Computational fluid dynamics-based virtual angiograms for the detection of flow stagnation in intracranial aneurysms.

The goal of this study was to test if CFD-based virtual angiograms could be used to automatically discriminate between intracranial aneurysms (IAs) with and without flow stagnation. Time density curves (TDC) were extracted from patient digital subtraction angiography (DSA) image sequences by computing the average gray level intensity inside the aneurysm region and used to define injection profiles for each subject. Subject-specific 3D models were reconstructed from 3D rotational angiography (3DRA) and computational fluid dynamics (CFD) simulations were performed to simulate the blood flow inside IAs. Transport equations were solved numerically to simulate the dynamics of contrast injection into the parent arteries and IAs and then the contrast retention time (RET) was calculated. The importance of gravitational pooling of contrast agent within the aneurysm was evaluated by modeling contrast agent and blood as a mixture of two fluids with different densities and viscosities. Virtual angiograms can reproduce DSA sequences if the correct injection profile is used. RET can identify aneurysms with significant flow stagnation even when the injection profile is not known. Using a small sample of 14 IAs of which seven were previously classified as having flow stagnation, it was found that a threshold RET value of 0.46 s can successfully identify flow stagnation. CFD-based prediction of stagnation was in more than 90% agreement with independent visual DSA assessment of stagnation in a second sample of 34 IAs. While gravitational pooling prolonged contrast retention time it did not affect the predictive capabilities of RET. CFD-based virtual angiograms can detect flow stagnation in IAs and can be used to automatically identify aneurysms with flow stagnation even without including gravitational effects on contrast agents.

High-Fidelity Simulation of Pathogen Propagation, Transmission and Mitigation in the Built Environment.

An overview of high-fidelity modeling of pathogen propagation, transmission and mitigation in the built environment is given. In order to derive the required physical and numerical models, the current understanding of pathogen, and in particular virus transmission and mitigation is summarized. The ordinary and partial differential equations that describe the flow, the particles and possibly the UV radiation loads in rooms or HVAC ducts are presented, as well as proper numerical methods to solve them in an expedient way. Thereafter, the motion of pedestrians, as well as proper ways to couple computational fluid dynamics and computational crowd dynamics to enable high-fidelity pathogen transmission and infection simulations is treated. The present review shows that high-fidelity simulations of pathogen propagation, transmission and mitigation in the built environment have reached a high degree of sophistication, offering a quantum leap in accuracy from simpler probabilistic models. This is particularly the case when considering the propagation of pathogens via aerosols in the presence of moving pedestrians.

A Multiscale Approach for the Numerical Simulation of Turbulent Flows with Droplets.

A multiscale approach for the detailed simulation of water droplets dispersed in a turbulent airflow is presented. The multiscale procedure combines a novel representative volume element (RVE) with the Pseudo Direct Numerical Simulation (P-DNS) method. The solution at the coarse-scale relies on a synthetic model, constructed using precomputed offline RVE simulations and an alternating digital tree, to characterize the non-linear dynamic response at the fine-scale. A set of numerical experiments for a wide range of volume fractions, particle distribution sizes, and external shear forces in the RVE are carried out. Quantitative results of the statistically stationary turbulent state are obtained, and the turbulence modulation phenomenon due to the presence of droplets is discussed. The developed synthetic model is then employed to solve global scale simulations of flows with airborne droplets via the P-DNS method. Improved predictions are obtained for flow conditions where turbulence modulation is noticeable.

High fidelity modeling of aerosol pathogen propagation in built environments with moving pedestrians.

A high fidelity model for the propagation of pathogens via aerosols in the presence of moving pedestrians is proposed. The key idea is the tight coupling of computational fluid dynamics and computational crowd dynamics in order to capture the emission, transport and inhalation of pathogen loads in space and time. An example simulating pathogen propagation in a narrow corridor with moving pedestrians clearly shows the considerable effect that pedestrian motion has on airflow, and hence on pathogen propagation and potential infectivity.

Detailed simulation of viral propagation in the built environment.

A summary is given of the mechanical characteristics of virus contaminants and the transmission via droplets and aerosols. The ordinary and partial differential equations describing the physics of these processes with high fidelity are presented, as well as appropriate numerical schemes to solve them. Several examples taken from recent evaluations of the built environment are shown, as well as the optimal placement of sensors.

