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Shi J, Manjunatha K, Behr M, Vogt F, Reese S. A physics-informed deep learning framework for modeling of coronary in-stent restenosis. Biomech Model Mechanobiol 2024; 23:615-629. [PMID: 38236483 DOI: 10.1007/s10237-023-01796-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 11/22/2023] [Indexed: 01/19/2024]
Abstract
Machine learning (ML) techniques have shown great potential in cardiovascular surgery, including real-time stenosis recognition, detection of stented coronary anomalies, and prediction of in-stent restenosis (ISR). However, estimating neointima evolution poses challenges for ML models due to limitations in manual measurements, variations in image quality, low data availability, and the difficulty of acquiring biological quantities. An effective in silico model is necessary to accurately capture the mechanisms leading to neointimal hyperplasia. Physics-informed neural networks (PINNs), a novel deep learning (DL) method, have emerged as a promising approach that integrates physical laws and measurements into modeling. PINNs have demonstrated success in solving partial differential equations (PDEs) and have been applied in various biological systems. This paper aims to develop a robust multiphysics surrogate model for ISR estimation using the physics-informed DL approach, incorporating biological constraints and drug elution effects. The model seeks to enhance prediction accuracy, provide insights into disease progression factors, and promote ISR diagnosis and treatment planning. A set of coupled advection-reaction-diffusion type PDEs is constructed to track the evolution of the influential factors associated with ISR, such as platelet-derived growth factor (PDGF), the transforming growth factor- β (TGF- β ), the extracellular matrix (ECM), the density of smooth muscle cells (SMC), and the drug concentration. The nature of PINNs allows for the integration of patient-specific data (procedure-related, clinical and genetic, etc.) into the model, improving prediction accuracy and assisting in the optimization of stent implantation parameters to mitigate risks. This research addresses the existing gap in predictive models for ISR using DL and holds the potential to enhance patient outcomes through predictive risk assessment.
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Affiliation(s)
- Jianye Shi
- Institute of Applied Mechanics, RWTH Aachen University, Aachen, Germany.
| | - Kiran Manjunatha
- Institute of Applied Mechanics, RWTH Aachen University, Aachen, Germany
| | - Marek Behr
- Chair for Computational Analysis of Technical Systems, RWTH Aachen University, Aachen, Germany
| | - Felix Vogt
- Department of Cardiology, Pulmonology, Intensive Care and Vascular Medicine, RWTH Aachen University, Aachen, Germany
| | - Stefanie Reese
- Institute of Applied Mechanics, RWTH Aachen University, Aachen, Germany
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2
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Manjunatha K, Schaaps N, Behr M, Vogt F, Reese S. Computational modeling of in-stent restenosis: Pharmacokinetic and pharmacodynamic evaluation. Comput Biol Med 2023; 167:107686. [PMID: 37972534 DOI: 10.1016/j.compbiomed.2023.107686] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 10/11/2023] [Accepted: 11/06/2023] [Indexed: 11/19/2023]
Abstract
Persistence of the pathology of in-stent restenosis even with the advent of drug-eluting stents warrants the development of highly resolved in silico models. These computational models assist in gaining insights into the transient biochemical and cellular mechanisms involved and thereby optimize the stent implantation parameters. Within this work, an already established fully-coupled Lagrangian finite element framework for modeling the restenotic growth is enhanced with the incorporation of endothelium-mediated effects and pharmacological influences of rapamycin-based drugs embedded in the polymeric layers of the current generation drug-eluting stents. The continuum mechanical description of growth is further justified in the context of thermodynamic consistency. Qualitative inferences are drawn from the model developed herein regarding the efficacy of the level of drug embedment within the struts as well as the release profiles adopted. The framework is then intended to serve as a tool for clinicians to tune the interventional procedures patient-specifically.
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Affiliation(s)
- Kiran Manjunatha
- Institute of Applied Mechanics, RWTH Aachen University, Germany.
| | - Nicole Schaaps
- Department of Cardiology, Vascular Medicine and Intensive Care, RWTH Aachen University, Germany
| | - Marek Behr
- Chair for Computational Analysis of Technical Systems, RWTH Aachen University, Germany
| | - Felix Vogt
- Department of Cardiology, Vascular Medicine and Intensive Care, RWTH Aachen University, Germany
| | - Stefanie Reese
- Institute of Applied Mechanics, RWTH Aachen University, Germany
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3
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Manjunatha K, Behr M, Vogt F, Reese S. A multiphysics modeling approach for in-stent restenosis: Theoretical aspects and finite element implementation. Comput Biol Med 2022; 150:106166. [PMID: 36252366 DOI: 10.1016/j.compbiomed.2022.106166] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 09/19/2022] [Accepted: 10/01/2022] [Indexed: 11/21/2022]
Abstract
Development of in silico models that capture progression of diseases in soft biological tissues are intrinsic in the validation of the hypothesized cellular and molecular mechanisms involved in the respective pathologies. In addition, they also aid in patient-specific adaptation of interventional procedures. In this regard, a fully-coupled high-fidelity Lagrangian finite element framework is proposed within this work which replicates the pathology of in-stent restenosis observed post stent implantation in a coronary artery. Advection-reaction-diffusion equations are set up to track the concentrations of the platelet-derived growth factor, the transforming growth factor-β, the extracellular matrix, and the density of the smooth muscle cells. A continuum mechanical description of volumetric growth involved in the restenotic process, coupled to the evolution of the previously defined vessel wall constituents, is presented. Further, the finite element implementation of the model is discussed, and the behavior of the computational model is investigated via suitable numerical examples. Qualitative validation of the computational model is presented by emulating a stented artery. Patient-specific data are intended to be integrated into the model to predict the risk of in-stent restenosis, and thereby assist in the tuning of stent implantation parameters to mitigate the risk.
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Affiliation(s)
- Kiran Manjunatha
- Institute of Applied Mechanics, RWTH Aachen University, Germany.
| | - Marek Behr
- Chair for Computational Analysis of Technical Systems, RWTH Aachen University, Germany
| | - Felix Vogt
- Department of Cardiology, Pulmonology, Intensive Care and Vascular Medicine, RWTH Aachen University, Germany
| | - Stefanie Reese
- Institute of Applied Mechanics, RWTH Aachen University, Germany
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4
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An agent-based model of vibration-induced intimal hyperplasia. Biomech Model Mechanobiol 2022; 21:1457-1481. [DOI: 10.1007/s10237-022-01601-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 06/13/2022] [Indexed: 11/26/2022]
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5
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A Multiscale Approach for Predicting Certain Effects of Hand-Transmitted Vibration on Finger Arteries. VIBRATION 2022. [DOI: 10.3390/vibration5020014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Prolonged exposure to strong hand-arm vibrations can lead to vascular disorders such as Vibration White Finger (VWF). We modeled the onset of this peripheral vascular disease in two steps. The first consists in assessing the reduction in shearing forces exerted by the blood on the walls of the arteries (Wall Shear Stress—WSS) during exposure to vibrations. An acute but repeated reduction in WSS can lead to arterial stenosis characteristic of VWF. The second step is devoted to using a numerical mechano-biological model to predict this stenosis as a function of WSS. WSS is reduced by a factor of 3 during exposure to vibration of 40 m·s−2. This reduction is independent of the frequency of excitation between 31 Hz and 400 Hz. WSS decreases logarithmically when the amplitude of the vibration increases. The mechano-biological model simulated arterial stenosis of 30% for an employee exposed for 4 h a day for 10 years. This model also highlighted the chronic accumulation of matrix metalloproteinase 2. By considering daily exposure and the vibratory level, we can calculate the degree of stenosis, thus that of the disease for chronic exposure to vibrations.
