A Rapid and Computationally Inexpensive Method to Virtually Implant Current and Next-Generation Stents into Subject-Specific Computational Fluid Dynamics Models

Computational modeling is often used to quantify hemodynamic alterations induced by stenting, but frequently uses simplified device or vascular representations. Based on a series of Boolean operations, we developed an efficient and robust method for assessing the influence of current and next-generation stents on local hemodynamics and vascular biomechanics quantified by computational fluid dynamics. Stent designs were parameterized to allow easy control over design features including the number, width and circumferential or longitudinal spacing of struts, as well as the implantation diameter and overall length. The approach allowed stents to be automatically regenerated for rapid analysis of the contribution of design features to resulting hemodynamic alterations. The applicability of the method was demonstrated with patient-specific models of a stented coronary artery bifurcation and basilar trunk aneurysm constructed from medical imaging data. In the coronary bifurcation, we analyzed the hemodynamic difference between closed-cell and open-cell stent geometries. We investigated the impact of decreased strut size in stents with a constant porosity for increasing flow stasis within the stented basilar aneurysm model. These examples demonstrate the current method can be used to investigate differences in stent performance in complex vascular beds for a variety of stenting procedures and clinical scenarios

Microfocal X-Ray Computed Tomography Post-Processing Operations for Optimizing Reconstruction Volumes of Stented Arteries During 3D Computational Fluid Dynamics Modeling

Restenosis caused by neointimal hyperplasia (NH) remains an important clinical problem after stent implantation. Restenosis varies with stent geometry, and idealized computational fluid dynamics (CFD) models have indicated that geometric properties of the implanted stent may differentially influence NH. However, 3D studies capturing the in vivo flow domain within stented vessels have not been conducted at a resolution sufficient to detect subtle alterations in vascular geometry caused by the stent and the subsequent temporal development of NH. We present the details and limitations of a series of post-processing operations used in conjunction with microfocal X-ray CT imaging and reconstruction to generate geometrically accurate flow domains within the localized region of a stent several weeks after implantation. Microfocal X-ray CT reconstruction volumes were subjected to an automated program to perform arterial thresholding, spatial orientation, and surface smoothing of stented and unstented rabbit iliac arteries several weeks after antegrade implantation. A transfer function was obtained for the current post-processing methodology containing reconstructed 16 mm stents implanted into rabbit iliac arteries for up to 21 days after implantation and resolved at circumferential and axial resolutions of 32 and 50 μm, respectively. The results indicate that the techniques presented are sufficient to resolve distributions of WSS with 80% accuracy in segments containing 16 surface perturbations over a 16 mm stented region. These methods will be used to test the hypothesis that reductions in normalized wall shear stress (WSS) and increases in the spatial disparity of WSS immediately after stent implantation may spatially correlate with the temporal development of NH within the stented region

Identification of Hemodynamically Optimal Coronary Stent Designs Based on Vessel Caliber

Coronary stent design influences local patterns of wall shear stress (WSS) that are associated with neointimal growth, restenosis, and the endothelialization of stent struts. The number of circumferentially repeating crowns NC for a given stent de- sign is often modified depending on the target vessel caliber, but the hemodynamic implications of altering NC have not previously been studied. In this investigation, we analyzed the relationship between vessel diameter and the hemodynamically optimal NC using a derivative-free optimization algorithm coupled with computational fluid dynamics. The algorithm computed the optimal vessel diameter, defined as minimizing the area of stent-induced low WSS, for various configurations (i.e., NC) of a generic slotted-tube design and designs that resemble commercially available stents. Stents were modeled in idealized coronary arteries with a vessel diameter that was allowed to vary between 2 and 5 mm. The results indicate that the optimal vessel diameter increases for stent configurations with greater NC, and the designs of current commercial stents incorporate a greater NC than hemodynamically optimal stent designs. This finding suggests that reducing the NC of current stents may improve the hemodynamic environment within stented arteries and reduce the likelihood of excessive neointimal growth and thrombus formation

Immersive Visualization for Enhanced Computational Fluid Dynamics Analysis

Modern biomedical computer simulations produce spatiotemporal results that are often viewed at a single point in time on standard 2D displays. An immersive visualization environment (IVE) with 3D stereoscopic capability can mitigate some shortcomings of 2D displays via improved depth cues and active movement to further appreciate the spatial localization of imaging data with temporal computational fluid dynamics (CFD) results. We present a semi-automatic workflow for the import, processing, rendering, and stereoscopic visualization of high resolution, patient-specific imaging data, and CFD results in an IVE. Versatility of the workflow is highlighted with current clinical sequelae known to be influenced by adverse hemodynamics to illustrate potential clinical utility

