Journal article 1010 views 108 downloads
A data-driven model to study utero-ovarian blood flow physiology during pregnancy
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Michael Lewis,
Dareyoush Rassi,
Raoul van Loon
Biomechanics and Modeling in Mechanobiology, Volume: 18, Pages: 1155 - 1176
Swansea University Authors:
Jason Carson , Michael Lewis, Raoul van Loon
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DOI (Published version): 10.1007/s10237-019-01135-3
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...
| Published in: | Biomechanics and Modeling in Mechanobiology |
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| ISSN: | 1617-7959 1617-7940 |
| Published: |
2019
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa48907 |
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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 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. |
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| Keywords: |
Pregnancy, 1D–0D cardiovascular network, Physiological adaptation, Data-driven modelling, Utero-ovarian flow |
| College: |
Faculty of Science and Engineering |
| Start Page: |
1155 |
| End Page: |
1176 |