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6
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Ye D, Zun P, Krzhizhanovskaya V, Hoekstra AG. Uncertainty quantification of a three-dimensional in-stent restenosis model with surrogate modelling. J R Soc Interface 2022; 19:20210864. [PMID: 35193385 PMCID: PMC8867271 DOI: 10.1098/rsif.2021.0864] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
In-stent restenosis is a recurrence of coronary artery narrowing due to vascular injury caused by balloon dilation and stent placement. It may lead to the relapse of angina symptoms or to an acute coronary syndrome. An uncertainty quantification of a model for in-stent restenosis with four uncertain parameters (endothelium regeneration time, the threshold strain for smooth muscle cell bond breaking, blood flow velocity and the percentage of fenestration in the internal elastic lamina) is presented. Two quantities of interest were studied, namely the average cross-sectional area and the maximum relative area loss in a vessel. Owing to the high computational cost required for uncertainty quantification, a surrogate model, based on Gaussian process regression with proper orthogonal decomposition, was developed and subsequently used for model response evaluation in the uncertainty quantification. A detailed analysis of the uncertainty propagation is presented. Around 11% and 16% uncertainty is observed on the two quantities of interest, respectively, and the uncertainty estimates show that a higher fenestration mainly determines the uncertainty in the neointimal growth at the initial stage of the process. The uncertainties in blood flow velocity and endothelium regeneration time mainly determine the uncertainty in the quantities of interest at the later, clinically relevant stages of the restenosis process.
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Affiliation(s)
- Dongwei Ye
- Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands
| | - Pavel Zun
- Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands.,National Center for Cognitive Research, ITMO University, Saint Petersburg, Russia
| | - Valeria Krzhizhanovskaya
- Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands
| | - Alfons G Hoekstra
- Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands
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7
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Digital Twins for Tissue Culture Techniques—Concepts, Expectations, and State of the Art. Processes (Basel) 2021. [DOI: 10.3390/pr9030447] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Techniques to provide in vitro tissue culture have undergone significant changes during the last decades, and current applications involve interactions of cells and organoids, three-dimensional cell co-cultures, and organ/body-on-chip tools. Efficient computer-aided and mathematical model-based methods are required for efficient and knowledge-driven characterization, optimization, and routine manufacturing of tissue culture systems. As an alternative to purely experimental-driven research, the usage of comprehensive mathematical models as a virtual in silico representation of the tissue culture, namely a digital twin, can be advantageous. Digital twins include the mechanistic of the biological system in the form of diverse mathematical models, which describe the interaction between tissue culture techniques and cell growth, metabolism, and the quality of the tissue. In this review, current concepts, expectations, and the state of the art of digital twins for tissue culture concepts will be highlighted. In general, DT’s can be applied along the full process chain and along the product life cycle. Due to the complexity, the focus of this review will be especially on the design, characterization, and operation of the tissue culture techniques.
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8
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Watson MG, Byrne HM, Macaskill C, Myerscough MR. A multiphase model of growth factor-regulated atherosclerotic cap formation. J Math Biol 2020; 81:725-767. [PMID: 32728827 DOI: 10.1007/s00285-020-01526-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Revised: 05/13/2020] [Indexed: 12/17/2022]
Abstract
Atherosclerosis is characterised by the growth of fatty plaques in the inner artery wall. In mature plaques, vascular smooth muscle cells (SMCs) are recruited from adjacent tissue to deposit a collagenous cap over the fatty plaque core. This cap isolates the thrombogenic plaque content from the bloodstream and prevents the clotting cascade that leads to myocardial infarction or stroke. Despite the protective role of the cap, the mechanisms that regulate cap formation and maintenance are not well understood. It remains unclear why some caps become stable, while others become vulnerable to rupture. We develop a multiphase PDE model with non-standard boundary conditions to investigate collagen cap formation by SMCs in response to diffusible growth factor signals from the endothelium. Platelet-derived growth factor stimulates SMC migration, proliferation and collagen degradation, while transforming growth factor (TGF)-[Formula: see text] stimulates SMC collagen synthesis and inhibits collagen degradation. The model SMCs respond haptotactically to gradients in the collagen phase and have reduced rates of migration and proliferation in dense collagenous tissue. The model, which is parameterised using in vivo and in vitro experimental data, reproduces several observations from plaque growth in mice. Numerical and analytical results demonstrate that a stable cap can be formed by a relatively small SMC population and emphasise the critical role of TGF-[Formula: see text] in effective cap formation. These findings provide unique insight into the mechanisms that may lead to plaque destabilisation and rupture. This work represents an important step towards the development of a comprehensive in silico plaque model.
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Affiliation(s)
- Michael G Watson
- School of Mathematics and Statistics, University of Sydney, Sydney, Australia.
