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Personalising cardiovascular network models in pregnancy: A two‐tiered parameter estimation approach
Uterine artery Doppler waveforms are often studied to determine whether a patient is at risk of developing pathologies such as pre‐eclampsia. Many uterine waveform indices have been developed, which attempt to relate characteristics of the waveform with the physiological adaptation of the maternal c...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286682/ https://www.ncbi.nlm.nih.gov/pubmed/31799783 http://dx.doi.org/10.1002/cnm.3267 |
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author | Carson, Jason Warrander, Lynne Johnstone, Edward van Loon, Raoul |
author_facet | Carson, Jason Warrander, Lynne Johnstone, Edward van Loon, Raoul |
author_sort | Carson, Jason |
collection | PubMed |
description | Uterine artery Doppler waveforms are often studied to determine whether a patient is at risk of developing pathologies such as pre‐eclampsia. Many uterine waveform indices have been developed, which attempt to relate characteristics of the waveform with the physiological adaptation of the maternal cardiovascular system, and are often suggested to be an indicator of increased placenta resistance and arterial stiffness. Doppler waveforms of four patients, two of whom developed pre‐eclampsia, are compared with a comprehensive closed‐loop model of pregnancy. The closed‐loop model has been previously validated but has been extended to include an improved parameter estimation technique that utilises systolic and diastolic blood pressure, cardiac output, heart rate, and pulse wave velocity measurements to adapt model resistances, compliances, blood volume, and the mean vessel areas in the main systemic arteries. The shape of the model‐predicted uterine artery velocity waveforms showed good agreement with the characteristics observed in the patient Doppler waveforms. The personalised models obtained now allow a prediction of the uterine pressure waveforms in addition to the uterine velocity. This allows for a more detailed mechanistic analysis of the waveforms, eg, wave intensity analysis, to study existing clinical indices. The findings indicate that to accurately estimate arterial stiffness, both pulse pressure and pulse wave velocities are required. In addition, the results predict that patients who developed pre‐eclampsia later in pregnancy have larger vessel areas in the main systemic arteries compared with the two patients who had normal pregnancy outcomes. |
format | Online Article Text |
id | pubmed-9286682 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92866822022-07-19 Personalising cardiovascular network models in pregnancy: A two‐tiered parameter estimation approach Carson, Jason Warrander, Lynne Johnstone, Edward van Loon, Raoul Int J Numer Method Biomed Eng Special Issue Articles Uterine artery Doppler waveforms are often studied to determine whether a patient is at risk of developing pathologies such as pre‐eclampsia. Many uterine waveform indices have been developed, which attempt to relate characteristics of the waveform with the physiological adaptation of the maternal cardiovascular system, and are often suggested to be an indicator of increased placenta resistance and arterial stiffness. Doppler waveforms of four patients, two of whom developed pre‐eclampsia, are compared with a comprehensive closed‐loop model of pregnancy. The closed‐loop model has been previously validated but has been extended to include an improved parameter estimation technique that utilises systolic and diastolic blood pressure, cardiac output, heart rate, and pulse wave velocity measurements to adapt model resistances, compliances, blood volume, and the mean vessel areas in the main systemic arteries. The shape of the model‐predicted uterine artery velocity waveforms showed good agreement with the characteristics observed in the patient Doppler waveforms. The personalised models obtained now allow a prediction of the uterine pressure waveforms in addition to the uterine velocity. This allows for a more detailed mechanistic analysis of the waveforms, eg, wave intensity analysis, to study existing clinical indices. The findings indicate that to accurately estimate arterial stiffness, both pulse pressure and pulse wave velocities are required. In addition, the results predict that patients who developed pre‐eclampsia later in pregnancy have larger vessel areas in the main systemic arteries compared with the two patients who had normal pregnancy outcomes. John Wiley and Sons Inc. 2020-01-13 2021-11 /pmc/articles/PMC9286682/ /pubmed/31799783 http://dx.doi.org/10.1002/cnm.3267 Text en © 2019 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons, Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Special Issue Articles Carson, Jason Warrander, Lynne Johnstone, Edward van Loon, Raoul Personalising cardiovascular network models in pregnancy: A two‐tiered parameter estimation approach |
title | Personalising cardiovascular network models in pregnancy: A two‐tiered parameter estimation approach |
title_full | Personalising cardiovascular network models in pregnancy: A two‐tiered parameter estimation approach |
title_fullStr | Personalising cardiovascular network models in pregnancy: A two‐tiered parameter estimation approach |
title_full_unstemmed | Personalising cardiovascular network models in pregnancy: A two‐tiered parameter estimation approach |
title_short | Personalising cardiovascular network models in pregnancy: A two‐tiered parameter estimation approach |
title_sort | personalising cardiovascular network models in pregnancy: a two‐tiered parameter estimation approach |
topic | Special Issue Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286682/ https://www.ncbi.nlm.nih.gov/pubmed/31799783 http://dx.doi.org/10.1002/cnm.3267 |
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