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Using personalised cardiovascular models to identify new diagnostic predictors for pre-eclampsia / CLAUDIA POPP

Swansea University Author: CLAUDIA POPP

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Abstract

Haemodynamic adaptations play a crucial role in uteroplacental perfusion during pregnancy. In particular, modifications of the utero-ovarian arterial network cause a significant increase in blood volume distributed to the placenta and foetus. Failure to make these cardiovascular modifications result...

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Published: Swansea, Wales, UK 2023
Institution: Swansea University
Degree level: Master of Research
Degree name: MSc by Research
Supervisor: van Loon, Raoul.
URI: https://cronfa.swan.ac.uk/Record/cronfa64040
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Failure to make these cardiovascular modifications results in complicated pregnancies caused by different disorders such as hypertension, pre-eclampsia, intrauterine growth restriction (IUGR), and placental insufficiency. In pre-eclampsia, the modifications of the utero-ovarian arterial network are unsuccessful and cause less blood volume to be distributed to the placenta and foetus. Pre-eclampsia is a hypertensive disorder that is still not fully understood, and clinicians still fail at identifying pre-eclamptic women during controls, especially at differentiating between hypertensive women and pre-eclamptic women. One reason for this is that clinicians rely heavily on blood pressure when diagnosing pre-eclampsia, and this biomarker has similar readings for both pre-eclampsia and hypertension. As part of the diagnosis of pre-eclampsia, proteinuria is used. In order to improve the diagnosis of pre-eclampsia, other biomarkers are being researched. A dataset of 21 patients was used to find novel biomarkers that can classify pre-eclampsia. The dataset is divided into two groups: uncomplicated pregnancies with hypertensive women and complicated pregnancies with pre-eclampsia. A computational model of the cardiovascular system is used to simulate blood and pressure solutions based on patient-specific observations in order to develop a new biomarker. The model employs 1D modelling which incorporates a wave intensity analysis that models forward and backward waves to provide more precise predictions of wave propagation across the artery system, particularly in the utero-ovarian system. The proposed biomarkers will include dimensionless terms formed by global maternal parameters such as systolic blood pressure, stroke volume, pulse wave velocity, etc., or local uterine parameters such as pressure and velocity in specific vessels of the uterine system. Afterwards, their ability as a classifier of pre-eclampsia will be investigated. Besides this, a case study of the prone position in pregnancy and its effects on cardiovascular changes will be carried out. To do this, the computational model will be used to study what happens when a pregnant woman is positioned in the prone position and how vital metrics like blood pressure and cardiac output are altered. It was found that the biomarkers based on the radial and arcuate arteries have a better classification ability for pre-eclampsia, even higher than the Doppler-measured Resistance Index (RI) and Pulsatility Index (PI). The novelty of this work is the introduction of new biomarkers through the use of a computational model, as well as the demonstration of the dependability and use of 1D modelling in pregnancy. The model demonstrated how biomarkers that could not be measured clinically may be easily calculated using 1D modelling and provide critical information about the utero-ovarian circulation. Future work should concentrate on changing the existing solver into a much faster and simpler solver, as well as validating the biomarkers in a larger dataset.</abstract><type>E-Thesis</type><journal/><volume/><journalNumber/><paginationStart/><paginationEnd/><publisher/><placeOfPublication>Swansea, Wales, UK</placeOfPublication><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic/><keywords>Pre-eclampsia, computational modelling, cardiovascular system, pregnancy, biomarkers</keywords><publishedDay>10</publishedDay><publishedMonth>7</publishedMonth><publishedYear>2023</publishedYear><publishedDate>2023-07-10</publishedDate><doi/><url/><notes/><college>COLLEGE NANME</college><CollegeCode>COLLEGE CODE</CollegeCode><institution>Swansea University</institution><supervisor>van Loon, Raoul.