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A data-driven model to study utero-ovarian blood flow physiology during pregnancy

Jason Carson Orcid Logo, Michael Lewis, Dareyoush Rassi, Raoul van Loon Orcid Logo

Biomechanics and Modeling in Mechanobiology, Volume: 18, Pages: 1155 - 1176

Swansea University Authors: Jason Carson Orcid Logo, Michael Lewis, Raoul van Loon Orcid Logo

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Abstract

In this paper, we describe a mathematical model of the cardiovascular system in human pregnancy. An automated, closed-loop 1D–0D modelling framework was developed, and we demonstrate its efficacy in (1) reproducing measured multi-variate cardiovascular variables (pulse pressure, total peripheral res...

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Published in: Biomechanics and Modeling in Mechanobiology
ISSN: 1617-7959 1617-7940
Published: 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa48907
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first_indexed 2019-02-19T20:06:25Z
last_indexed 2023-01-11T14:24:44Z
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spelling 2022-12-18T09:59:30.9899860 v2 48907 2019-02-19 A data-driven model to study utero-ovarian blood flow physiology during pregnancy c1f2c28fbe6a41c5134b45abde5abb93 0000-0001-6634-9123 Jason Carson Jason Carson true false b59c8f5c056bac7e6995385f22ad1639 Michael Lewis Michael Lewis true false 880b30f90841a022f1e5bac32fb12193 0000-0003-3581-5827 Raoul van Loon Raoul van Loon true false 2019-02-19 MEDE In this paper, we describe a mathematical model of the cardiovascular system in human pregnancy. An automated, closed-loop 1D–0D modelling framework was developed, and we demonstrate its efficacy in (1) reproducing measured multi-variate cardiovascular variables (pulse pressure, total peripheral resistance and cardiac output) and (2) providing automated estimates of variables that have not been measured (uterine arterial and venous blood flow, pulse wave velocity, pulsatility index). This is the first model capable of estimating volumetric blood flow to the uterus via the utero-ovarian communicating arteries. It is also the first model capable of capturing wave propagation phenomena in the utero-ovarian circulation, which are important for the accurate estimation of arterial stiffness in contemporary obstetric practice. The model will provide a basis for future studies aiming to elucidate the physiological mechanisms underlying the dynamic properties (changing shapes) of vascular flow waveforms that are observed with advancing gestation. This in turn will facilitate the development of methods for the earlier detection of pathologies that have an influence on vascular structure and behaviour. Journal Article Biomechanics and Modeling in Mechanobiology 18 1155 1176 1617-7959 1617-7940 Pregnancy, 1D–0D cardiovascular network, Physiological adaptation, Data-driven modelling, Utero-ovarian flow 15 8 2019 2019-08-15 10.1007/s10237-019-01135-3 COLLEGE NANME Biomedical Engineering COLLEGE CODE MEDE Swansea University 2022-12-18T09:59:30.9899860 2019-02-19T14:34:07.5572351 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised Jason Carson 0000-0001-6634-9123 1 Michael Lewis 2 Dareyoush Rassi 3 Raoul van Loon 0000-0003-3581-5827 4 48907__17598__301fcae1dfa4461eb0edeb930e564a8b.pdf 48907.pdf 2020-06-29T16:39:49.7776353 Output 3393403 application/pdf Version of Record true This article is distributed under the terms of the Creative Commons Attribution 4.0 International License true eng http://creativecommons.org/licenses/by/4.0/
title A data-driven model to study utero-ovarian blood flow physiology during pregnancy
spellingShingle A data-driven model to study utero-ovarian blood flow physiology during pregnancy
Jason Carson
Michael Lewis
Raoul van Loon
title_short A data-driven model to study utero-ovarian blood flow physiology during pregnancy
title_full A data-driven model to study utero-ovarian blood flow physiology during pregnancy
title_fullStr A data-driven model to study utero-ovarian blood flow physiology during pregnancy
title_full_unstemmed A data-driven model to study utero-ovarian blood flow physiology during pregnancy
title_sort A data-driven model to study utero-ovarian blood flow physiology during pregnancy
author_id_str_mv c1f2c28fbe6a41c5134b45abde5abb93
b59c8f5c056bac7e6995385f22ad1639
880b30f90841a022f1e5bac32fb12193
author_id_fullname_str_mv c1f2c28fbe6a41c5134b45abde5abb93_***_Jason Carson
b59c8f5c056bac7e6995385f22ad1639_***_Michael Lewis
880b30f90841a022f1e5bac32fb12193_***_Raoul van Loon
author Jason Carson
Michael Lewis
Raoul van Loon
author2 Jason Carson
Michael Lewis
Dareyoush Rassi
Raoul van Loon
format Journal article
container_title Biomechanics and Modeling in Mechanobiology
container_volume 18
container_start_page 1155
publishDate 2019
institution Swansea University
issn 1617-7959
1617-7940
doi_str_mv 10.1007/s10237-019-01135-3
college_str Faculty of Science and Engineering
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hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
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department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
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description In this paper, we describe a mathematical model of the cardiovascular system in human pregnancy. An automated, closed-loop 1D–0D modelling framework was developed, and we demonstrate its efficacy in (1) reproducing measured multi-variate cardiovascular variables (pulse pressure, total peripheral resistance and cardiac output) and (2) providing automated estimates of variables that have not been measured (uterine arterial and venous blood flow, pulse wave velocity, pulsatility index). This is the first model capable of estimating volumetric blood flow to the uterus via the utero-ovarian communicating arteries. It is also the first model capable of capturing wave propagation phenomena in the utero-ovarian circulation, which are important for the accurate estimation of arterial stiffness in contemporary obstetric practice. The model will provide a basis for future studies aiming to elucidate the physiological mechanisms underlying the dynamic properties (changing shapes) of vascular flow waveforms that are observed with advancing gestation. This in turn will facilitate the development of methods for the earlier detection of pathologies that have an influence on vascular structure and behaviour.
published_date 2019-08-15T03:59:36Z
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