Gaussian process emulation to accelerate parameter estimation in a mechanical model of the left ventricle: a critical step towards clinical end-user relevance

Noè, U. , Lazarus, A., Gao, H. , Davies, V. , Macdonald, B. , Mangion, K., Berry, C. , Luo, X. and Husmeier, D. (2019) Gaussian process emulation to accelerate parameter estimation in a mechanical model of the left ventricle: a critical step towards clinical end-user relevance. Journal of the Royal Society: Interface, 16(156), 20190114. (doi:10.1098/rsif.2019.0114) (PMID:31266415)

Noè, U. , Lazarus, A., Gao, H. , Davies, V. , Macdonald, B. , Mangion, K., Berry, C. , Luo, X. and Husmeier, D. (2019) Gaussian process emulation to accelerate parameter estimation in a mechanical model of the left ventricle: a critical step towards clinical end-user relevance. Journal of the Royal Society: Interface, 16(156), 20190114. (doi:10.1098/rsif.2019.0114) (PMID:31266415)

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Abstract

In recent years, we have witnessed substantial advances in the mathematical modelling of the biomechanical processes underlying the dynamics of the cardiac soft-tissue. Gao et al. (Gao et al. 2017 J. R. Soc. Interface14, 20170203 (doi:10.1098/rsif.2017.0203)) demonstrated that the parameters underlying the biomechanical model have diagnostic value for prognosticating the risk of myocardial infarction. However, the computational costs of parameter estimation are prohibitive when the goal lies in building real-time clinical decision support systems. This is due to the need to repeatedly solve the mathematical equations numerically using finite-element discretization during an iterative optimization routine. The present article presents a method for accelerating the inference of the constitutive parameters by using statistical emulation with Gaussian processes. We demonstrate how the computational costs can be reduced by about three orders of magnitude, with hardly any loss in accuracy, and we assess various alternative techniques in a comparative evaluation study based on simulated data obtained by solving the left ventricular model with the finite-element method, and real magnetic resonance images data for a human volunteer.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Berry, Professor Colin and Davies, Dr Vincent and Gao, Dr Hao and Lazarus, Mr Alan and Luo, Professor Xiaoyu and Mangion, Dr Kenneth and Noe, Mr Umberto and Husmeier, Professor Dirk and Macdonald, Dr Benn
Authors: Noè, U., Lazarus, A., Gao, H., Davies, V., Macdonald, B., Mangion, K., Berry, C., Luo, X., and Husmeier, D.
College/School:College of Medical Veterinary and Life Sciences > Institute of Cardiovascular and Medical Sciences
College of Science and Engineering > School of Mathematics and Statistics
College of Science and Engineering > School of Mathematics and Statistics > Mathematics
College of Science and Engineering > School of Mathematics and Statistics > Statistics
College of Science and Engineering > School of Computing Science
Journal Name:Journal of the Royal Society: Interface
Publisher:The Royal Society
ISSN:1742-5689
ISSN (Online):1742-5662
Published Online:03 July 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Journal of the Royal Society: Interface 16(156): 20190114
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
694461EPSRC Centre for Multiscale soft tissue mechanics with application to heart & cancerRaymond OgdenEngineering and Physical Sciences Research Council (EPSRC)EP/N014642/1M&S - MATHEMATICS
544551Validation and significance of myocardial haemorrhage revealed by "bright blood" T2-weighted MRI in heart attack survivors: a prospective cohort study.Colin BerryBritish Heart Foundation (BHF)PG/11/2/28474RI CARDIOVASCULAR & MEDICAL SCIENCES
662681"First steps towards modelling myocardial infarction (a computed MI Physiome): A case-control study of novel biomechanical parameters in acute MI survivors with left ventricular dysfunction."Colin BerryBritish Heart Foundation (BHF)PG/14/64/31043RI CARDIOVASCULAR & MEDICAL SCIENCES