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A data-driven model to study utero-ovarian blood flow physiology during pregnancy
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6647440/ https://www.ncbi.nlm.nih.gov/pubmed/30838498 http://dx.doi.org/10.1007/s10237-019-01135-3 |
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author | Carson, Jason Lewis, Michael Rassi, Dareyoush Van Loon, Raoul |
author_facet | Carson, Jason Lewis, Michael Rassi, Dareyoush Van Loon, Raoul |
author_sort | Carson, Jason |
collection | PubMed |
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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10237-019-01135-3) contains supplementary material, which is available to authorised users. |
format | Online Article Text |
id | pubmed-6647440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-66474402019-08-06 A data-driven model to study utero-ovarian blood flow physiology during pregnancy Carson, Jason Lewis, Michael Rassi, Dareyoush Van Loon, Raoul Biomech Model Mechanobiol Original Paper 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10237-019-01135-3) contains supplementary material, which is available to authorised users. Springer Berlin Heidelberg 2019-03-05 2019 /pmc/articles/PMC6647440/ /pubmed/30838498 http://dx.doi.org/10.1007/s10237-019-01135-3 Text en © Springer-Verlag GmbH Germany, part of Springer Nature 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Paper Carson, Jason Lewis, Michael Rassi, Dareyoush Van Loon, Raoul A data-driven model to study utero-ovarian blood flow physiology during pregnancy |
title | 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_short | A data-driven model to study utero-ovarian blood flow physiology during pregnancy |
title_sort | data-driven model to study utero-ovarian blood flow physiology during pregnancy |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6647440/ https://www.ncbi.nlm.nih.gov/pubmed/30838498 http://dx.doi.org/10.1007/s10237-019-01135-3 |
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