30 research outputs found
Location-Specific Comparison Between a 3D In-Stent Restenosis Model and Micro-CT and Histology Data from Porcine <em>In Vivo</em> Experiments
A 1D pulse wave propagation model of the hemodynamics of calf muscle pump function
The calf muscle pump is a mechanism which increases venous return and thereby compensates for the fluid shift towards the lower body during standing. During a muscle contraction, the embedded deep veins collapse and venous return increases. In the subsequent relaxation phase, muscle perfusion increases due to increased perfusion pressure, as the proximal venous valves temporarily reduce the distal venous pressure (shielding). The superficial and deep veins are connected via perforators, which contain valves allowing flow in the superficial-to-deep direction. The aim of this study is to investigate and quantify the physiological mechanisms of the calf muscle pump, including the effect of venous valves, hydrostatic pressure, and the superficial venous system. Using a one-dimensional pulse wave propagation model, a muscle contraction is simulated by increasing the extravascular pressure in the deep venous segments. The hemodynamics are studied in three different configurations: a single artery–vein configuration with and without valves and a more detailed configuration including a superficial vein. Proximal venous valves increase effective venous return by 53% by preventing reflux. Furthermore, the proximal valves shielding function increases perfusion following contraction. Finally, the superficial system aids in maintaining the perfusion during the contraction phase and reduces the refilling time by 37%
Location-specific comparison between a 3D in-stent restenosis model and micro-CT and histology data from porcine in vivo experiments
Background
Coronary artery restenosis is an important side effect of percutaneous coronary intervention. Computational models can be used to better understand this process. We report on an approach for validation of an in silico 3D model of in-stent restenosis in porcine coronary arteries and illustrate this approach by comparing the modelling results to in vivo data for 14 and 28 days post-stenting.
Methods
This multiscale model includes single-scale models for stent deployment, blood flow and tissue growth in the stented vessel, including smooth muscle cell (SMC) proliferation and extracellular matrix (ECM) production. The validation procedure uses data from porcine in vivo experiments, by simulating stent deployment using stent geometry obtained from micro computed tomography (micro-CT) of the stented vessel and directly comparing the simulation results of neointimal growth to histological sections taken at the same locations.
Results
Metrics for comparison are per-strut neointimal thickness and per-section neointimal area. The neointimal area predicted by the model demonstrates a good agreement with the detailed experimental data. For 14 days post-stenting the relative neointimal area, averaged over all vessel sections considered, was 20 ± 3% in vivo and 22 ± 4% in silico. For 28 days, the area was 42 ± 3% in vivo and 41 ± 3% in silico.
Conclusions
The approach presented here provides a very detailed, location-specific, validation methodology for in silico restenosis models. The model was able to closely match both histology datasets with a single set of parameters. Good agreement was obtained for both the overall amount of neointima produced and the local distribution. It should be noted that including vessel curvature and ECM production in the model was paramount to obtain a good agreement with the experimental data
A particle-based model for endothelial cell migration under flow conditions
Endothelial cells (ECs) play a major role in the healing process following angioplasty to inhibit excessive neointima. This makes the process of EC healing after injury, in particular EC migration in a stented vessel, important for recovery of normal vessel function. In that context, we present a novel particle-based model of EC migration and validate it against in vitro experimental data. We have developed a particle-based model of EC migration under flow conditions in an in vitro vessel with obstacles. Cell movement in the model is a combination of random walks and directed movement along the local flow velocity vector. For model calibration, a set of experimental data for cell migration in a similarly shaped channel has been used. We have calibrated the model for a baseline case of a channel with no obstacles and then applied it to the case of a channel with ridges on the bottom surface, representative of stent strut geometry. We were able to closely reproduce the cell migration speed and angular distribution of their movement relative to the flow direction reported in vitro. The model also reproduces qualitative aspects of EC migration, such as entrapment of cells downstream from the flow-disturbing ridge. The model has the potential, after more extensive in vitro validation, to study the effect of variation in strut spacing and shape, through modification of the local flow, on EC migration. The results of this study support the hypothesis that EC migration is strongly affected by the direction and magnitude of local wall shear stress
Adaptation and development of software simulation methodologies for cardiovascular engineering: present and future challenges from an end-user perspective
This paper describes the use of diverse software tools in cardiovascular applications. These tools were primarily developed in the field of engineering and the applications presented push the boundaries of the software to address events related to venous and arterial valve closure, exploration of dynamic boundary conditions or the inclusion of multi-scale boundary conditions from protein to organ levels. The future of cardiovascular research and the challenges that modellers and clinicians face from validation to clinical uptake are discussed from an end-user perspective
The Ring Vortex: Concepts for a Novel Complex Flow Phantom for Medical Imaging
Calibration of medical imaging systems that provide quantitative measures relating to complex physiological flows is challenging. Physical test objects available for the purpose either offer a known simple flow far removed from the complexity of pathology (e.g. parabolic flow in a straight pipe) or complex
relevant flows in which the details of the flow behaviour are unknown. This paper presents the ring vortex as a candidate for a complex flow phantom, since it is marked by inherently complex flow features that are controllable, predictable, reproducible and stable. These characteristics are demonstrated by a combination of analytical, numerical (CFD) and experimental methods. Together they provide a consistent perspective on ring vortex behaviour and highlight qualities relevant to phantom design. Discussion of the results indicates that a liquid phantom based on the ring vortex may have merit as a complex flow phantom for multimodal imaging. Furthermore, availability of such a flow reference may also serve as a benchmark for quality assurance of simulation methodologies
Full-field analysis of epicardial strain in an in vitro porcine heart platform.