| | - Helen M Byrne
- Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, UK
| | - Charlie Macaskill
- School of Mathematics and Statistics, University of Sydney, Sydney, Australia
| | - Mary R Myerscough
- School of Mathematics and Statistics, University of Sydney, Sydney, Australia
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9
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Stalidzans E, Zanin M, Tieri P, Castiglione F, Polster A, Scheiner S, Pahle J, Stres B, List M, Baumbach J, Lautizi M, Van Steen K, Schmidt HH. Mechanistic Modeling and Multiscale Applications for Precision Medicine: Theory and Practice. NETWORK AND SYSTEMS MEDICINE 2020. [DOI: 10.1089/nsm.2020.0002] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Affiliation(s)
- Egils Stalidzans
- Computational Systems Biology Group, University of Latvia, Riga, Latvia
- Latvian Biomedical Reasearch and Study Centre, Riga, Latvia
| | - Massimiliano Zanin
- Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Spain
| | - Paolo Tieri
- CNR National Research Council, IAC Institute for Applied Computing, Rome, Italy
| | - Filippo Castiglione
- CNR National Research Council, IAC Institute for Applied Computing, Rome, Italy
| | | | - Stefan Scheiner
- Institute for Mechanics of Materials and Structures, Vienna University of Technology, Vienna, Austria
| | - Jürgen Pahle
- BioQuant, Heidelberg University, Heidelberg, Germany
| | - Blaž Stres
- Department of Animal Science, University of Ljubljana, Ljubljana, Slovenia
- Faculty of Civil and Geodetic Engineering, University of Ljubljana, Ljubljana, Slovenia
- Department of Automation, Biocybernetics and Robotics, Jozef Stefan Institute, Ljubljana, Slovenia
| | - Markus List
- Big Data in BioMedicine Research Group, Chair of Experimental Bioinformatics, TUM School of Weihenstephan, Technical University of Munich, Freising, Germany
| | - Jan Baumbach
- Chair of Experimental Bioinformatics, TUM School of Weihenstephan, Technical University of Munich, Freising, Germany
| | - Manuela Lautizi
- Computational Systems Medicine Research Group, Chair of Experimental Bioinformatics, TUM School of Weihenstephan, Technical University of Munich, Freising, Germany
| | - Kristel Van Steen
- BIO-Systems Genetics, GIGA-R, University of Liège, Liège, Belgium
- BIO3—Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Harald H.H.W. Schmidt
- Department of Pharmacology and Personalised Medicine, Faculty of Health, Medicine and Life Science, Maastricht University, Maastricht, The Netherlands
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10
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Mechanistic evaluation of long-term in-stent restenosis based on models of tissue damage and growth. Biomech Model Mechanobiol 2020; 19:1425-1446. [PMID: 31912322 PMCID: PMC7502446 DOI: 10.1007/s10237-019-01279-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 12/17/2019] [Indexed: 02/06/2023]
Abstract
Development and application of advanced mechanical models of soft tissues and their growth represent one of the main directions in modern mechanics of solids. Such models are increasingly used to deal with complex biomedical problems. Prediction of in-stent restenosis for patients treated with coronary stents remains a highly challenging task. Using a finite element method, this paper presents a mechanistic approach to evaluate the development of in-stent restenosis in an artery following stent implantation. Hyperelastic models with damage, verified with experimental results, are used to describe the level of tissue damage in arterial layers and plaque caused by such intervention. A tissue-growth model, associated with vessel damage, is adopted to describe the growth behaviour of a media layer after stent implantation. Narrowing of lumen diameter with time is used to quantify the development of in-stent restenosis in the vessel after stenting. It is demonstrated that stent designs and materials strongly affect the stenting-induced damage in the media layer and the subsequent development of in-stent restenosis. The larger the artery expansion achieved during balloon inflation, the higher the damage introduced to the media layer, leading to an increased level of in-stent restenosis. In addition, the development of in-stent restenosis is directly correlated with the artery expansion during the stent deployment. The correlation is further used to predict the effect of a complex clinical procedure, such as stent overlapping, on the level of in-stent restenosis developed after percutaneous coronary intervention.
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11
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Escuer J, Martínez MA, McGinty S, Peña E. Mathematical modelling of the restenosis process after stent implantation. J R Soc Interface 2019; 16:20190313. [PMID: 31409233 DOI: 10.1098/rsif.2019.0313] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The stenting procedure has evolved to become a highly successful technique for the clinical treatment of advanced atherosclerotic lesions in arteries. However, the development of in-stent restenosis remains a key problem. In this work, a novel two-dimensional continuum mathematical model is proposed to describe the complex restenosis process following the insertion of a stent into a coronary artery. The biological species considered to play a key role in restenosis development are growth factors, matrix metalloproteinases, extracellular matrix, smooth muscle cells and endothelial cells. Diffusion-reaction equations are used for modelling the mass balance between species in the arterial wall. Experimental data from the literature have been used in order to estimate model parameters. Moreover, a sensitivity analysis has been performed to study the impact of varying the parameters of the model on the evolution of the biological species. The results demonstrate that this computational model qualitatively captures the key characteristics of the lesion growth and the healing process within an artery subjected to non-physiological mechanical forces. Our results suggest that the arterial wall response is driven by the damage area, smooth muscle cell proliferation and the collagen turnover among other factors.
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Affiliation(s)
- Javier Escuer
- Applied Mechanics and Bioengineering Group (AMB), Aragón Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza, Spain
| | - Miguel A Martínez
- Applied Mechanics and Bioengineering Group (AMB), Aragón Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
| | - Sean McGinty
- Division of Biomedical Engineering, University of Glasgow, Glasgow, UK
| | - Estefanía Peña
- Applied Mechanics and Bioengineering Group (AMB), Aragón Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
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12
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Nikishova A, Veen L, Zun P, Hoekstra AG. Semi-intrusive multiscale metamodelling uncertainty quantification with application to a model of in-stent restenosis. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2019; 377:20180154. [PMID: 30967038 PMCID: PMC6388010 DOI: 10.1098/rsta.2018.0154] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/10/2018] [Indexed: 05/02/2023]
Abstract
We explore the efficiency of a semi-intrusive uncertainty quantification (UQ) method for multiscale models as proposed by us in an earlier publication. We applied the multiscale metamodelling UQ method to a two-dimensional multiscale model for the wound healing response in a coronary artery after stenting (in-stent restenosis). The results obtained by the semi-intrusive method show a good match to those obtained by a black-box quasi-Monte Carlo method. Moreover, we significantly reduce the computational cost of the UQ. We conclude that the semi-intrusive metamodelling method is reliable and efficient, and can be applied to such complex models as the in-stent restenosis ISR2D model. This article is part of the theme issue 'Multiscale modelling, simulation and computing: from the desktop to the exascale'.
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Affiliation(s)
- A. Nikishova
- Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - L. Veen
- Netherlands eScience Center, 1098 XG Amsterdam, The Netherlands
| | - P. Zun
- Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- ITMO University, Saint Petersburg, 197101, Russia
| | - A. G. Hoekstra
- Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- ITMO University, Saint Petersburg, 197101, Russia
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13
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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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14
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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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15
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Hassanzadeh P, Atyabi F, Dinarvand R. Tissue engineering: Still facing a long way ahead. J Control Release 2018; 279:181-197. [DOI: 10.1016/j.jconrel.2018.04.024] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 04/09/2018] [Accepted: 04/11/2018] [Indexed: 02/07/2023]
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16
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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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17
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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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18
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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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19
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Complex Data-driven Predictive Modeling in Personalized Clinical Decision Support for Acute Coronary Syndrome Episodes. ACTA ACUST UNITED AC 2016. [DOI: 10.1016/j.procs.2016.05.332] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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20
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Mizeranschi A, Groen D, Borgdorff J, Hoekstra AG, Chopard B, Dubitzky W. Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine. Methods Mol Biol 2016; 1386:375-404. [PMID: 26677192 DOI: 10.1007/978-1-4939-3283-2_17] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.
