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Please use this identifier to cite or link to this item: http://hdl.handle.net/2262/39846

Title: Computational simulation methodologies for mechanobiological modelling: a cell-centred approach to neointima development in stents.
Author: KELLY, DANIEL
LENNON, ALEXANDER BENEDICT
PRENDERGAST, PATRICK JOHN
EARLY, MICHAEL
BOYLE, COLIN
Sponsor: Science Foundation Ireland
Author's Homepage: http://people.tcd.ie/pprender
http://people.tcd.ie/kellyd9
http://people.tcd.ie/lennonab
http://people.tcd.ie/earlym
http://people.tcd.ie/boyleco
Keywords: cell-centred
lattice-based
Issue Date: 2010
Citation: 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, 368, 1921, 2010, 2919-35
Series/Report no.: Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
368
1921
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.
Description: PUBLISHED
URI: http://hdl.handle.net/2262/39846
Related links: http://rsta.royalsocietypublishing.org/content/368/1921/2919.abstract
Appears in Collections:Mechanical & Manufacturing Eng (Scholarly Publications)

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