</supervisor><degreelevel>Master of Research</degreelevel><degreename>MSc by Research</degreename><apcterm/><funders/><projectreference/><lastEdited>2023-08-07T16:28:16.4807019</lastEdited><Created>2023-08-07T16:16:05.9738003</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Engineering and Applied Sciences - Biomedical Engineering</level></path><authors><author><firstname>CLAUDIA</firstname><surname>POPP</surname><order>1</order></author></authors><documents><document><filename>64040__28253__99aa2e824a86418ba4f1c5f2a7598e4d.pdf</filename><originalFilename>2023_Popp_CM.final.64040.pdf</originalFilename><uploaded>2023-08-07T16:26:07.5347658</uploaded><type>Output</type><contentLength>4174255</contentLength><contentType>application/pdf</contentType><version>E-Thesis – open access</version><cronfaStatus>true</cronfaStatus><documentNotes>Copyright: The Author, Claudia M. 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spelling v2 64040 2023-08-07 Using personalised cardiovascular models to identify new diagnostic predictors for pre-eclampsia 390258a988aabbfb83515b831a281289 CLAUDIA POPP CLAUDIA POPP true false 2023-08-07 Haemodynamic adaptations play a crucial role in uteroplacental perfusion during pregnancy. In particular, modifications of the utero-ovarian arterial network cause a significant increase in blood volume distributed to the placenta and foetus. Failure to make these cardiovascular modifications results in complicated pregnancies caused by different disorders such as hypertension, pre-eclampsia, intrauterine growth restriction (IUGR), and placental insufficiency. In pre-eclampsia, the modifications of the utero-ovarian arterial network are unsuccessful and cause less blood volume to be distributed to the placenta and foetus. Pre-eclampsia is a hypertensive disorder that is still not fully understood, and clinicians still fail at identifying pre-eclamptic women during controls, especially at differentiating between hypertensive women and pre-eclamptic women. One reason for this is that clinicians rely heavily on blood pressure when diagnosing pre-eclampsia, and this biomarker has similar readings for both pre-eclampsia and hypertension. As part of the diagnosis of pre-eclampsia, proteinuria is used. In order to improve the diagnosis of pre-eclampsia, other biomarkers are being researched. A dataset of 21 patients was used to find novel biomarkers that can classify pre-eclampsia. The dataset is divided into two groups: uncomplicated pregnancies with hypertensive women and complicated pregnancies with pre-eclampsia. A computational model of the cardiovascular system is used to simulate blood and pressure solutions based on patient-specific observations in order to develop a new biomarker. The model employs 1D modelling which incorporates a wave intensity analysis that models forward and backward waves to provide more precise predictions of wave propagation across the artery system, particularly in the utero-ovarian system. The proposed biomarkers will include dimensionless terms formed by global maternal parameters such as systolic blood pressure, stroke volume, pulse wave velocity, etc., or local uterine parameters such as pressure and velocity in specific vessels of the uterine system. Afterwards, their ability as a classifier of pre-eclampsia will be investigated. Besides this, a case study of the prone position in pregnancy and its effects on cardiovascular changes will be carried out. To do this, the computational model will be used to study what happens when a pregnant woman is positioned in the prone position and how vital metrics like blood pressure and cardiac output are altered. It was found that the biomarkers based on the radial and arcuate arteries have a better classification ability for pre-eclampsia, even higher than the Doppler-measured Resistance Index (RI) and Pulsatility Index (PI). The novelty of this work is the introduction of new biomarkers through the use of a computational model, as well as the demonstration of the dependability and use of 1D modelling in pregnancy. The model demonstrated how biomarkers that could not be measured clinically may be easily calculated using 1D modelling and provide critical information about the utero-ovarian circulation. Future work should concentrate on changing the existing solver into a much faster and simpler solver, as well as validating the biomarkers in a larger dataset. E-Thesis Swansea, Wales, UK Pre-eclampsia, computational modelling, cardiovascular system, pregnancy, biomarkers 10 7 2023 2023-07-10 COLLEGE NANME COLLEGE CODE Swansea University van Loon, Raoul. Master of Research MSc by Research 2023-08-07T16:28:16.4807019 2023-08-07T16:16:05.9738003 Faculty of Science and Engineering School of Engineering and Applied Sciences - Biomedical Engineering CLAUDIA POPP 1 64040__28253__99aa2e824a86418ba4f1c5f2a7598e4d.pdf 2023_Popp_CM.final.64040.pdf 2023-08-07T16:26:07.5347658 Output 4174255 application/pdf E-Thesis – open access true Copyright: The Author, Claudia M. Popp, 2023. true eng