Mechanisms Involved in the Formation of Biocompatible Lipid Polymeric Hollow Patchy Particles.

Patchy polymeric particles have anisotropic surface domains that can be remarkably useful in diverse medical and industrial fields because of their ability to simultaneously present two different surface chemistries on the same construct. In this article, we report the mechanisms involved in the formation of novel lipid-polymeric hollow patchy particles during their synthesis. By cross-sectioning the patchy particles, we found that a phase segregation phenomenon occurs between the core, shell, and patch. Importantly, we found that the shear stress that the polymer blend undergoes during the particle synthesis is the most important parameter for the formation of these patchy particles. In addition, we found that the interplay of solvent-solvent, polymer-solvent, and polymer-polymer-solvent interactions generates particles with different surface morphologies. Understanding the mechanisms involved in the formation of patchy particles allows us to have a better control on their physicochemical properties. Therefore, these fundamental studies are critical to achieve batch control and scalability, which are essential aspects that must be addressed in any type of particle synthesis to be safely used in medicine.

Computational Hemodynamics Framework for the Analysis of Cerebral Aneurysms.

Assessing the risk of rupture of intracranial aneurysms is important for clinicians because the natural rupture risk can be exceeded by the small but significant risk carried by current treatments. To this end numerous investigators have used image-based computational fluid dynamics models to extract patient-specific hemodynamics information, but there is no consensus on which variables or hemodynamic characteristics are the most important. This paper describes a computational framework to study and characterize the hemodynamic environment of cerebral aneurysms in order to relate it to clinical events such as growth or rupture. In particular, a number of hemodynamic quantities are proposed to describe the most salient features of these hemodynamic environments. Application to a patient population indicates that ruptured aneurysms tend to have concentrated inflows, concentrated wall shear stress distributions, high maximal wall shear stress and smaller viscous dissipation ratios than unruptured aneurysms. Furthermore, these statistical associations are largely unaffected by the choice of physiologic flow conditions. This confirms the notion that hemodynamic information derived from image-based computational models can be used to assess aneurysm rupture risk, to test hypotheses about the mechanisms responsible for aneurysm formation, progression and rupture, and to answer specific clinical questions.

Fast Numerical Solutions of Patient-Specific Blood Flows in 3D Arterial Systems.

The study of hemodynamics in arterial models constructed from patient-specific medical images requires the solution of the incompressible flow equations in geometries characterized by complex branching tubular structures. The main challenge with this kind of geometries is that the convergence rate of the pressure Poisson solver is dominated by the graph depth of the computational grid. This paper presents a deflated preconditioned conjugate gradients (DPCG) algorithm for accelerating the pressure Poisson solver. A subspace deflation technique is used to approximate the lowest eigenvalues along tubular domains. This methodology was tested with an idealized cylindrical model and three patient-specific models of cerebral arteries and aneurysms constructed from medical images. For these cases, the number of iterations decreased by up to a factor of 16, while the total CPU time was reduced by up to 4 times when compared with the standard PCG solver.

Hemodynamic Analysis of Intracranial Aneurysms with Moving Parent Arteries: Basilar Tip Aneurysms.

The effects of parent artery motion on the hemodynamics of basilar tip saccular aneurysms and its potential effect on aneurysm rupture were studied.The aneurysm and parent artery motions in two patients were determined from cine loops of dynamic angiographies. The oscillatory motion amplitude was quantified by registering the frames. Patient-specific computational fluid dynamics (CFD) models of both aneurysms were constructed from 3D rotational angiography images. Two CFD calculations were performed for each patient, corresponding to static and moving models. The motion estimated from the dynamic images was used to move the surface grid points in the moving model. Visualizations from the simulations were compared for wall shear stress (WSS), velocity profiles, and streamlines.In both patients a rigid oscillation of the aneurysm and basilar artery in the anterio-posterior direction was observed and measured. The distribution of WSS was nearly identical between the models of each patient, as well as major intra-aneurysmal flow structures, inflow jets, and regions of impingement.The motion observed in pulsating intracranial vasculature does not have a major impact on intra-aneurysmal hemodynamic variables. Parent artery motion is unlikely to be a risk factor for increased risk of aneurysmal rupture.

Efficient simulation of blood flow past complex endovascular devices using an adaptive embedding technique.