The quantitative assessment of cardiac strain is increasingly performed to provide valuable insights on heart function. Currently, the most frequently used technique in the clinic is ultrasound-based speckle tracking echocardiography (STE). However, verification and validation of this modality are still under investigation and further reference measurements are required to support this activity. The aim of this work was to enable these reference measurements using a dynamic beating heart simulator to ensure reproducible, controlled, and realistic haemodynamic conditions and to validate the reliability of optical-based three-dimensional digital image correlation (3D-DIC) for a dynamic full-field analysis of epicardial strain. Specifically, performance assessment of 3D-DIC was carried out by evaluating the accuracy and repeatability of the strain measurements across multiple cardiac cycles in a single heart and between five hearts. Moreover, the ability of this optical method to differentiate strain variations when different haemodynamic conditions were imposed in the same heart was examined. Strain measurements were successfully accomplished in a region of the lateral left ventricle surface. Results were highly repeatable over heartbeats and across hearts (intraclass correlation coefficient = 0.99), whilst strain magnitude was significantly different between hearts, due to change in anatomy and wall thickness. Within an individual heart, strain variations between different haemodynamic scenarios were greater than the estimated error of the measurement technique. This study demonstrated the feasibility of applying 3D-DIC in a dynamic passive heart simulator. Most importantly, non-contact measurements were obtained at a high spatial resolution (~ 1.5 mm) allowing resolution of local variation of strain on the epicardial surface during ventricular filling. The experimental framework developed in this paper provides detailed measurement of cardiac strains under controlled conditions, as a reference for validation of clinical cardiac strain imaging modalities
Location-Specific Comparison Between a 3D In-Stent Restenosis Model and Micro-CT and Histology Data from Porcine In Vivo Experiments
Background: Coronary artery restenosis is an important side effect of percutaneous coronary intervention. Computational models can be used to better understand this process. We report on an approach for validation of an in silico 3D model of in-stent restenosis in porcine coronary arteries and illustrate this approach by comparing the modelling results to in vivo data for 14 and 28 days post-stenting. Methods: This multiscale model includes single-scale models for stent deployment, blood flow and tissue growth in the stented vessel, including smooth muscle cell (SMC) proliferation and extracellular matrix (ECM) production. The validation procedure uses data from porcine in vivo experiments, by simulating stent deployment using stent geometry obtained from micro computed tomography (micro-CT) of the stented vessel and directly comparing the simulation results of neointimal growth to histological sections taken at the same locations. Results: Metrics for comparison are per-strut neointimal thickness and per-section neointimal area. The neointimal area predicted by t
Location-Specific Comparison Between a 3D In-Stent Restenosis Model and Micro-CT and Histology Data from Porcine In Vivo Experiments
Background: Coronary artery restenosis is an important side effect of percutaneous coronary intervention. Computational models can be used to better understand this process. We report on an approach for validation of an in silico 3D model of in-stent restenosis in porcine coronary arteries and illustrate this approach by comparing the modelling results to in vivo data for 14 and 28 days post-stenting. Methods: This multiscale model includes single-scale models for stent deployment, blood flow and tissue growth in the stented vessel, including smooth muscle cell (SMC) proliferation and extracellular matrix (ECM) production. The validation procedure uses data from porcine in vivo experiments, by simulating stent deployment using stent geometry obtained from micro computed tomography (micro-CT) of the stented vessel and directly comparing the simulation results of neointimal growth to histological sections taken at the same locations. Results: Metrics for comparison are per-strut neointimal thickness and per-section neointimal area. The neointimal area predicted by t