Topological analysis of particle transport in lung airways: Predicting particle source and destination

A verified and validated moving domain computational fluid dynamics solver with applications to cardiovascular flows

Computational fluid dynamics (CFD) in combination with patient-specific medical images has been used to correlate flow phenotypes with disease initiation, progression and outcome, in search of a prospective clinical tool. A large number of CFD software packages are available, but are typically based on rigid domains and low-order finite volume methods, and are often implemented in massive low-level C++ libraries. Furthermore, only a handful of solvers have been appropriately verified and validated for their intended use. Our goal was to develop, verify and validate an open-source CFD solver for moving domains, with applications to cardiovascular flows. The solver is an extension of the CFD solver Oasis, which is based on the finite element method and implemented using the FEniCS open source framework. The new solver, named OasisMove, extends Oasis by expressing the Navier-Stokes equations in the arbitrary Lagrangian-Eulerian formulation, which is suitable for handling moving domains. For code verification we used the method of manufactured solutions for a moving 2D vortex problem, and for validation we compared our results against existing high-resolution simulations and laboratory experiments for two moving domain problems of varying complexity. Verification results showed that the L 2 error followed the theoretical convergence rates. The temporal accuracy was second-order, while the spatial accuracy was second- and third-order using ℙ 1 / ℙ 1 and ℙ 2 / ℙ 1 finite elements, respectively. Validation results showed good agreement with existing benchmark results, by reproducing lift and drag coefficients with less than 1% error, and demonstrating the solver's ability to capture vortex patterns in transitional and turbulent-like flow regimes. In conclusion, we have shown that OasisMove is an open-source, accurate and reliable solver for cardiovascular flows in moving domains.

Guiding the prostatic artery embolization procedure with computational uid dynamics

Benign prostatic hyperplasia (BPH) is a common disease associated with lower urinary tract symptoms and the most frequent benign tumor in men. To reduce BPH therapy complications, prostatic artery embolization (PAE) was developed to replace the surgical options. PAE is a minimally invasive technique in which emboli are injected into the prostate arteries (PA), obstructing the blood flow in the hypervascular nodules. In this work, a personalized PAE treatment strategy was proposed using patient-specific computational fluid dynamics (CFD). First, the hemodynamics environment in the iliac arterial tree considering a large network of bifurcations was studied. The results showed complex blood flow patterns in the iliac arterial network. Subsequently, the transport of embolic particulates during PAE for the standard horizontal and a hypothetical vertical patient positioning was simulated using Lagrangian particle tracking. Emboli with different sizes were released at various locations across the iliac arterial tree. The emboli entering the PA were mapped back to their initial location to create emboli release maps (ERMs). The obtained ERMs during the standard patient positioning for smaller emboli at certain release locations showed distinct regions in which if the emboli were released within these regions, all of them would reach the PA without non-target embolization. During the hypothetical vertical patient positioning, the larger emboli formed a larger coherent region in the ERMs. Our patient-specific model can be used to find the best spatial location for emboli injection and perform the embolization procedure with minimal off-target delivery.

The effect of the volumetric flow rate and endotracheal tube diameter on the pressure distribution in human airways

The comprehension of the fluid flow in the upper airways is of paramount importance when treating patients under clinical conditions that demand mechanical ventilation. Barotrauma and overdistension are related to undesirable pressures and might be responsible for morbidity and mortality. In the current work we use computational fluid dynamics to investigate the pressure field in the upper respiratory airways. We performed a set of simulations varying the volumetric flow rate of mechanical ventilators and we have shown that the pressure profile can be calculated by means of the volumetric flow rate in accordance with a mathematical expression given by P_av=aV˙², where P_av is the average pressure at selected sections of the upper airways and V˙ is the volumetric flow rate. Numerical findings provide evidence that the constant a varies with the location of the plane in the upper airways. We also show that some particular diameters of endotracheal tubes (ETT) must be used with care for a given range of volumetric flow rates. Overall, we document an important relationship among pressure, volumetric flow rate and selected internal diameters from ETT.

Flow topology and targeted drug delivery in cardiovascular disease

Targeted drug delivery is a promising technique to direct the drug to the specific diseased region. Nanoparticles have provided an attractive approach for this purpose. In practice, the major focus of targeted delivery has been on targeting cell receptors. However, the complex fluid mechanics in diseased biomedical flows questions if a sufficient number of nanoparticles can reach the desired region. In this paper, we propose that hidden topological structures in cardiovascular flows identified with Lagrangian coherent structures (LCS) control drug transport and provide valuable information for optimizing targeted drug delivery efficiency. We couple image-based computational fluid dynamics (CFD) with continuum transport models to study nanoparticle transport in coronary artery disease. We simulate nanoparticle transport as well as the recently proposed shear targeted drug delivery system that couples micro-carriers with nanoparticle drugs. The role of the LCS formed near the stenosed artery in controlling drug transport is discussed. Our results motivate the design of smart micro-needles guided by flow topology, which could achieve optimal drug delivery efficiency.

