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A physiologically realistic virtual patient database for the study of arterial haemodynamics
International Journal for Numerical Methods in Biomedical Engineering, Volume: 37, Issue: 10
Swansea University Authors: Perumal Nithiarasu , Sanjay Pant
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DOI (Published version): 10.1002/cnm.3497
Abstract
This study creates a physiologically realistic virtual patient database (VPD), representing the human arterial system, for the primary purpose of studying the effects of arterial disease on haemodynamics. A low dimensional representation of an anatomically detailed arterial network is outlined, and...
Published in: | International Journal for Numerical Methods in Biomedical Engineering |
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ISSN: | 2040-7939 2040-7947 |
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Wiley
2021
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URI: | https://cronfa.swan.ac.uk/Record/cronfa56785 |
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This combination of the arterial network parameters (representing a virtual patient) and the haemodynamics waveforms of pressure and flow-rates at various locations (representing functional response and potential measurements that can be acquired in the virtual patient) makes up the VPD. While 75,000 VPs are sampled from the posterior distribution, 10,000 are discarded as the initial burn-in period of the MCMC sampler. A further 12,857 VPs are subsequently removed due to the presence of negative average flow-rate, reducing the VPD to 52,143. Due to undesirable behaviour observed in some VPs—asymmetric under- and over-damped pressure and flow-rate profiles in left and right sides of the arterial system—a filter is proposed to remove VPs showing such behaviour. Post application of the filter, the VPD has 28,868 subjects. It is shown that the methodology is appropriate by comparing the VPD statistics to those reported in literature across real populations. 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2022-08-15T11:22:09.2234253 v2 56785 2021-05-04 A physiologically realistic virtual patient database for the study of arterial haemodynamics 3b28bf59358fc2b9bd9a46897dbfc92d 0000-0002-4901-2980 Perumal Nithiarasu Perumal Nithiarasu true false 43b388e955511a9d1b86b863c2018a9f 0000-0002-2081-308X Sanjay Pant Sanjay Pant true false 2021-05-04 ACEM This study creates a physiologically realistic virtual patient database (VPD), representing the human arterial system, for the primary purpose of studying the effects of arterial disease on haemodynamics. A low dimensional representation of an anatomically detailed arterial network is outlined, and a physiologically realistic posterior distribution for its parameters constructed through the use of a Bayesian approach. This approach combines both physiological/geometrical constraints and the available measurements reported in the literature. A key contribution of this work is to present a framework for including all such available information for the creation of virtual patients (VPs). The Markov Chain Monte Carlo (MCMC) method is used to sample random VPs from this posterior distribution, and the pressure and flow-rate profiles associated with each VP computed through a physics based model of pulse wave propagation. This combination of the arterial network parameters (representing a virtual patient) and the haemodynamics waveforms of pressure and flow-rates at various locations (representing functional response and potential measurements that can be acquired in the virtual patient) makes up the VPD. While 75,000 VPs are sampled from the posterior distribution, 10,000 are discarded as the initial burn-in period of the MCMC sampler. A further 12,857 VPs are subsequently removed due to the presence of negative average flow-rate, reducing the VPD to 52,143. Due to undesirable behaviour observed in some VPs—asymmetric under- and over-damped pressure and flow-rate profiles in left and right sides of the arterial system—a filter is proposed to remove VPs showing such behaviour. Post application of the filter, the VPD has 28,868 subjects. It is shown that the methodology is appropriate by comparing the VPD statistics to those reported in literature across real populations. Generally, a good agreement between the two is found while respecting physiological/geometrical constraints. Journal Article International Journal for Numerical Methods in Biomedical Engineering 37 10 Wiley 2040-7939 2040-7947 virtual patients; stenosis; aneurysm; pulse wave haemodynamics; MCMC; screening; virtual patient database 8 10 2021 2021-10-08 10.1002/cnm.3497 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University EPSRC, Grant/Award Numbers: EP/N509553/1, EP/R010811/1 2022-08-15T11:22:09.2234253 2021-05-04T13:18:57.2464835 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering Gareth Jones 1 Jim Parr 2 Perumal Nithiarasu 0000-0002-4901-2980 3 Sanjay Pant 0000-0002-2081-308X 4 56785__19795__af29f37159f0450582fd794577d69d5a.pdf 56785.pdf 2021-05-04T13:20:54.1608829 Output 8318564 application/pdf Accepted Manuscript true 2022-05-10T00:00:00.0000000 true eng http://creativecommons.org/licenses/by-nc-nd/4.0/ 76 Sanjay Pant Sanjay.Pant@Swansea.ac.uk true https://doi.org/10.5281/zenodo.4549763 false |
title |
A physiologically realistic virtual patient database for the study of arterial haemodynamics |
spellingShingle |
A physiologically realistic virtual patient database for the study of arterial haemodynamics Perumal Nithiarasu Sanjay Pant |
title_short |
A physiologically realistic virtual patient database for the study of arterial haemodynamics |
title_full |
A physiologically realistic virtual patient database for the study of arterial haemodynamics |
title_fullStr |
A physiologically realistic virtual patient database for the study of arterial haemodynamics |
title_full_unstemmed |
A physiologically realistic virtual patient database for the study of arterial haemodynamics |
title_sort |
A physiologically realistic virtual patient database for the study of arterial haemodynamics |
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3b28bf59358fc2b9bd9a46897dbfc92d 43b388e955511a9d1b86b863c2018a9f |
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3b28bf59358fc2b9bd9a46897dbfc92d_***_Perumal Nithiarasu 43b388e955511a9d1b86b863c2018a9f_***_Sanjay Pant |
author |
Perumal Nithiarasu Sanjay Pant |
author2 |
Gareth Jones Jim Parr Perumal Nithiarasu Sanjay Pant |
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International Journal for Numerical Methods in Biomedical Engineering |
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37 |
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2040-7939 2040-7947 |
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10.1002/cnm.3497 |
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Wiley |
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description |
This study creates a physiologically realistic virtual patient database (VPD), representing the human arterial system, for the primary purpose of studying the effects of arterial disease on haemodynamics. A low dimensional representation of an anatomically detailed arterial network is outlined, and a physiologically realistic posterior distribution for its parameters constructed through the use of a Bayesian approach. This approach combines both physiological/geometrical constraints and the available measurements reported in the literature. A key contribution of this work is to present a framework for including all such available information for the creation of virtual patients (VPs). The Markov Chain Monte Carlo (MCMC) method is used to sample random VPs from this posterior distribution, and the pressure and flow-rate profiles associated with each VP computed through a physics based model of pulse wave propagation. This combination of the arterial network parameters (representing a virtual patient) and the haemodynamics waveforms of pressure and flow-rates at various locations (representing functional response and potential measurements that can be acquired in the virtual patient) makes up the VPD. While 75,000 VPs are sampled from the posterior distribution, 10,000 are discarded as the initial burn-in period of the MCMC sampler. A further 12,857 VPs are subsequently removed due to the presence of negative average flow-rate, reducing the VPD to 52,143. Due to undesirable behaviour observed in some VPs—asymmetric under- and over-damped pressure and flow-rate profiles in left and right sides of the arterial system—a filter is proposed to remove VPs showing such behaviour. Post application of the filter, the VPD has 28,868 subjects. It is shown that the methodology is appropriate by comparing the VPD statistics to those reported in literature across real populations. Generally, a good agreement between the two is found while respecting physiological/geometrical constraints. |
published_date |
2021-10-08T08:01:25Z |
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11.04748 |