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Affiliation(s)
- Alexandru Mizeranschi
- Biomedical Sciences Research Institute, University of Ulster, Cromore Road, Coleraine, Co. Londonderry, BT52 1SA, UK
| | - Derek Groen
- Chemistry Department, Centre for Computational Science, University College London, 20 Gordon Street, WC1H 0AJ, London, UK
| | - Joris Borgdorff
- Netherlands eScience Center, Science Park 140, 1098 XG, Amsterdam, The Netherlands
| | - Alfons G Hoekstra
- Computational Science Lab, Institute for Informatics, Faculty of Science, University of Amsterdam, Sciencepark 904, 1098 XH, Amsterdam, The Netherlands
- Advanced Computing Lab, ITMO University, 197101, 49 Kronverkskiy av., St. Petersburg, Russia
| | - Bastien Chopard
- Computer Science Department, University of Geneva, 7 route de Drize, 1227, Carouge, Switzerland
| | - Werner Dubitzky
- Biomedical Sciences Research Institute, University of Ulster, Cromore Road, Coleraine, Co. Londonderry, BT52 1SA, UK.
- School of Biomedical Sciences, University of Ulster, Coleraine campus, Cromore Road, Coleraine, Co. Londonderry, BT52 1SA, UK.
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21
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Randles A, Draeger EW, Bailey PE. Massively parallel simulations of hemodynamics in the primary large arteries of the human vasculature. JOURNAL OF COMPUTATIONAL SCIENCE 2015; 9:70-75. [PMID: 29152011 PMCID: PMC5693253 DOI: 10.1016/j.jocs.2015.04.003] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
We present a computational model of three-dimensional and unsteady hemodynamics within the primary large arteries in the human on 1,572,864 cores of the IBM Blue Gene/Q. Models of large regions of the circulatory system are needed to study the impact of local factors on global hemodynamics and to inform next generation drug delivery mechanisms. The HARVEY code successfully addresses key challenges that can hinder effective solution of image-based hemodynamics on contemporary supercomputers, such as limited memory capacity and bandwidth, flexible load balancing, and scalability. This work is the first demonstration of large fluid dynamics simulations of the aortofemoral region of the circulatory system at resolutions as small as 10 μm.
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Affiliation(s)
- Amanda Randles
- Lawrence Livermore National Laboratory, Livermore, CA, USA
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22
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Viceconti M, Hunter P, Hose R. Big Data, Big Knowledge: Big Data for Personalized Healthcare. IEEE J Biomed Health Inform 2015. [DOI: 10.1109/jbhi.2015.2406883] [Citation(s) in RCA: 191] [Impact Index Per Article: 21.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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23
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van der Sman RGM, Broeze J. Multiscale analysis of structure development in expanded starch snacks. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2014; 26:464103. [PMID: 25347195 DOI: 10.1088/0953-8984/26/46/464103] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
In this paper we perform a multiscale analysis of the food structuring process of the expansion of starchy snack foods like keropok, which obtains a solid foam structure. In particular, we want to investigate the validity of the hypothesis of Kokini and coworkers, that expansion is optimal at the moisture content, where the glass transition and the boiling line intersect. In our analysis we make use of several tools, (1) time scale analysis from the field of physical transport phenomena, (2) the scale separation map (SSM) developed within a multiscale simulation framework of complex automata, (3) the supplemented state diagram (SSD), depicting phase transition and glass transition lines, and (4) a multiscale simulation model for the bubble expansion. Results of the time scale analysis are plotted in the SSD, and give insight into the dominant physical processes involved in expansion. Furthermore, the results of the time scale analysis are used to construct the SSM, which has aided us in the construction of the multiscale simulation model. Simulation results are plotted in the SSD. This clearly shows that the hypothesis of Kokini is qualitatively true, but has to be refined. Our results show that bubble expansion is optimal for moisture content, where the boiling line for gas pressure of 4 bars intersects the isoviscosity line of the critical viscosity 10(6) Pa.s, which runs parallel to the glass transition line.
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Affiliation(s)
- R G M van der Sman
- Agrotechnology Food Sciences Group, Wageningen University & Research, 6708 PB Wageningen, The Netherlands
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24
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Hoekstra A, Chopard B, Coveney P. Multiscale modelling and simulation: a position paper. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A: MATHEMATICAL, PHYSICAL AND ENGINEERING SCIENCES 2014; 372:rsta.2013.0377. [PMID: 24982256 DOI: 10.1098/rsta.2013.0377] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
We argue that, despite the fact that the field of multiscale modelling and simulation has enjoyed significant success within the past decade, it still holds many open questions that are deemed important but so far have barely been explored. We believe that this is at least in part due to the fact that the field has been mainly developed within disciplinary silos. The principal topics that in our view would benefit from a targeted
multidisciplinary
research effort are related to reaching consensus as to what exactly one means by ‘multiscale modelling’, formulating a generic theory or calculus of multiscale modelling, applying such concepts to the urgent question of validation and verification of multiscale models, and the issue of numerical error propagation in multiscale models. Moreover, we believe that this would, in principle, also lay the foundation for more efficient, well-defined and usable multiscale computing environments. We believe that multidisciplinary research to fill in the gaps is timely, highly relevant, and with substantial potential impact on many scientific disciplines.
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Affiliation(s)
- Alfons Hoekstra
- Computational Science, Institute for Informatics, Faculty of Science, University of Amsterdam, The Netherlands
- National Research University ITMO, St Petersburg, Russian Federation
| | | | - Peter Coveney
- Centre for Computational Science, University College London, London, UK
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25
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Borgdorff J, Ben Belgacem M, Bona-Casas C, Fazendeiro L, Groen D, Hoenen O, Mizeranschi A, Suter JL, Coster D, Coveney PV, Dubitzky W, Hoekstra AG, Strand P, Chopard B. Performance of distributed multiscale simulations. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2014; 372:rsta.2013.0407. [PMID: 24982258 PMCID: PMC4084531 DOI: 10.1098/rsta.2013.0407] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Multiscale simulations model phenomena across natural scales using monolithic or component-based code, running on local or distributed resources. In this work, we investigate the performance of distributed multiscale computing of component-based models, guided by six multiscale applications with different characteristics and from several disciplines. Three modes of distributed multiscale computing are identified: supplementing local dependencies with large-scale resources, load distribution over multiple resources, and load balancing of small- and large-scale resources. We find that the first mode has the apparent benefit of increasing simulation speed, and the second mode can increase simulation speed if local resources are limited. Depending on resource reservation and model coupling topology, the third mode may result in a reduction of resource consumption.