Quantification of Local Hemodynamic Alterations Caused by Virtual Implantation of Three Commercially Available Stents for the Treatment of Aortic Coarctation

Patients with coarctation of the aorta (CoA) are prone to morbidity including atherosclerotic plaque that has been shown to correlate with altered wall shear stress (WSS) in the descending thoracic aorta (dAo). We created the first patient-specific computational fluid dynamics (CFD) model of a CoA patient treated by Palmaz stenting to date, and compared resulting WSS distributions to those from virtual implantation of Genesis XD and modified NuMED CP stents, also commonly used for CoA. CFD models were created from magnetic resonance imaging, fluoroscopy and blood pressure data. Simulations incorporated vessel deformation, downstream vascular resistance and compliance to match measured data and generate blood flow velocity and time-averaged WSS (TAWSS) results. TAWSS was quantified longitudinally and circumferentially in the stented region and dAo. While modest differences were seen in the distal portion of the stented region, marked differences were observed downstream along the posterior dAo and depended on stent type. The Genesis XD model had the least area of TAWSS values exceeding the threshold for platelet aggregation in vitro, followed by the Palmaz and NuMED CP stents. Alterations in local blood flow patterns and WSS imparted on the dAo appear to depend on the type of stent implanted for CoA. Following confirmation in larger studies, these findings may aid pediatric interventional cardiologists in selecting the most appropriate stent for each patient, and ultimately reduce long-term morbidity following treatment for CoA by stenting

Improving Cardiovascular Stent Design Using Patient-Specific Models and Shape Optimization

Stent geometry influences local hemodynamic alterations (i.e. the forces moving blood through the cardiovascular system) associated with adverse clinical outcomes. Computational fluid dynamics (CFD) is frequently used to quantify stent-induced hemodynamic disturbances, but previous CFD studies have relied on simplified device or vascular representations. Additionally, efforts to minimize stent-induced hemodynamic disturbances using CFD models often only compare a small number of possible stent geometries. This thesis describes methods for modeling commercial stents in patient-specific vessels along with computational techniques for determining optimal stent geometries that address the limitations of previous studies. An efficient and robust method was developed for virtually implanting stent models into patient-specific vascular geometries derived from medical imaging data. Models of commercial stent designs were parameterized to allow easy control over design features. Stent models were then virtually implanted into vessel geometries using a series of Boolean operations. This approach allowed stented vessel models to be automatically regenerated for rapid analysis of the contribution of design features to resulting hemodynamic alterations. The applicability of the method was demonstrated with patient-specific models of a stented coronary artery bifurcation and basilar trunk aneurysm to reveal how it can be used to investigate differences in hemodynamic performance in complex vascular beds for a variety of clinical scenarios. To identify hemodynamically optimal stents designs, a computational framework was constructed to couple CFD with a derivative-free optimization algorithm. The optimization algorithm was fully-automated such that solid model construction, mesh generation, CFD simulation and time-averaged wall shear stress (TAWSS) quantification did not require user intervention. The method was applied to determine the optimal number of circumferentially repeating stent cells (NC) for a slotted-tube stents and various commercial stents. Optimal stent designs were defined as those minimizing the area of low TAWSS. It was determined the optimal value of NC is dependent on the intrastrut angle with respect to the primary flow direction. Additionally, the geometries of current commercial stents were found to generally incorporate a greater NC than is hemodynamically optimal. The application of the virtual stent implantation and optimization methods may lead to stents with superior hemodynamic performance and the potential for improved clinical outcomes. Future in vivo studies are needed to validate the findings of the computational results obtained from the methods developed in this thesis

Comparison and calibration of a real-time virtual stenting algorithm using Finite Element Analysis and Genetic Algorithms

In this paper, we perform a comparative analysis between two computational methods for virtual stent deployment: a novel fast virtual stenting method, which is based on a spring–mass model, is compared with detailed finite element analysis in a sequence of in silico experiments. Given the results of the initial comparison, we present a way to optimise the fast method by calibrating a set of parameters with the help of a genetic algorithm, which utilises the outcomes of the finite element analysis as a learning reference. As a result of the calibration phase, we were able to substantially reduce the force measure discrepancy between the two methods and validate the fast stenting method by assessing the differences in the final device configurations

Shear-promoted drug encapsulation into red blood cells: a CFD model and μ-PIV analysis

The present work focuses on the main parameters that influence shear-promoted encapsulation of drugs into erythrocytes. A CFD model was built to investigate the fluid dynamics of a suspension of particles flowing in a commercial micro channel. Micro Particle Image Velocimetry (μ-PIV) allowed to take into account for the real properties of the red blood cell (RBC), thus having a deeper understanding of the process. Coupling these results with an analytical diffusion model, suitable working conditions were defined for different values of haematocrit