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Nikishova A, Veen L, Zun P, Hoekstra AG. Uncertainty Quantification of a Multiscale Model for In-Stent Restenosis. Cardiovasc Eng Technol 2018; 9:761-774. [PMID: 30136082 PMCID: PMC6290695 DOI: 10.1007/s13239-018-00372-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Accepted: 08/09/2018] [Indexed: 12/11/2022]
Abstract
Purpose Coronary artery stenosis, or abnormal narrowing, is a widespread and potentially fatal cardiac disease. After treatment by balloon angioplasty and stenting, restenosis may occur inside the stent due to excessive neointima formation. Simulations of in-stent restenosis can provide new insight into this process. However, uncertainties due to variability in patient-specific parameters must be taken into account. Methods We performed an uncertainty quantification (UQ) study on a complex two-dimensional in-stent restenosis model. We used a quasi-Monte Carlo method for UQ of the neointimal area, and the Sobol sensitivity analysis (SA) to estimate the proportions of aleatory and epistemic uncertainties and to determine the most important input parameters. Results We observe approximately 30% uncertainty in the mean neointimal area as simulated by the model. Depending on whether a fast initial endothelium recovery occurs, the proportion of the model variance due to natural variability ranges from 15 to 35%. The endothelium regeneration time is identified as the most influential model parameter. Conclusion The model output contains a moderate quantity of uncertainty, and the model precision can be increased by obtaining a more certain value on the endothelium regeneration time. We conclude that the quasi-Monte Carlo UQ and the Sobol SA are reliable methods for estimating uncertainties in the response of complicated multiscale cardiovascular models.
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Affiliation(s)
- Anna Nikishova
- Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands.
| | - Lourens Veen
- Netherlands eScience Center, Amsterdam, The Netherlands
| | - Pavel Zun
- Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands.,ITMO University, Saint Petersburg, Russia
| | - Alfons G Hoekstra
- Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands.,ITMO University, Saint Petersburg, Russia
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Garbey M, Casarin S, Berceli SA. A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation. Biomech Model Mechanobiol 2018; 18:29-44. [PMID: 30094656 PMCID: PMC6373284 DOI: 10.1007/s10237-018-1065-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 07/26/2018] [Indexed: 11/27/2022]
Abstract
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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Affiliation(s)
- Marc Garbey
- Houston Methodist Research Institute, Houston, TX, USA. .,Department of Surgery, Houston Methodist Hospital, Houston, TX, USA. .,LaSIE, UMR CNRS 7356, University of la Rochelle, La Rochelle, France.
| | - Stefano Casarin
- Houston Methodist Research Institute, Houston, TX, USA.,LaSIE, UMR CNRS 7356, University of la Rochelle, La Rochelle, France
| | - Scott A Berceli
- Department of Surgery, University of Florida, Gainesville, FL, USA.,Malcom Randall VAMC, Gainesville, FL, USA
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Melnikova NB, Svitenkov AI, Hose DR, Hoekstra AG. A cell-based mechanical model of coronary artery tunica media. J R Soc Interface 2018; 14:rsif.2017.0028. [PMID: 28679664 DOI: 10.1098/rsif.2017.0028] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 06/05/2017] [Indexed: 12/23/2022] Open
Abstract
A three-dimensional cell-based mechanical model of coronary artery tunica media is proposed. The model is composed of spherical cells forming a hexagonal close-packed lattice. Tissue anisotropy is taken into account by varying interaction forces with the direction of intercellular connection. Several cell-centre interaction potentials for repulsion and attraction are considered, including the Hertz contact model and its neo-Hookean extension, the Johnson-Kendall-Roberts model of adhesive contact, and a wormlike chain model. The model is validated against data from in vitro uni-axial tension tests performed on dissected strips of tunica media. The wormlike chain potential in combination with the neo-Hookean Hertz contact model produces stress-stretch curves which represent the experimental data very well.
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Affiliation(s)
- N B Melnikova
- Saint Petersburg National Research University of Information Technologies, Mechanics and Optics, Saint Petersburg, Russia .,Peter the Great State Polytechnic University, Saint Petersburg, Russia
| | - A I Svitenkov
- Saint Petersburg National Research University of Information Technologies, Mechanics and Optics, Saint Petersburg, Russia
| | - D R Hose
- University of Sheffield, Sheffield, UK
| | - A G Hoekstra
- Saint Petersburg National Research University of Information Technologies, Mechanics and Optics, Saint Petersburg, Russia.,University of Amsterdam, Amsterdam, The Netherlands
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Zun PS, Anikina T, Svitenkov A, Hoekstra AG. A Comparison of Fully-Coupled 3D In-Stent Restenosis Simulations to In-vivo Data. Front Physiol 2017; 8:284. [PMID: 28588498 PMCID: PMC5440556 DOI: 10.3389/fphys.2017.00284] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Accepted: 04/19/2017] [Indexed: 01/05/2023] Open
Abstract
We describe our fully-coupled 3D multiscale model of in-stent restenosis, with blood flow simulations coupled to smooth muscle cell proliferation, and report results of numerical simulations performed with this model. This novel model is based on several previously reported 2D models. We study the effects of various parameters on the process of restenosis and compare with in vivo porcine data where we observe good qualitative agreement. We study the effects of stent deployment depth (and related injury score), reendothelization speed, and simulate the effect of stent width. Also we demonstrate that we are now capable to simulate restenosis in real-sized (18 mm long, 2.8 mm wide) vessel geometries.