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Affiliation(s)
- J Borgdorff
- Computational Science, Informatics Institute, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - M Ben Belgacem
- Computer Science Department, University of Geneva, 1227 Carouge, Switzerland
| | - C Bona-Casas
- Department of Applied Mathematics, University of A Coruña, 15001 A Coruña, Spain
| | - L Fazendeiro
- Department of Earth and Space Sciences, Chalmers University of Technology, 41296 Göteborg, Sweden
| | - D Groen
- Centre for Computational Science, University College London, 20 Gordon Street, London WC1H OAJ, UK
| | - O Hoenen
- Max-Planck-Institut für Plasmaphysik, 85748 Garching, Germany
| | - A Mizeranschi
- Nano Systems Biology, School of Biomedicine, University of Ulster, Coleraine BTS2 1SA, UK
| | - J L Suter
- Centre for Computational Science, University College London, 20 Gordon Street, London WC1H OAJ, UK
| | - D Coster
- Max-Planck-Institut für Plasmaphysik, 85748 Garching, Germany
| | - P V Coveney
- Centre for Computational Science, University College London, 20 Gordon Street, London WC1H OAJ, UK
| | - W Dubitzky
- Nano Systems Biology, School of Biomedicine, University of Ulster, Coleraine BTS2 1SA, UK
| | - A G Hoekstra
- Computational Science, Informatics Institute, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands National Research University ITMO, Kronverkskiy prospekt 49, 197101 St Petersburg, Russia
| | - P Strand
- Department of Earth and Space Sciences, Chalmers University of Technology, 41296 Göteborg, Sweden
| | - B Chopard
- Computer Science Department, University of Geneva, 1227 Carouge, Switzerland
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26
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Chopard B, Borgdorff J, Hoekstra AG. A framework for multi-scale modelling. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2014; 372:rsta.2013.0378. [PMID: 24982249 PMCID: PMC4084523 DOI: 10.1098/rsta.2013.0378] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
We review a methodology to design, implement and execute multi-scale and multi-science numerical simulations. We identify important ingredients of multi-scale modelling and give a precise definition of them. Our framework assumes that a multi-scale model can be formulated in terms of a collection of coupled single-scale submodels. With concepts such as the scale separation map, the generic submodel execution loop (SEL) and the coupling templates, one can define a multi-scale modelling language which is a bridge between the application design and the computer implementation. Our approach has been successfully applied to an increasing number of applications from different fields of science and technology.
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Affiliation(s)
- B Chopard
- Department of Computer Science, University of Geneva, Geneva, Switzerland
| | - Joris Borgdorff
- Department of Computational Science, University of Amsterdam, Amsterdam, The Netherlands
| | - A G Hoekstra
- Department of Computational Science, University of Amsterdam, Amsterdam, The Netherlands National Research University ITMO, Saint-Petersburg, Russia
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27
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van der Sman R, Vergeldt F, Van As H, van Dalen G, Voda A, van Duynhoven J. Multiphysics pore-scale model for the rehydration of porous foods. INNOV FOOD SCI EMERG 2014. [DOI: 10.1016/j.ifset.2013.11.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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28
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Castiglione F, Pappalardo F, Bianca C, Russo G, Motta S. Modeling biology spanning different scales: an open challenge. BIOMED RESEARCH INTERNATIONAL 2014; 2014:902545. [PMID: 25143952 PMCID: PMC4124842 DOI: 10.1155/2014/902545] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2014] [Accepted: 06/25/2014] [Indexed: 02/03/2023]
Abstract
It is coming nowadays more clear that in order to obtain a unified description of the different mechanisms governing the behavior and causality relations among the various parts of a living system, the development of comprehensive computational and mathematical models at different space and time scales is required. This is one of the most formidable challenges of modern biology characterized by the availability of huge amount of high throughput measurements. In this paper we draw attention to the importance of multiscale modeling in the framework of studies of biological systems in general and of the immune system in particular.
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Affiliation(s)
- Filippo Castiglione
- Institute for Applied Mathematics, National Research Council of Italy, Rome, Italy
| | | | - Carlo Bianca
- Theoretical Physics of Condensed Matter, Sorbonne Universities, UPMC Univ Paris 6, 75252 Paris Cedex 05, France
- UMR 7600 LPTMC, CNRS, 75252 Paris Cedex 05, France
| | - Giulia Russo
- Department of Pharmaceutical Sciences, University of Catania, Catania, Italy
| | - Santo Motta
- Department of Mathematics and Computer Science, University of Catania, 95125 Catania, Italy
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29
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From Histology and Imaging Data to Models for In-Stent Restenosis. Int J Artif Organs 2014; 37:786-800. [DOI: 10.5301/ijao.5000336] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/29/2014] [Indexed: 11/20/2022]
Abstract
The implantation of stents has been used to treat coronary artery stenosis for several decades. Although stenting is successful in restoring the vessel lumen and is a minimally invasive approach, the long-term outcomes are often compromised by in-stent restenosis (ISR). Animal models have provided insights into the pathophysiology of ISR and are widely used to evaluate candidate drug inhibitors of ISR. Such biological models allow the response of the vessel to stent implantation to be studied without the variation of lesion characteristics encountered in patient studies. This paper describes the development of complementary in silico models employed to improve the understanding of the biological response to stenting using a porcine model of restenosis. This includes experimental quantification using microCT imaging and histology and the use of this data to establish numerical models of restenosis. Comparison of in silico results with histology is used to examine the relationship between spatial localization of fluid and solid mechanics stimuli immediately post-stenting. Multi-scale simulation methods are employed to study the evolution of neointimal growth over time and the variation in the extent of neointimal hyperplasia within the stented region. Interpretation of model results through direct comparison with the biological response contributes to more detailed understanding of the pathophysiology of ISR, and suggests the focus for follow-up studies. In conclusion we outline the challenges which remain to both complete our understanding of the mechanisms responsible for restenosis and translate these models to applications in stent design and treatment planning at both population-based and patient-specific levels.
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30
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Tahir H, Bona-Casas C, Narracott AJ, Iqbal J, Gunn J, Lawford P, Hoekstra AG. Endothelial repair process and its relevance to longitudinal neointimal tissue patterns: comparing histology with in silico modelling. J R Soc Interface 2014; 11:20140022. [PMID: 24621816 DOI: 10.1098/rsif.2014.0022] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Re-establishing a functional endothelium following endovascular treatment is an important factor in arresting neointimal proliferation. In this study, both histology (in vivo) and computational simulations (in silico) are used to evaluate neointimal growth patterns within coronary arteries along the axial direction of the stent. Comparison of the growth configurations in vivo and in silico was undertaken to identify candidate mechanisms for endothelial repair. Stent, lumen and neointimal areas were measured from histological sections obtained from eight right coronary stented porcine arteries. Two re-endothelialization scenarios (endothelial cell (EC) random seeding and EC growth from proximal and distal ends) were implemented in silico to evaluate their influence on the morphology of the simulated lesions. Subject to the assumptions made in the current simulations, comparison between in vivo and in silico results suggests that endothelial growth does not occur from the proximal and distal ends alone, but is more consistent with the assumption of a random seeding process. This may occur either from the patches of endothelium which survive following stent implantation or from attachment of circulating endothelial progenitor cells.