The simulation of blood flow past endovascular devices such as coils and stents is a challenging problem due to the complex geometry of the devices. Traditional unstructured grid computational fluid dynamics relies on the generation of finite element grids that conform to the boundary of the computational domain. However, the generation of such grids for patient-specific modeling of cerebral aneurysm treatment with coils or stents is extremely difficult and time consuming. This paper describes the application of an adaptive grid embedding technique previously developed for complex fluid structure interaction problems to the simulation of endovascular devices. A hybrid approach is used: the vessel walls are treated with body conforming grids and the endovascular devices with an adaptive mesh embedding technique. This methodology fits naturally in the framework of image-based computational fluid dynamics and opens the door for exploration of different therapeutic options and personalization of endovascular procedures.

Blood flow modeling in carotid arteries with computational fluid dynamics and MR imaging.

RATIONALE AND OBJECTIVES: The authors' goal was to develop a noninvasive method for detailed assessment of blood flow patterns from direct in vivo measurements of vessel anatomy and flow rates. MATERIALS AND METHODS: The authors developed a method to construct realistic patient-specific finite element models of blood flow in carotid arteries. Anatomic models are reconstructed from contrast material-enhanced magnetic resonance (MR) angiographic images with a tubular deformable model along each arterial branch. A surface-merging algorithm is used to create a watertight model of the carotid bifurcation for subsequent finite element grid generation, and a fully implicit scheme is used to solve the incompressible Navier-Stokes equations on unstructured grids. Physiologic boundary conditions are derived from cine phase-contrast MR flow velocity measurements at two locations below and above the bifurcation. Vessel wall compliance is incorporated by means of fluid-solid interaction algorithms. RESULTS: The method was tested on imaging data from a healthy subject and a patient with mild stenosis. Finite element grids were successfully generated, and pulsatile blood flow calculations were performed. Computed and measured velocity profiles show good agreement. Flow patterns and wall shear stress distributions were visualized. CONCLUSIONS: Patient-specific computational fluid dynamics modeling based on MR images can be performed robustly and efficiently. Preliminary validation studies in a physical flow-through model suggest that the model is accurate. This method can be used to characterize blood flow patterns in healthy and diseased arteries and may eventually help physicians to supplement imaging-based diagnosis and predict and evaluate the outcome of interventional procedures.

Fluid dynamics of flapping aquatic flight in the bird wrasse: three-dimensional unsteady computations with fin deformation.

Many fishes that swim with the paired pectoral fins use fin-stroke parameters that produce thrust force from lift in a mechanism of underwater flight. These locomotor mechanisms are of interest to behavioral biologists, biomechanics researchers and engineers. In the present study, we performed the first three-dimensional unsteady computations of fish swimming with oscillating and deforming fins. The objective of these computations was to investigate the fluid dynamics of force production associated with the flapping aquatic flight of the bird wrasse Gomphosus varius. For this computational work, we used the geometry of the wrasse and its pectoral fin, and previously measured fin kinematics, as the starting points for computational investigation of three-dimensional (3-D) unsteady fluid dynamics. We performed a 3-D steady computation and a complete set of 3-D quasisteady computations for a range of pectoral fin positions and surface velocities. An unstructured, grid-based, unsteady Navier-Stokes solver with automatic adaptive remeshing was then used to compute the unsteady flow about the wrasse through several complete cycles of pectoral fin oscillation. The shape deformation of the pectoral fin throughout the oscillation was taken from the experimental kinematics. The pressure distribution on the body of the bird wrasse and its pectoral fins was computed and integrated to give body and fin forces which were decomposed into lift and thrust. The velocity field variation on the surface of the wrasse body, on the pectoral fins and in the near-wake was computed throughout the swimming cycle. We compared our computational results for the steady, quasi-steady and unsteady cases with the experimental data on axial and vertical acceleration obtained from the pectoral fin kinematics experiments. These comparisons show that steady state computations are incapable of describing the fluid dynamics of flapping fins. Quasi-steady state computations, with correct incorporation of the experimental kinematics, are useful when determining trends in force production, but do not provide accurate estimates of the magnitudes of the forces produced. By contrast, unsteady computations about the deforming pectoral fins using experimentally measured fin kinematics were found to give excellent agreement, both in the time history of force production throughout the flapping strokes and in the magnitudes of the generated forces.