Predictive haemodynamics in a one-dimensional human carotid artery bifurcation. Part II: application to graft design
Predictive haemodynamics in a one-dimensional human carotid artery bifurcation. Part II: application to graft design
A Bayesian surrogate modelling technique is proposed that may be able to predict an optimal bypass graft configuration for patients suffering with stenosis in the internal carotid artery (ICA). At the outset, this statistical technique is considered as a means for identifying key geometric parameters influencing haemodynamics in the human carotid bifurcation. This methodology uses a design of experiments (DoE) technique to generate candidate geometries for flow analysis. A pulsatile one dimensional Navier-Stokes solver incorporating fluid-wall interactions for a Newtonian fluid which predicts pressure and flow in the carotid bifurcation (comprising a stenosed segment in the internal carotid artery) is used for the numerical simulations. Two metrics, pressure variation factor (PVF) and maximum pressure (pm) are employed to directly compare the global and local effects, respectively, of variations in the geometry. The values of PVF and pm are then used to construct two Bayesian surrogate models. These models are statistically analysed to visualise how each geometric parameter influences PVF and pm. Percentage of stenosis is found to influence these pressure based metrics more than any other geometric parameter. Later, we identify bypass grafts with optimal geometric and material properties which have low values of PVF on five test cases with 70%, 75%, 80%, 85% and 90% stenosis in the ICA, respectively.
1-D blood flow, Bayesian modeling, carotid artery, graft design, parametric studies, statistical analysis
1176-1184
Kolachalama, V. B.
bdf48fba-3c93-4542-9d23-67d1e792d54e
Bressloff, N. W.
4f531e64-dbb3-41e3-a5d3-e6a5a7a77c92
Nair, P. B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Shearman, C. P.
cf4d6317-f54d-4ab3-ba49-c6797897bbcf
March 2008
Kolachalama, V. B.
bdf48fba-3c93-4542-9d23-67d1e792d54e
Bressloff, N. W.
4f531e64-dbb3-41e3-a5d3-e6a5a7a77c92
Nair, P. B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Shearman, C. P.
cf4d6317-f54d-4ab3-ba49-c6797897bbcf
Kolachalama, V. B., Bressloff, N. W., Nair, P. B. and Shearman, C. P.
(2008)
Predictive haemodynamics in a one-dimensional human carotid artery bifurcation. Part II: application to graft design.
IEEE Transactions on Biomedical Engineering, 55 (3), .
(doi:10.1109/TBME.2007.912398).
Abstract
A Bayesian surrogate modelling technique is proposed that may be able to predict an optimal bypass graft configuration for patients suffering with stenosis in the internal carotid artery (ICA). At the outset, this statistical technique is considered as a means for identifying key geometric parameters influencing haemodynamics in the human carotid bifurcation. This methodology uses a design of experiments (DoE) technique to generate candidate geometries for flow analysis. A pulsatile one dimensional Navier-Stokes solver incorporating fluid-wall interactions for a Newtonian fluid which predicts pressure and flow in the carotid bifurcation (comprising a stenosed segment in the internal carotid artery) is used for the numerical simulations. Two metrics, pressure variation factor (PVF) and maximum pressure (pm) are employed to directly compare the global and local effects, respectively, of variations in the geometry. The values of PVF and pm are then used to construct two Bayesian surrogate models. These models are statistically analysed to visualise how each geometric parameter influences PVF and pm. Percentage of stenosis is found to influence these pressure based metrics more than any other geometric parameter. Later, we identify bypass grafts with optimal geometric and material properties which have low values of PVF on five test cases with 70%, 75%, 80%, 85% and 90% stenosis in the ICA, respectively.
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Published date: March 2008
Additional Information:
This paper presents one of the first attempts to apply statistical design methods (largely developed in the aerospace sector) to the field of biomedical device design. One of the key drivers here cocerns the extra information that could be provided to clinicians when attempting to plan treatment for vascular disease.
Keywords:
1-D blood flow, Bayesian modeling, carotid artery, graft design, parametric studies, statistical analysis
Organisations:
Dev Origins of Health & Disease
Identifiers
Local EPrints ID: 70452
URI: http://eprints.soton.ac.uk/id/eprint/70452
ISSN: 0018-9294
PURE UUID: c7ee9943-e88b-40cb-b1c3-6fcf6bf7af3f
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Date deposited: 02 Feb 2010
Last modified: 13 Mar 2024 20:03
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Author:
V. B. Kolachalama
Author:
P. B. Nair
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