An investigation of damage mechanisms in mechanobiological models of in-stent restenosis

Nolan, David; Lally, Caitríona

doi:10.1016/j.jocs.2017.04.009

Cited by 44 publications

(52 citation statements)

References 44 publications

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“…A large stream of works on multiscale modeling of vascular adaptation, especially after stenting in arteries, has been so far developed, and it is available from the literature (Nolan and Lally 2018 ; Boyle et al. 2010 ; Zahedmanesh and Lally 2011 ; Zun et al.…”

Section: Discussionmentioning

confidence: 99%

A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation

Garbey

Casarin

Berceli

2018

Biomech Model Mechanobiol

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Peripheral arterial occlusive disease is a chronic pathology affecting at least 8-12 million people in the USA, typically treated with a vein graft bypass or through the deployment of a stent in order to restore the physiological circulation. Failure of peripheral endovascular interventions occurs at the intersection of vascular biology, biomechanics, and clinical decision making. It is our hypothesis that the majority of endovascular treatment approaches share the same driving mechanisms and that a deep understanding of the adaptation process is pivotal in order to improve the current outcome of the procedure. The postsurgical adaptation of vein graft bypasses offers the perfect example of how the balance between intimal hyperplasia and wall remodeling determines the failure or the success of the intervention. Accordingly, this work presents a versatile computational model able to capture the feedback loop that describes the interaction between events at cellular/tissue level and mechano-environmental conditions. The work here presented is a generalization and an improvement of a previous work by our group of investigators, where an agent-based model uses a cellular automata principle on a fixed hexagonal grid to reproduce the leading events of the graft's restenosis. The new hybrid model here presented allows a more realistic simulation both of the biological laws that drive the cellular behavior and of the active role of the membranes that separate the various layers of the vein. The novel feature is to use an immersed boundary implementation of a highly viscous flow to represent SMC motility and matrix reorganization in response to graft adaptation. Our implementation is modular, and this makes us able to choose the right compromise between closeness to the physiological reality and complexity of the model. The focus of this paper is to offer a new modular implementation that combines the best features of an agent-based model, continuum mechanics, and particle-tracking methods to cope with the multiscale nature of the adaptation phenomena. This hybrid method allows us to quickly test various hypotheses with a particular attention to cellular motility, a process that we demonstrated should be driven by mechanical homeostasis in order to maintain the right balance between cells and extracellular matrix in order to reproduce a distribution similar to histological experimental data from vein grafts.

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Section: Discussionmentioning

confidence: 99%

A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation

Garbey

Casarin

Berceli

2018

Biomech Model Mechanobiol

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“…The authors demonstrate that incorrect use of isochoric anisotropic invariants can generate dramatic errors, even for cases of near-incompressible materials. Even though anisotropic hyperelastic models have been used for a wide range of diverse biomechanical applications [12][13][14][15][16][17][18][19], no previous study, to the best of the authors' knowledge, has investigated the behavior of notches in anisotropic hyperelastic skin type materials. The need for such an analysis is further motivated by the experimental study by Yang et al [20] of edge cracks in skin composed of collagen fiber and elastin.…”

Section: Introductionmentioning

confidence: 99%

The influence of fibre alignment on the fracture toughness of anisotropic soft tissue

Baranwal

Agnihotri

McGarry

2020

Engineering Fracture Mechanics

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Finite element (FE) simulations are performed to investigate the effect of fiber induced anisotropy on the notch behavior in hyperelastic skin type materials. The modified anisotropic (MA) model is used to define the constitutive behavior in FE simulations through Abaqus user defined material model UMAT. A parametric study is carried out to examine the effect of fiber orientation, notch root radius and sample geometry on the stress field ahead of the notch tip. A non-dimensional parameter  is defined to characterize the combined effect of J energy and average anisotropic energy (aniso)avg on the notch behavior. It is shown that fibre orientation significantly influences the stress state and J-integral at the notch. The findings of the present study will be helpful in determining optimal constitution and orientation of skin grafts at locations of high stress and complex geometries, such as corner of eyes and lips etc.

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“…20), as well as in various in vivo (reviewed in Ref. 22), in vitro 3,19 and in silico 5,6,16,30,35,41,48,55 – 57 models. Computational models of ISR usually represent cells by on-lattice or freely moving agents, but continuum-based models have also been proposed.…”

Section: Introductionmentioning

confidence: 99%

Location-Specific Comparison Between a 3D In-Stent Restenosis Model and Micro-CT and Histology Data from Porcine In Vivo Experiments

Zun

Narracott

Chiastra

et al. 2019

Cardiovasc Eng Tech

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BackgroundCoronary 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.MethodsThis 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.ResultsMetrics 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.ConclusionsThe 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.Electronic supplementary materialThe online version of this article (10.1007/s13239-019-00431-4) contains supplementary material, which is available to authorized users.

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An investigation of damage mechanisms in mechanobiological models of in-stent restenosis

Cited by 44 publications

References 44 publications

A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation

A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation

The influence of fibre alignment on the fracture toughness of anisotropic soft tissue

Location-Specific Comparison Between a 3D In-Stent Restenosis Model and Micro-CT and Histology Data from Porcine In Vivo Experiments

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