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Multi-objective optimisation of stent dilation strategy in a patient-specific coronary artery via computational and surrogate modelling

Multi-objective optimisation of stent dilation strategy in a patient-specific coronary artery via computational and surrogate modelling
Multi-objective optimisation of stent dilation strategy in a patient-specific coronary artery via computational and surrogate modelling
Although contemporary stents have been shown to improve short and long term clinical outcomes, the optimum dilation protocol is still uncertain in challenging cases characterised by long, highly calcified and tortuous anatomy. Recent clinical studies have revealed that in these cases, sub-optimal delivery can result in stent thrombosis (ST) and/or neointimal thickening as a result of stent malapposition (SM) and/or severe vessel trauma. One of the major contributors to vessel trauma is the damage caused by balloon dilation during stent deployment. In the present work, a Kriging based response surface modelling approach has been implemented to search for optimum stent deployment strategies in a clinically challenging, patient specific diseased coronary artery. In particular, the aims of this study were: (i) to understand the impact of the balloon pressure and unpressurised diameter on stent malapposition, drug distribution and wall stresses via computer simulations and (ii) obtain potentially optimal dilation protocols to simultaneously minimise stent malapposition and tissue wall stresses and maximise drug diffusion in the tissue. The results indicate that SM is inversely proportional to tissue stresses and drug deliverability. After analytical multi-objective optimisation, a set of “non-dominated” dilation scenarios was proposed as a post-optimisation methodology for protocol selection. Using this method, it has been shown that, for a given patient specific model, optimal stent expansion can be predicted. Such a framework could potentially be used by interventional cardiologists to minimise stent malapposition and tissue stresses whilst maximising drug deliverability in any patient-specific case.
stents, patient specific model, optimisation, surrogate modelling, finite element analysis
0021-9290
1-11
Ragkousis, Georgios E.
7812fa1c-12d2-49a9-ac07-654bb1b32a4c
Curzen, Nick
70f3ea49-51b1-418f-8e56-8210aef1abf4
Bressloff, Neil W.
4f531e64-dbb3-41e3-a5d3-e6a5a7a77c92
Ragkousis, Georgios E.
7812fa1c-12d2-49a9-ac07-654bb1b32a4c
Curzen, Nick
70f3ea49-51b1-418f-8e56-8210aef1abf4
Bressloff, Neil W.
4f531e64-dbb3-41e3-a5d3-e6a5a7a77c92

Ragkousis, Georgios E., Curzen, Nick and Bressloff, Neil W. (2016) Multi-objective optimisation of stent dilation strategy in a patient-specific coronary artery via computational and surrogate modelling. Journal of Biomechanics, 1-11. (doi:10.1016/j.jbiomech.2015.12.013).

Record type: Article

Abstract

Although contemporary stents have been shown to improve short and long term clinical outcomes, the optimum dilation protocol is still uncertain in challenging cases characterised by long, highly calcified and tortuous anatomy. Recent clinical studies have revealed that in these cases, sub-optimal delivery can result in stent thrombosis (ST) and/or neointimal thickening as a result of stent malapposition (SM) and/or severe vessel trauma. One of the major contributors to vessel trauma is the damage caused by balloon dilation during stent deployment. In the present work, a Kriging based response surface modelling approach has been implemented to search for optimum stent deployment strategies in a clinically challenging, patient specific diseased coronary artery. In particular, the aims of this study were: (i) to understand the impact of the balloon pressure and unpressurised diameter on stent malapposition, drug distribution and wall stresses via computer simulations and (ii) obtain potentially optimal dilation protocols to simultaneously minimise stent malapposition and tissue wall stresses and maximise drug diffusion in the tissue. The results indicate that SM is inversely proportional to tissue stresses and drug deliverability. After analytical multi-objective optimisation, a set of “non-dominated” dilation scenarios was proposed as a post-optimisation methodology for protocol selection. Using this method, it has been shown that, for a given patient specific model, optimal stent expansion can be predicted. Such a framework could potentially be used by interventional cardiologists to minimise stent malapposition and tissue stresses whilst maximising drug deliverability in any patient-specific case.

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More information

Accepted/In Press date: 3 December 2015
e-pub ahead of print date: 12 December 2015
Published date: 25 January 2016
Keywords: stents, patient specific model, optimisation, surrogate modelling, finite element analysis
Organisations: Faculty of Medicine, Faculty of Engineering and the Environment

Identifiers

Local EPrints ID: 385655
URI: http://eprints.soton.ac.uk/id/eprint/385655
ISSN: 0021-9290
PURE UUID: 5e2e1146-61cd-4857-bb49-f760d39faec7
ORCID for Nick Curzen: ORCID iD orcid.org/0000-0001-9651-7829

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Date deposited: 20 Jan 2016 12:35
Last modified: 18 Feb 2021 17:04

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