title Using personalised cardiovascular models to identify new diagnostic predictors for pre-eclampsia
spellingShingle Using personalised cardiovascular models to identify new diagnostic predictors for pre-eclampsia
CLAUDIA POPP
title_short Using personalised cardiovascular models to identify new diagnostic predictors for pre-eclampsia
title_full Using personalised cardiovascular models to identify new diagnostic predictors for pre-eclampsia
title_fullStr Using personalised cardiovascular models to identify new diagnostic predictors for pre-eclampsia
title_full_unstemmed Using personalised cardiovascular models to identify new diagnostic predictors for pre-eclampsia
title_sort Using personalised cardiovascular models to identify new diagnostic predictors for pre-eclampsia
author_id_str_mv 390258a988aabbfb83515b831a281289
author_id_fullname_str_mv 390258a988aabbfb83515b831a281289_***_CLAUDIA POPP
author CLAUDIA POPP
author2 CLAUDIA POPP
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hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Biomedical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Biomedical Engineering
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description Haemodynamic adaptations play a crucial role in uteroplacental perfusion during pregnancy. In particular, modifications of the utero-ovarian arterial network cause a significant increase in blood volume distributed to the placenta and foetus. Failure to make these cardiovascular modifications results in complicated pregnancies caused by different disorders such as hypertension, pre-eclampsia, intrauterine growth restriction (IUGR), and placental insufficiency. In pre-eclampsia, the modifications of the utero-ovarian arterial network are unsuccessful and cause less blood volume to be distributed to the placenta and foetus. Pre-eclampsia is a hypertensive disorder that is still not fully understood, and clinicians still fail at identifying pre-eclamptic women during controls, especially at differentiating between hypertensive women and pre-eclamptic women. One reason for this is that clinicians rely heavily on blood pressure when diagnosing pre-eclampsia, and this biomarker has similar readings for both pre-eclampsia and hypertension. As part of the diagnosis of pre-eclampsia, proteinuria is used. In order to improve the diagnosis of pre-eclampsia, other biomarkers are being researched. A dataset of 21 patients was used to find novel biomarkers that can classify pre-eclampsia. The dataset is divided into two groups: uncomplicated pregnancies with hypertensive women and complicated pregnancies with pre-eclampsia. A computational model of the cardiovascular system is used to simulate blood and pressure solutions based on patient-specific observations in order to develop a new biomarker. The model employs 1D modelling which incorporates a wave intensity analysis that models forward and backward waves to provide more precise predictions of wave propagation across the artery system, particularly in the utero-ovarian system. The proposed biomarkers will include dimensionless terms formed by global maternal parameters such as systolic blood pressure, stroke volume, pulse wave velocity, etc., or local uterine parameters such as pressure and velocity in specific vessels of the uterine system. Afterwards, their ability as a classifier of pre-eclampsia will be investigated. Besides this, a case study of the prone position in pregnancy and its effects on cardiovascular changes will be carried out. To do this, the computational model will be used to study what happens when a pregnant woman is positioned in the prone position and how vital metrics like blood pressure and cardiac output are altered. It was found that the biomarkers based on the radial and arcuate arteries have a better classification ability for pre-eclampsia, even higher than the Doppler-measured Resistance Index (RI) and Pulsatility Index (PI). The novelty of this work is the introduction of new biomarkers through the use of a computational model, as well as the demonstration of the dependability and use of 1D modelling in pregnancy. The model demonstrated how biomarkers that could not be measured clinically may be easily calculated using 1D modelling and provide critical information about the utero-ovarian circulation. Future work should concentrate on changing the existing solver into a much faster and simpler solver, as well as validating the biomarkers in a larger dataset.
published_date 2023-07-10T16:28:12Z
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