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Affiliation(s)
- Hannan Tahir
- Computational Science, Informatics Institute, University of Amsterdam, , Science Park 904, Amsterdam 1098 XH, The Netherlands
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31
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Groen D, Borgdorff J, Bona-Casas C, Hetherington J, Nash RW, Zasada SJ, Saverchenko I, Mamonski M, Kurowski K, Bernabeu MO, Hoekstra AG, Coveney PV. Flexible composition and execution of high performance, high fidelity multiscale biomedical simulations. Interface Focus 2014; 3:20120087. [PMID: 24427530 DOI: 10.1098/rsfs.2012.0087] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Multiscale simulations are essential in the biomedical domain to accurately model human physiology. We present a modular approach for designing, constructing and executing multiscale simulations on a wide range of resources, from laptops to petascale supercomputers, including combinations of these. Our work features two multiscale applications, in-stent restenosis and cerebrovascular bloodflow, which combine multiple existing single-scale applications to create a multiscale simulation. These applications can be efficiently coupled, deployed and executed on computers up to the largest (peta) scale, incurring a coupling overhead of 1-10% of the total execution time.
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Affiliation(s)
- D Groen
- Centre for Computational Science, University College London, UK
| | - J Borgdorff
- Section Computational Science, University of Amsterdam, The Netherlands
| | - C Bona-Casas
- Section Computational Science, University of Amsterdam, The Netherlands
| | - J Hetherington
- Centre for Computational Science, University College London, UK
| | - R W Nash
- Centre for Computational Science, University College London, UK
| | - S J Zasada
- Centre for Computational Science, University College London, UK
| | | | - M Mamonski
- Poznan Supercomputing and Networking Center, Poznan, Poland
| | - K Kurowski
- Poznan Supercomputing and Networking Center, Poznan, Poland
| | - M O Bernabeu
- Centre for Computational Science, University College London, UK
| | - A G Hoekstra
- Section Computational Science, University of Amsterdam, The Netherlands
| | - P V Coveney
- Centre for Computational Science, University College London, UK
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32
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Tahir H, Bona-Casas C, Hoekstra AG. Modelling the effect of a functional endothelium on the development of in-stent restenosis. PLoS One 2013; 8:e66138. [PMID: 23785479 PMCID: PMC3681932 DOI: 10.1371/journal.pone.0066138] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2013] [Accepted: 05/01/2013] [Indexed: 11/19/2022] Open
Abstract
Treatment of stenosed coronary arteries by balloon angioplasty and stenting results in arterial injury including severe damage to the endothelium at the site of treatment and initiates a complex cascade of inflammatory processes that may lead to the development of in-stent restenosis (ISR). Many clinical and biological factors involved in the progression of restenotic lesions have been studied in detail over the past few years but the mystery behind the pathophysiological mechanisms of this disease is still unresolved. In the present work, the effects of re-endothelialization and nitric oxide release on neointimal growth are investigated in-silico using a two dimensional multi-scale model of ISR. The effect of stent deployment depths on the development of ISR is studied as a function of time after stenting. Two dimensional domains were prepared by deploying bare metal stent struts at three different deployment depths into the tissue. Shear stress distribution on endothelial cells, obtained by blood flow simulations, was translated into nitric oxide production that keeps the smooth muscle cells in quiescent state. The cellular growth trends were plotted as a function of time and the data indicate a positive correlation between the neointimal growths and strut deployment depths in the presence of a functional endothelium, in qualitative agreement with in-vivo data. Additionally, no ISR is observed if a functional endothelium appears much earlier.
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Affiliation(s)
- Hannan Tahir
- Computational Science, Informatics Institute, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands.
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33
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Van der Heiden K, Gijsen FJH, Narracott A, Hsiao S, Halliday I, Gunn J, Wentzel JJ, Evans PC. The effects of stenting on shear stress: relevance to endothelial injury and repair. Cardiovasc Res 2013; 99:269-75. [PMID: 23592806 DOI: 10.1093/cvr/cvt090] [Citation(s) in RCA: 91] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Stent deployment following balloon angioplasty is used routinely to treat coronary artery disease. These interventions cause damage and loss of endothelial cells (EC), and thus promote in-stent thrombosis and restenosis. Injured arteries are repaired (intrinsically) by locally derived EC and by circulating endothelial progenitor cells which migrate and proliferate to re-populate denuded regions. However, re-endothelialization is not always complete and often dysfunctional. Moreover, the molecular and biomechanical mechanisms that control EC repair and function in stented segments are poorly understood. Here, we propose that stents modify endothelial repair processes, in part, by altering fluid shear stress, a mechanical force that influences EC migration and proliferation. A more detailed understanding of the biomechanical processes that control endothelial healing would provide a platform for the development of novel therapeutic approaches to minimize damage and promote vascular repair in stented arteries.
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Affiliation(s)
- Kim Van der Heiden
- Biomedical Engineering, Department Cardiology, ErasmusMC, Rotterdam, The Netherlands
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34
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Borgdorff J, Mamonski M, Bosak B, Groen D, Belgacem MB, Kurowski K, Hoekstra AG. Multiscale Computing with the Multiscale Modeling Library and Runtime Environment. ACTA ACUST UNITED AC 2013. [DOI: 10.1016/j.procs.2013.05.275] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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35
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Zahedmanesh H, Van Oosterwyck H, Lally C. A multi-scale mechanobiological model of in-stent restenosis: deciphering the role of matrix metalloproteinase and extracellular matrix changes. Comput Methods Biomech Biomed Engin 2012; 17:813-28. [DOI: 10.1080/10255842.2012.716830] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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36
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Burkitt M, Walker D, Romano DM, Fazeli A. Computational modelling of maternal interactions with spermatozoa: potentials and prospects. Reprod Fertil Dev 2012; 23:976-89. [PMID: 22127003 DOI: 10.1071/rd11032] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2011] [Accepted: 07/12/2011] [Indexed: 12/20/2022] Open
Abstract
Understanding the complex interactions between gametes, embryos and the maternal tract is required knowledge for combating infertility and developing new methods of contraception. Here we present some main aspects of spermatozoa interactions with the mammalian oviduct before fertilisation and discuss how computational modelling can be used as an invaluable aid to experimental investigation in this field. A complete predictive computational model of gamete and embryo interactions with the female reproductive tract is a long way off. However, the enormity of this task should not discourage us from working towards it. Computational modelling allows us to investigate aspects of maternal communication with gametes and embryos, which are financially, ethically or practically difficult to look at experimentally. In silico models of maternal communication with gametes and embryos can be used as tools to complement in vivo experiments, in the same way as in vitro and in situ models.
