema, chronic obstructive pulmonary diseases (COPD) and asthma. These conditions are characterized by a persistent and gradually increasing airflow restriction producing a slow reduction of the rate of mass flow within the respiratory system (Dolovich, Ruffin and Roberts, 1981). Additionally, such diseases may lead to airway deformation. Geometry of airway is an imperative aspect when taking into account of deposition of particle in the respiratory system. In addition to limitations linked to the conventional management of a variety of chronic respiratory diseases an increasing consideration has been paid to the use of targeted drug delivery systems. In the human airways various studies have been conducted on particle transport and airflow for years. The good vascularization, huge surface area, vast capacity for exchange of solute and extreme-thinness of the epithelium of alveoli make the lung ideal for drug delivery.

The effectiveness of a treatment mainly relies on the methods via which a drug is provided and optimal drug concentration  since any deviation from the provided dose of drug can prove to be toxic or  may not generate any therapeutic effect. Certain severe diseases take time to cure; this has suggested an increasing requirement for a multidisciplinary move towards the delivery of therapeutic drugs to target tissues (Scheuch and Siekmeier, 2007). For example, for diseases like asthma the drug delivery through the inhaled route is considered to be the more efficient way compared to the oral intake of medication. Lately the delivery of drugs for primarily systemic action is regarded as an appealing non-invasive substitute to intravenous administration. Delivery of drug to human airways has turned out to be a good target and of incredible biomedical and scientific curiosity in the health care study sphere since the lung is equipped with absorbing pharmaceuticals ability for any route either a systematic or a local one. The epithelial cells of respiratory system have a major function in the control of airway quality and the formation of respiratory lining fluid. Considering this important fact, growing interest has been shown to the likelihood of a use of drug delivery system via pulmonary route for not only local but also systemic delivery of therapeutic drug agents (Patil and Sarasija, 2012). Nevertheless, it is still not likely to determine precisely what amount of the inhaled drug in reality reaches the target area within the human airways.  Evidently the need for accuracy in drugs dosing is needed. An accurate idea of the delivery of drug within the airway can facilitate achievement of optimum therapeutic effects. Therefore, a model known as Computational Fluid Dynamics is studied for the precise delivery of drug.  The requirement for more accurate and specific techniques has promoted the application of this technology. Previously, it has been successfully in use in engineering for analysis and finding solutions of problems involving fluid flows (Leong, Chen, Lee, et al., 2010). Now it has founds its new applications in the field of medicine. Moreover, respiratory diseases are gaining more consideration in recent years. The respiratory passages are not simple areas to study and therefore CFD use provides a substitutive way of assessing the impact of pharmaceutical aerosols/drugs in the management of respiratory disorders. Research on particle deposition within the airways has chiefly been conducted as a result of air pollution and related consequences on the life quality, arising from the industrialization and urbanisation (Ayappa and Rapoport, 2003). The particles deposition in human lungs can lead to a number of respiratory diseases. WHO (2014) has also shown that 3 out of 10 major reasons behind mortality globally were due to respiratory ailments. Also, the ability to determine the particle deposition of medicines on the respiratory tract internal surfaces is essential so as to make sure that the areas affected by the diseases get the proper drugs without causing any adverse effects or losses. Thus, there is a requirement for ongoing studies and experiments using mature technologies like Computational Fluid Dynamics. The focus of this paper is to examine the particle deposition or drug delivery in human airway by means of computational flow modelling in addition to advantages, disadvantages and novelties of CFD.

WHAT IS COMPUTATIONAL FLUID DYNAMICS (CFD)?

Computational Fluid Dynamics (CFD) is a technique of simulating behaviour of fluid flow by means of high pace computers (Versteeg, and Malalasekera, 2007).  This model may serve as a competent way of studying the difficult effects of ventilatory parameters, airway geometry, and features of particle and thus help in the plan of human subject trials (Leong, Chen, Lee, et al. 2010).  Mathematical equations are used in this model and that explain the behaviour of gases and air i.e. momentum, mass conservation and energy.  It also uses algorithms for the purpose of analysis and finding solutions for problems associated with fluid flow. CFD has advanced to the rising power and reduced price of computers, and it is now utilized for solving of the Navier–Stokes equations. The Navier–Stokes equations regulates the movement of fluids and they were first found at the same time by Claude Navier, a French engineer, and George Stokes,an Irish enginee back to hundreds of years ago. They are anchored in Newton's laws of movement and are appropriate to be applies for any kind of flow. They can be employed to find out the pressure and velocity, and therefore a fluid behaviour in any point in space.

