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Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation

Sanjay Pant Orcid Logo, Chiara Corsini, Catriona Baker, Tain-Yen Hsia, Giancarlo Pennati, Irene E. Vignon-Clementel

Journal of Biomechanics, Volume: 49, Issue: 11, Pages: 2162 - 2173

Swansea University Author: Sanjay Pant Orcid Logo

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DOI (Published version): 10.1016/j.jbiomech.2015.11.030

Abstract

A closed-loop lumped parameter model of blood circulation is considered for single-ventricle shunt physiology. Its parameters are estimated by an inverse problem based on patient-specific haemodynamics measurements. As opposed to a black-box approach, maximizing the number of parameters that are rel...

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Published in: Journal of Biomechanics
ISSN: 0021-9290
Published: 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa34500
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first_indexed 2017-06-27T20:09:31Z
last_indexed 2018-02-09T05:24:42Z
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spelling 2017-07-05T13:33:26.8681355 v2 34500 2017-06-27 Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation 43b388e955511a9d1b86b863c2018a9f 0000-0002-2081-308X Sanjay Pant Sanjay Pant true false 2017-06-27 MECH A closed-loop lumped parameter model of blood circulation is considered for single-ventricle shunt physiology. Its parameters are estimated by an inverse problem based on patient-specific haemodynamics measurements. As opposed to a black-box approach, maximizing the number of parameters that are related to physically measurable quantities motivates the present model. Heart chambers are described by a single-fibre mechanics model, and valve function is modelled with smooth opening and closure. A model for valve prolapse leading to valve regurgitation is proposed. The method of data assimilation, in particular the unscented Kalman filter, is used to estimate the model parameters from time-varying clinical measurements. This method takes into account both the uncertainty in prior knowledge related to the parameters and the uncertainty associated with the clinical measurements. Two patient-specific cases – one without regurgitation and one with atrioventricular valve regurgitation – are presented. Pulmonary and systemic circulation parameters are successfully estimated, without assumptions on their relationships. Parameters governing the behaviour of heart chambers and valves are either fixed based on biomechanics, or estimated. Results of the inverse problem are validated qualitatively through clinical measurements or clinical estimates that were not included in the parameter estimation procedure. The model and the estimation method are shown to successfully capture patient-specific clinical observations, even with regurgitation, such as the double peaked nature of valvular flows and anomalies in electrocardiogram readings. Lastly, biomechanical implications of the results are discussed. Journal Article Journal of Biomechanics 49 11 2162 2173 0021-9290 Single-ventricle physiology, Valve regurgitation, Data assimilation, Unscented Kalman filter, Patient-specific modelling, Single-fibre heart model 26 7 2016 2016-07-26 10.1016/j.jbiomech.2015.11.030 COLLEGE NANME Mechanical Engineering COLLEGE CODE MECH Swansea University 2017-07-05T13:33:26.8681355 2017-06-27T16:23:09.2305131 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering Sanjay Pant 0000-0002-2081-308X 1 Chiara Corsini 2 Catriona Baker 3 Tain-Yen Hsia 4 Giancarlo Pennati 5 Irene E. Vignon-Clementel 6
title Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation
spellingShingle Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation
Sanjay Pant
title_short Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation
title_full Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation
title_fullStr Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation
title_full_unstemmed Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation
title_sort Data assimilation and modelling of patient-specific single-ventricle physiology with and without valve regurgitation
author_id_str_mv 43b388e955511a9d1b86b863c2018a9f
author_id_fullname_str_mv 43b388e955511a9d1b86b863c2018a9f_***_Sanjay Pant
author Sanjay Pant
author2 Sanjay Pant
Chiara Corsini
Catriona Baker
Tain-Yen Hsia
Giancarlo Pennati
Irene E. Vignon-Clementel
format Journal article
container_title Journal of Biomechanics
container_volume 49
container_issue 11
container_start_page 2162
publishDate 2016
institution Swansea University
issn 0021-9290
doi_str_mv 10.1016/j.jbiomech.2015.11.030
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering
document_store_str 0
active_str 0
description A closed-loop lumped parameter model of blood circulation is considered for single-ventricle shunt physiology. Its parameters are estimated by an inverse problem based on patient-specific haemodynamics measurements. As opposed to a black-box approach, maximizing the number of parameters that are related to physically measurable quantities motivates the present model. Heart chambers are described by a single-fibre mechanics model, and valve function is modelled with smooth opening and closure. A model for valve prolapse leading to valve regurgitation is proposed. The method of data assimilation, in particular the unscented Kalman filter, is used to estimate the model parameters from time-varying clinical measurements. This method takes into account both the uncertainty in prior knowledge related to the parameters and the uncertainty associated with the clinical measurements. Two patient-specific cases – one without regurgitation and one with atrioventricular valve regurgitation – are presented. Pulmonary and systemic circulation parameters are successfully estimated, without assumptions on their relationships. Parameters governing the behaviour of heart chambers and valves are either fixed based on biomechanics, or estimated. Results of the inverse problem are validated qualitatively through clinical measurements or clinical estimates that were not included in the parameter estimation procedure. The model and the estimation method are shown to successfully capture patient-specific clinical observations, even with regurgitation, such as the double peaked nature of valvular flows and anomalies in electrocardiogram readings. Lastly, biomechanical implications of the results are discussed.
published_date 2016-07-26T03:42:48Z
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score 11.016235

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