Computational fluid dynamic models as tools to predict aerosol distribution in tracheobronchial airways

Aerosol and pollutants, in form of particulates 5-8 μm in main size face every day our respiratory system as natural suspension in air or forced to be inhaled as a coadjutant in a medical therapy for respiratory diseases. This inhalation happens in children to elderly, women and men, healthy or sick and disable people. In this paper we analyzed the inhalation of aerosol in conditions assimilable to the thermal therapy. We use a computational fluid dynamic 3D model to compute and visualize the trajectories of aerosol (3-7-10-25 µm) down to the sixth generation of bronchi, in a steady and dynamic condition (7 µm) set as breath cycle at rest. Results, compared to a set of milestone experimental studies published in literature, allow the comprehension of particles behavior during the inhalation from mouth to bronchi sixth generation, the visualization of jet at larynx constriction and vortices, in an averaged characteristic rigorous geometrical model including tracheal rings. Results on trajectories and deposition show the importance of the including transient physiological breath cycle on aerosol deposition analyses. Numerical and graphical results, may enable the design of medical devices and protocols to make the inhalations more effective in all the users' population.

Computational fluid dynamics modelling of human upper airway: A review

BACKGROUND AND OBJECTIVE

Human upper airway (HUA) has been widely investigated by many researchers covering various aspects, such as the effects of geometrical parameters on the pressure, velocity and airflow characteristics. Clinically significant obstruction can develop anywhere throughout the upper airway, leading to asphyxia and death; this is where recognition and treatment are essential and lifesaving. The availability of advanced computer, either hardware or software, and rapid development in numerical method have encouraged researchers to simulate the airflow characteristics and properties of HUA by using various patient conditions at different ranges of geometry and operating conditions. Computational fluid dynamics (CFD) has emerged as an efficient alternative tool to understand the airflow of HUA and in preparing patients to undergo surgery. The main objective of this article is to review the literature that deals with the CFD approach and modeling in analyzing HUA.

METHODS

This review article discusses the experimental and computational methods in the study of HUA. The discussion includes computational fluid dynamics approach and steps involved in the modeling used to investigate the flow characteristics of HUA. From inception to May 2020, databases of PubMed, Embase, Scopus, the Cochrane Library, BioMed Central, and Web of Science have been utilized to conduct a thorough investigation of the literature. There had been no language restrictions in publication and study design of the database searches. A total of 117 articles relevant to the topic under investigation were thoroughly and critically reviewed to give a clear information about the subject. The article summarizes the review in the form of method of studying the HUA, CFD approach in HUA, and the application of CFD for predicting HUA obstacle, including the type of CFD commercial software are used in this research area.

RESULTS

This review found that the human upper airway was well studied through the application of computational fluid dynamics, which had considerably enhanced the understanding of flow in HUA. In addition, it assisted in making strategic and reasonable decision regarding the adoption of treatment methods in clinical settings. The literature suggests that most studies were related to HUA simulation that considerably focused on the aspects of fluid dynamics. However, there is a literature gap in obtaining information on the effects of fluid-structure interaction (FSI). The application of FSI in HUA is still limited in the literature; as such, this could be a potential area for future researchers. Furthermore, majority of researchers present the findings of their work through the mechanism of airflow, such as that of velocity, pressure, and shear stress. This includes the use of Navier-Stokes equation via CFD to help visualize the actual mechanism of the airflow. The above-mentioned technique expresses the turbulent kinetic energy (TKE) in its result to demonstrate the real mechanism of the airflow. Apart from that, key result such as wall shear stress (WSS) can be revealed via turbulent kinetic energy (TKE) and turbulent energy dissipation (TED), where it can be suggestive of wall injury and collapsibility tissue to the HUA.

Particle transport and deposition correlation with near-wall flow characteristic under inspiratory airflow in lung airways

Exposure of lung airways to detrimental suspended aerosols in the environment increases the vulnerability of the respiratory and cardiovascular systems. In addition, recent developments in therapeutic inhalation devices magnify the importance of particle transport. In this manuscript, particle transport and deposition patterns in the upper tracheobronchial (TB) tree were studied where the inertial forces are considerable for microparticles. Wall shear stress divergence (WSSdiv) is proposed as a wall-based parameter that can predict particle deposition patterns. WSSdiv is proportional to near-wall normal velocity and can quantify the strength of flow towards and away from the wall. Computational fluid dynamics (CFD) simulations were performed to quantify airflow velocity and WSS vectors for steady inhalation in one case-control and unsteady inhalation in six subject-specific airway trees. Turbulent flow simulation was performed for the steady case using large eddy simulation to study the effect of turbulence. Magnetic resonance velocimetry (MRV) measurements were used to validate the case-control CFD simulation. Inertial particle transport was modeled by solving the Maxey-Riley equation in a Lagrangian framework. Deposition percentage (DP) was quantified for the case-control model over five particle sizes. DP was found to be proportional to particle size in agreement with previous studies in the literature. A normalized deposition concentration (DC) was defined to characterize localized deposition. A relatively strong correlation (Pearson value > 0.7) was found between DC and positive WSSdiv for physiologically relevant Stokes (St) numbers. Additionally, a regional analysis was performed after dividing the lungs into smaller areas. A spatial integral of positive WSSdiv over each division was shown to maintain a very strong correlation (Pearson value > 0.9) with cumulative spatial DC or regional dosimetry. The conclusions were generalized to a larger population in which two healthy and four asthmatic patients were investigated. This study shows that WSSdiv could be used to predict the qualitative surface deposition and relative regional dosimetry without the need to solve a particle transport problem.