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Affiliation(s)
- Pavel S. Zun
- Saint Petersburg State University of Information Technologies, Mechanics and Optics (ITMO) UniversitySt. Petersburg, Russia
- Computational Science Lab, Faculty of Science, Institute for Informatics, University of AmsterdamAmsterdam, Netherlands
| | - Tatiana Anikina
- Saint Petersburg State University of Information Technologies, Mechanics and Optics (ITMO) UniversitySt. Petersburg, Russia
- Computational Science Lab, Faculty of Science, Institute for Informatics, University of AmsterdamAmsterdam, Netherlands
| | - Andrew Svitenkov
- Saint Petersburg State University of Information Technologies, Mechanics and Optics (ITMO) UniversitySt. Petersburg, Russia
| | - Alfons G. Hoekstra
- Saint Petersburg State University of Information Technologies, Mechanics and Optics (ITMO) UniversitySt. Petersburg, Russia
- Computational Science Lab, Faculty of Science, Institute for Informatics, University of AmsterdamAmsterdam, Netherlands
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Hoekstra AG, Alowayyed S, Lorenz E, Melnikova N, Mountrakis L, van Rooij B, Svitenkov A, Závodszky G, Zun P. Towards the virtual artery: a multiscale model for vascular physiology at the physics-chemistry-biology interface. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2016; 374:rsta.2016.0146. [PMID: 27698036 PMCID: PMC5052730 DOI: 10.1098/rsta.2016.0146] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 07/14/2016] [Indexed: 05/27/2023]
Abstract
This discussion paper introduces the concept of the Virtual Artery as a multiscale model for arterial physiology and pathologies at the physics-chemistry-biology (PCB) interface. The cellular level is identified as the mesoscopic level, and we argue that by coupling cell-based models with other relevant models on the macro- and microscale, a versatile model of arterial health and disease can be composed. We review the necessary ingredients, both models of arteries at many different scales, as well as generic methods to compose multiscale models. Next, we discuss how this can be combined into the virtual artery. Finally, we argue that the concept of models at the PCB interface could or perhaps should become a powerful paradigm, not only as in our case for studying physiology, but also for many other systems that have such PCB interfaces.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.
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Affiliation(s)
- Alfons G Hoekstra
- Computational Science Laboratory, Institute for Informatics, Faculty of Science, University of Amsterdam, Sciencepark 904, 1098 XH Amsterdam, The Netherlands High Performance Computing Department, ITMO University, Saint Petersburg, Russia
| | - Saad Alowayyed
- Computational Science Laboratory, Institute for Informatics, Faculty of Science, University of Amsterdam, Sciencepark 904, 1098 XH Amsterdam, The Netherlands King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
| | - Eric Lorenz
- Computational Science Laboratory, Institute for Informatics, Faculty of Science, University of Amsterdam, Sciencepark 904, 1098 XH Amsterdam, The Netherlands Electric Ant Lab BV, Panamalaan 4 K, 1019AZ Amsterdam, The Netherlands
| | - Natalia Melnikova
- High Performance Computing Department, ITMO University, Saint Petersburg, Russia
| | - Lampros Mountrakis
- Computational Science Laboratory, Institute for Informatics, Faculty of Science, University of Amsterdam, Sciencepark 904, 1098 XH Amsterdam, The Netherlands
| | - Britt van Rooij
- Computational Science Laboratory, Institute for Informatics, Faculty of Science, University of Amsterdam, Sciencepark 904, 1098 XH Amsterdam, The Netherlands
| | - Andrew Svitenkov
- High Performance Computing Department, ITMO University, Saint Petersburg, Russia
| | - Gábor Závodszky
- Computational Science Laboratory, Institute for Informatics, Faculty of Science, University of Amsterdam, Sciencepark 904, 1098 XH Amsterdam, The Netherlands
| | - Pavel Zun
- High Performance Computing Department, ITMO University, Saint Petersburg, Russia
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