In present research on pulmonology, techniques of Computational Fluid Dynamics (CFD) are considered highly valuable. A computational model is able to track the drug’s progress from the device of delivery via the respiratory system and the consequent medication uptake. It precisely simulates the technique of inhalation corresponding with the lung volume and breathing cycle position (Walters, and Luke, 2010). Furthermore, an appropriate computational domain formation is important to get a helpful solution. Therefore, geometry needs to be carefully generated, amended and changed.

How CFD works?

CFD models are made from MRI or CT scan images of high-resolution with the help of an algorithm of commercial computer that changes data obtained via scanning into a three-dimensional model. This is presented in figure 1.  

Figure 2: Production of nose model of human and CFD simulation

Model outputs comprise velocity, airflow pattern (either turbulent or laminar), pressure, particle deposition, wall shear stress, and changes of temperature, at dissimilar rates of flow, in diverse parts of the airways. The results of present anatomical factors together with post-operative alterations can be considered. The results are calculated using Navier-Stokes equation as show in figure 3.

Figure 3: Navier-Stokes equation

ADVANTAGES OF CFD

The advantages of computational model analysis can be described in short words as follows: considerable savings in costs and time compared to other models, the analysis of systems or conditions that are very hard to simulate experimentally, and a almost limitless level of detail. Computer fluid dynamics (CFD) are in use for a  number of years now to learn and resolve problems related fluid in the industry and presents a smart way-out for precisely explaining systems at a practical cost (Pless, Keck, Wiesmiller, Lamche, Aschoff and Lindemann, 2004).

1.      Predict The Particles Behaviour

A great number of studies have conducted modelling of airways using computational domain (Sandeau, 2010; Gemci, 2008). Usmani, Biddiscombe and Barnes (2005) have tried to validate the results obtained from the particles deposition and comparing by the result of CFD. They did so by the help of a clinical test. They analysed the effect of the size of the particle on lung deposition in patients of asthma. During one deep breath these patients inhaled technetium-99m–labeled monodisperse albuterol aerosols with a mean aerodynamic diameter of 1.5, 3 and 6 µm. A gamma camera visualization was used to give both a visual and quantitative distribution of particles inside the respiratory system. CT scan for upper airway was also taken. The computations of laminar flow were conducted for one patient with uneven boundary state while the particles were being injected at the maximum flow rates. The particle density was shown by the results of experiment; high density of particle was noticed at red areas while low density of particles was noted at blue areas.

 The experimental results by Usmani, Biddiscombe and Barnes (2005) showed the particle density as visually given by the gamma camera. Red areas indicated a high particle density, blue areas a low particle density. The CFD results demonstrated coloured particle trails by residence time. Slow moving particles were shown by red colour while fast one with blue. This can be presented from the figure 2 as shown below.

Figure 2: simulation Results with CFD about of behaviour of particle at diverse sizes (Clarà and Tena, 2012).

In this experiment the results of particles tracks in the computational fluid dynamic ended where they strike the wall. In another words, larger particles in CFD were unable to go into the lungs beyond the big airways, they stopped in the big airways.  The smaller particles showed easy deposition to areas further than into the lungs. Thus, CFD results illustrated the similar tendency in lung deposition in opposition to size of particle as was obtained from Usmani, Biddiscombe and Barnes (2005) experiments. CFD computations well foresee the particles behaviour in the lungs.

2.      Visualisation of physiological and pathological conditions of airways

In the controlled clinical trial by Sun et al., for example, patients with nasal septum deviations were compared to subjects with no anatomical changes. Sun et al. concluded that by using nasal airflow simulation, it is possible to visualize the changes in nasal airflow caused by abnormal anatomy of the nose. Liu likewise demonstrated the impact of various forms of septal deviation on nasal airflow characteristics. Similarly, Guo showed that the unilateral hypertrophy infraturbinal also changed normal anatomy and influenced aerodynamics of the nasal cavity.

3.      CFD Used In The Process Of Drug Delivery To The Nose

Since high efficiency of computers and sophisticated numerical techniques, practicality of these computationally dynamics has been improved in current years.  Nowadays computer-aided designs can be safely applied to complex passages like nasal airway.

4.      Enhances Drug Delivery

A study found that numerical modelling can serve as an effective means in enhancing the drug delivery via aerosol sprays (Farkas , Balásházy, Szocs , 2006). Satisfactory numerical meshes, produced in dissimilar airway sections, facilitated more accurately to describe local patterns of deposition and trajectories of inhaled particles as done previously. They also found that deposition patterns demonstrate an increasing level of deposition heterogeneity within the airways. For example, in alveoli, the patterns of deposition are greatly affected by size of particle and course of gravity (Farkas , Balásházy, Szocs , 2006).