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Affiliation(s)
- Mark Burkitt
- The Department of Computer Science, University of Sheffield, Sheffield, Regent Court, 211 Portobello, Sheffield S1 4DP, UK
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37
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Halliday I, Atherton M, Care C, Collins M, Evans D, Evans P, Hose D, Khir A, König C, Krams R, Lawford P, Lishchuk S, Pontrelli G, Ridger V, Spencer T, Ventikos Y, Walker D, Watton P. Multi-scale interaction of particulate flow and the artery wall. Med Eng Phys 2011; 33:840-8. [DOI: 10.1016/j.medengphy.2010.09.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2010] [Revised: 08/05/2010] [Accepted: 09/10/2010] [Indexed: 10/18/2022]
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38
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Boyle CJ, Lennon AB, Prendergast PJ. In Silico Prediction of the Mechanobiological Response of Arterial Tissue: Application to Angioplasty and Stenting. J Biomech Eng 2011; 133:081001. [DOI: 10.1115/1.4004492] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
One way to restore physiological blood flow to occluded arteries involves the deformation of plaque using an intravascular balloon and preventing elastic recoil using a stent. Angioplasty and stent implantation cause unphysiological loading of the arterial tissue, which may lead to tissue in-growth and reblockage; termed “restenosis.” In this paper, a computational methodology for predicting the time-course of restenosis is presented. Stress-induced damage, computed using a remaining life approach, stimulates inflammation (production of matrix degrading factors and growth stimuli). This, in turn, induces a change in smooth muscle cell phenotype from contractile (as exists in the quiescent tissue) to synthetic (as exists in the growing tissue). In this paper, smooth muscle cell activity (migration, proliferation, and differentiation) is simulated in a lattice using a stochastic approach to model individual cell activity. The inflammation equations are examined under simplified loading cases. The mechanobiological parameters of the model were estimated by calibrating the model response to the results of a balloon angioplasty study in humans. The simulation method was then used to simulate restenosis in a two dimensional model of a stented artery. Cell activity predictions were similar to those observed during neointimal hyperplasia, culminating in the growth of restenosis. Similar to experiment, the amount of neointima produced increased with the degree of expansion of the stent, and this relationship was found to be highly dependant on the prescribed inflammatory response. It was found that the duration of inflammation affected the amount of restenosis produced, and that this effect was most pronounced with large stent expansions. In conclusion, the paper shows that the arterial tissue response to mechanical stimulation can be predicted using a stochastic cell modeling approach, and that the simulation captures features of restenosis development observed with real stents. The modeling approach is proposed for application in three dimensional models of cardiovascular stenting procedures.
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Affiliation(s)
- Colin J. Boyle
- Trinity Centre for Bioengineering, School of Engineering, University of Dublin, Trinity College, Dublin, Ireland
| | - Alexander B. Lennon
- Trinity Centre for Bioengineering, School of Engineering, University of Dublin, Trinity College, Dublin, Ireland
| | - Patrick J. Prendergast
- Trinity Centre for Bioengineering, School of Engineering, University of Dublin, Trinity College, Dublin, Ireland
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39
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Díaz-Zuccarini V, Lawford PV. An in-silico future for the engineering of functional tissues and organs. Organogenesis 2011; 6:245-51. [PMID: 21220955 DOI: 10.4161/org.6.4.13284] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Vanessa Díaz-Zuccarini
- University College London, Department of Mechanical Engineering, Torrington Place, London, UK.
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40
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Tahir H, Hoekstra AG, Lorenz E, Lawford PV, Hose DR, Gunn J, Evans DJW. Multi-scale simulations of the dynamics of in-stent restenosis: impact of stent deployment and design. Interface Focus 2011; 1:365-73. [PMID: 22670206 DOI: 10.1098/rsfs.2010.0024] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2010] [Accepted: 03/03/2011] [Indexed: 12/11/2022] Open
Abstract
Neointimal hyperplasia, a process of smooth muscle cell re-growth, is the result of a natural wound healing response of the injured artery after stent deployment. Excessive neointimal hyperplasia following coronary artery stenting results in in-stent restenosis (ISR). Regardless of recent developments in the field of coronary stent design, ISR remains a significant complication of this interventional therapy. The influence of stent design parameters such as strut thickness, shape and the depth of strut deployment within the vessel wall on the severity of restenosis has already been highlighted but the detail of this influence is unclear. These factors impact on local haemodynamics and vessel structure and affect the rate of neointima formation. This paper presents the first results of a multi-scale model of ISR. The development of the simulated restenosis as a function of stent deployment depth is compared with an in vivo porcine dataset. Moreover, the influence of strut size and shape is investigated, and the effect of a drug released at the site of injury, by means of a drug-eluting stent, is also examined. A strong correlation between strut thickness and the rate of smooth muscle cell proliferation has been observed. Simulation results also suggest that the growth of the restenotic lesion is strongly dependent on the stent strut cross-sectional profile.
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Affiliation(s)
- Hannan Tahir
- Computational Science, Faculty of Science , University of Amsterdam , Amsterdam , The Netherlands
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41
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Díaz-Zuccarini V, Pichardo-Almarza C. On the formalization of multi-scale and multi-science processes for integrative biology. Interface Focus 2011; 1:426-37. [PMID: 22670211 DOI: 10.1098/rsfs.2010.0038] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2010] [Accepted: 03/02/2011] [Indexed: 11/12/2022] Open
Abstract
The aim of this work is to introduce the general concept of 'Bond Graph' (BG) techniques applied in the context of multi-physics and multi-scale processes. BG modelling has a natural place in these developments. BGs are inherently coherent as the relationships defined between the 'elements' of the graph are strictly defined by causality rules and power (energy) conservation. BGs clearly show how power flows between components of the systems they represent. The 'effort' and 'flow' variables enable bidirectional information flow in the BG model. When the power level of a system is low, BGs degenerate into signal flow graphs in which information is mainly one-dimensional and power is minimal, i.e. they find a natural limitation when dealing with populations of individuals or purely kinetic models, as the concept of energy conservation in these systems is no longer relevant. The aim of this work is twofold: on the one hand, we will introduce the general concept of BG techniques applied in the context of multi-science and multi-scale models and, on the other hand, we will highlight some of the most promising features in the BG methodology by comparing with examples developed using well-established modelling techniques/software that could suggest developments or refinements to the current state-of-the-art tools, by providing a consistent framework from a structural and energetic point of view.