In addition to drug delivery, computational fluid dynamics is assisting surgeons advance their knowledge of airway physiology and the result of surgical amendments on the airflow in the airways (Quadrio, et al., 2014).

 NOVELTIES IN COMPUTATIONAL FLUID DYNAMICS

In respiratory physiology CFD has potential to examine nasal anatomy, vital functions of the nose like warming and conditioning of air, and the impact of pathophysiological alterations on breathing via nose (Achilles, et al., 2013). In addition, results following surgery of nose may also be predicted by the help of CFD.  This latest technology can also be applied in patients with problem of allergic rhinitis.

This novel technique about particle deposition in the lung can be utilized by pharmaceutical companies in the synthesis of innovative drugs that can help patients in diverse subjects (Vos, De Backer, Devolder, et al., 2006).  The understanding about the effect of inhaled drug can be achieved during the phase of testing.

Beside respiratory region CFD has paved its way to the study of fluid dynamics which are developed by reconstructive surgeries like bidirectional cavopulmonary anastomosis, Blalock-Taussig shunt and total cavopulmonary connection (Migliavacca, Dubini, & de Leval, 2000). Likewise, computational fluid dynamic (CFD) is used to comprehend the complex temporal and spatial hemodynamic alterations that exist in patients suffering from carotid artery stenosis of high-grade (Schirmer and Malek, 2012).

DISADVANTAGES OF COMPUTATIONAL FLUID DYNAMICS

It can be argued that Computational fluid dynamic models are merely simulations, and the expected results are obtained from difficult Navier-Stokes equation calculations that may not correspond to real life circumstances. Other disadvantages are given below.

1.      Geometry of Human Airway: The human airways are a complex composition to model. This is because they have a huge variety of sizes, are abundant, and they are obscure (Newman, 2005). Airways keep on changing their shape and size under normal conditions of breathing (Metzger, et al., 2008). It is therefore not computationally possible to carry out comprehensive simulations on entire human airways (Kleinstreuer, Zhang, and Zheng, 2008).

2.      Require Expertise: Computational fluid dynamic models are applied by the help of computers and therefore an expertise is required to handle computers and run this model. Since geometry of the flow is needed to get in order to represent computationally, this also necessitates skills. Success in the use of CFD lies basically in the availability of personnel with sufficient experience and knowledge in the management of these techniques. 

3.      In-depth Studies: Another particular concern is that since a number of respiratory tract diseases may keep on modifying the architecture of airways, simulation conducted under such circumstances requires more studies in detail, changing the model geometry. One more important thing is a need of study of respiratory zone area within the model.

4.      Take times : To become accustomed to an individual patient, computational model may primarily need a number of days of work, and it may affect the patient’s compliance and overall results.

POSSIBLE SOLUTION OF PROBLEMS FACED TO CFD TECHNIQUES

Since achieving personalized treatment needs time, one possible way to achieve it would be to develop exclusive airway models by the help of CFD techniques. Majority of hospitals have now acquired more strong software and high-definition scanners that can likely create 3-D reformations of the bronchial tree. Such three-dimensional images may serve as a central source of data for the production of a model that may offer analysis of particle deposition and flow via CFD systems. The possibilities of CT for studying the airway are underestimated. Nevertheless, novel techniques of making these models simpler are also being in a process of discovering. For instance, the utilization of partly constructed models in a sequence of bifurcations has facilitated decrease in times of simulation and modelling. CFD is a state of the art tool with potential to axel and further enhance development speed with the operation of codes of design optimization.  As processing of computer improves, more precise calculations of the specific respiratory airways would be capable to be ever more correctly reproduced in improved 3D models (Castro, Castro, and Costas, 2005).

In addition to in-depth studies, these mathematical models applying CFD should be compared and appraised with the standard approach given by Positron emission tomography or gammagraphy images.  CFD technology has a potential to visualize three-dimensional drug effects on the respiratory airways and thus it constitutes an appropriate tool for the drug effects visualization even for the therapy of nose conditions.

Conclusion

Overall, Computational fluid dynamic is a powerful tool with the application enabling drug deposition, physiological exploration and accurate results. These simulations generate realistic models which concur with other techniques of evaluating air flow of airways, and create dependable, comprehensible results. Furthermore this latest techniques can make possibility of a state where inhalers could be planned in such a manner that individual patient may get the accurate drug dose at the correct region in the respiratory system.

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