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Affiliation(s)
- Vanessa Díaz-Zuccarini
- Department of Mechanical Engineering , University College London , Torrington Place, London WC1E 7JE , UK
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42
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Dada JO, Mendes P. Multi-scale modelling and simulation in systems biology. Integr Biol (Camb) 2011; 3:86-96. [DOI: 10.1039/c0ib00075b] [Citation(s) in RCA: 129] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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43
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Chopard B, Falcone JL, Hoekstra AG, Borgdorff J. A Framework for Multiscale and Multiscience Modeling and Numerical Simulations. LECTURE NOTES IN COMPUTER SCIENCE 2011. [DOI: 10.1007/978-3-642-21341-0_2] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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44
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Buti F, Cacciagrano D, Corradini F, Merelli E, Tesei L, Pani M. Bone Remodelling in BioShape. ACTA ACUST UNITED AC 2010. [DOI: 10.1016/j.entcs.2010.12.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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45
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Boyle CJ, Lennon AB, Early M, Kelly DJ, Lally C, Prendergast PJ. Computational simulation methodologies for mechanobiological modelling: a cell-centred approach to neointima development in stents. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2010; 368:2919-35. [PMID: 20478914 PMCID: PMC2944394 DOI: 10.1098/rsta.2010.0071] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The design of medical devices could be very much improved if robust tools were available for computational simulation of tissue response to the presence of the implant. Such tools require algorithms to simulate the response of tissues to mechanical and chemical stimuli. Available methodologies include those based on the principle of mechanical homeostasis, those which use continuum models to simulate biological constituents, and the cell-centred approach, which models cells as autonomous agents. In the latter approach, cell behaviour is governed by rules based on the state of the local environment around the cell; and informed by experiment. Tissue growth and differentiation requires simulating many of these cells together. In this paper, the methodology and applications of cell-centred techniques--with particular application to mechanobiology--are reviewed, and a cell-centred model of tissue formation in the lumen of an artery in response to the deployment of a stent is presented. The method is capable of capturing some of the most important aspects of restenosis, including nonlinear lesion growth with time. The approach taken in this paper provides a framework for simulating restenosis; the next step will be to couple it with more patient-specific geometries and quantitative parameter data.
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Affiliation(s)
- C. J. Boyle
- Trinity Centre for Bioengineering, School of Engineering, Trinity College Dublin, Dublin, Republic of Ireland
| | - A. B. Lennon
- Trinity Centre for Bioengineering, School of Engineering, Trinity College Dublin, Dublin, Republic of Ireland
| | - M. Early
- Trinity Centre for Bioengineering, School of Engineering, Trinity College Dublin, Dublin, Republic of Ireland
| | - D. J. Kelly
- Trinity Centre for Bioengineering, School of Engineering, Trinity College Dublin, Dublin, Republic of Ireland
| | - C. Lally
- Trinity Centre for Bioengineering, School of Engineering, Trinity College Dublin, Dublin, Republic of Ireland
- Department of Mechanical and Manufacturing Engineering, Dublin City University, Dublin, Republic of Ireland
| | - P. J. Prendergast
- Trinity Centre for Bioengineering, School of Engineering, Trinity College Dublin, Dublin, Republic of Ireland
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46
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Hoekstra AG, Caiazzo A, Lorenz E, Falcone JL, Chopard B. Complex Automata: Multi-scale Modeling with Coupled Cellular Automata. UNDERSTANDING COMPLEX SYSTEMS 2010. [DOI: 10.1007/978-3-642-12203-3_3] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
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47
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Sloot PMA, Hoekstra AG. Multi-scale modelling in computational biomedicine. Brief Bioinform 2009; 11:142-52. [PMID: 20028713 DOI: 10.1093/bib/bbp038] [Citation(s) in RCA: 58] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The inherent complexity of biomedical systems is well recognized; they are multi-scale, multi-science systems, bridging a wide range of temporal and spatial scales. This article reviews the currently emerging field of multi-scale modelling in computational biomedicine. Many exciting multi-scale models exist or are under development. However, an underpinning multi-scale modelling methodology seems to be missing. We propose a direction that complements the classic dynamical systems approach and introduce two distinct case studies, transmission of resistance in human immunodeficiency virus spreading and in-stent restenosis in coronary artery disease.
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Affiliation(s)
- Peter M A Sloot
- Computational Science, Faculty of Science, University of Amsterdam, Kruislaan 403, 1098 SJ Amsterdam, The Netherlands.
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48
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Díaz-Zuccarini V, Narracott AJ, Burriesci G, Zervides C, Rafiroiu D, Jones D, Hose DR, Lawford PV. Adaptation and development of software simulation methodologies for cardiovascular engineering: present and future challenges from an end-user perspective. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2009; 367:2655-2666. [PMID: 19487202 PMCID: PMC2696108 DOI: 10.1098/rsta.2009.0052] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
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.
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Affiliation(s)
- V Díaz-Zuccarini
- Cardiovascular Engineering and Medical Devices Group, Department of Mechanical Engineering, University College London, Torrington Place, London WC1 7JE, UK.
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49
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Walker DC, Southgate J. The virtual cell--a candidate co-ordinator for 'middle-out' modelling of biological systems. Brief Bioinform 2009; 10:450-61. [PMID: 19293250 DOI: 10.1093/bib/bbp010] [Citation(s) in RCA: 54] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Understanding the functioning of biological systems depends on tackling complexity spanning spatial scales from genome to organ to whole organism. The basic unit of life, the cell, acts to co-ordinate information received across these scales and processes the myriad of signals to produce an integrated cellular response. Cells interact with and respond to other cells through direct or indirect contact, resulting in emergent structure and function of tissues and organs. Systems biology has traditionally used either a 'top-down' or 'bottom-up' approach. However, neither approach takes account of heterogeneity or 'noise', which is an inherent feature of cellular behaviour and may have significant impact on system level behaviour. We review existing approaches to modelling that use cellular automata or agent-based methodologies, where individual cells are represented as equivalent virtual entities governed by simple rules. These paradigms allow a direct one-to-one mapping between real and virtual cells that can be exploited in terms of acquiring parameters from experimental systems, or for model validation. Such models are inherently extensible and can be integrated with other modelling modalities (e.g. partial or ordinary differential equations) to model multi-scale phenomena. Alternatively, hierarchical agent models may be used to explore the functions of biological systems across temporal and spatial scales. This review examines individual-based models and the application of the paradigm to explore multi-scale phenomena in biology. In so doing, it demonstrates how cellular-based models have begun to play an important role in the development of 'middle-out' models, but with considerable potential for future development.
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Affiliation(s)
- Dawn C Walker
- Department of Computer Science at the University of Sheffield
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50
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Caiazzo A, Evans D, Falcone JL, Hegewald J, Lorenz E, Stahl B, Wang D, Bernsdorf J, Chopard B, Gunn J, Hose R, Krafczyk M, Lawford P, Smallwood R, Walker D, Hoekstra AG. Towards a Complex Automata Multiscale Model of In-Stent Restenosis. LECTURE NOTES IN COMPUTER SCIENCE 2009. [DOI: 10.1007/978-3-642-01970-8_70] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
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