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Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement
BACKGROUND: Pressure contour analysis is commonly used to estimate cardiac performance for patients suffering from cardiovascular dysfunction in the intensive care unit. However, the existing techniques for continuous estimation of stroke volume (SV) from pressure measurement can be unreliable durin...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5404318/ https://www.ncbi.nlm.nih.gov/pubmed/28438216 http://dx.doi.org/10.1186/s12938-017-0341-z |
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author | Kamoi, Shun Pretty, Christopher Balmer, Joel Davidson, Shaun Pironet, Antoine Desaive, Thomas Shaw, Geoffrey M. Chase, J. Geoffrey |
author_facet | Kamoi, Shun Pretty, Christopher Balmer, Joel Davidson, Shaun Pironet, Antoine Desaive, Thomas Shaw, Geoffrey M. Chase, J. Geoffrey |
author_sort | Kamoi, Shun |
collection | PubMed |
description | BACKGROUND: Pressure contour analysis is commonly used to estimate cardiac performance for patients suffering from cardiovascular dysfunction in the intensive care unit. However, the existing techniques for continuous estimation of stroke volume (SV) from pressure measurement can be unreliable during hemodynamic instability, which is inevitable for patients requiring significant treatment. For this reason, pressure contour methods must be improved to capture changes in vascular properties and thus provide accurate conversion from pressure to flow. METHODS: This paper presents a novel pressure contour method utilizing pulse wave velocity (PWV) measurement to capture vascular properties. A three-element Windkessel model combined with the reservoir–wave concept are used to decompose the pressure contour into components related to storage and flow. The model parameters are identified beat-to-beat from the water-hammer equation using measured PWV, wave component of the pressure, and an estimate of subject-specific aortic dimension. SV is then calculated by converting pressure to flow using identified model parameters. The accuracy of this novel method is investigated using data from porcine experiments (N = 4 Pietrain pigs, 20–24.5 kg), where hemodynamic properties were significantly altered using dobutamine, fluid administration, and mechanical ventilation. In the experiment, left ventricular volume was measured using admittance catheter, and aortic pressure waveforms were measured at two locations, the aortic arch and abdominal aorta. RESULTS: Bland–Altman analysis comparing gold-standard SV measured by the admittance catheter and estimated SV from the novel method showed average limits of agreement of ±26% across significant hemodynamic alterations. This result shows the method is capable of estimating clinically acceptable absolute SV values according to Critchely and Critchely. CONCLUSION: The novel pressure contour method presented can accurately estimate and track SV even when hemodynamic properties are significantly altered. Integrating PWV measurements into pressure contour analysis improves identification of beat-to-beat changes in Windkessel model parameters, and thus, provides accurate estimate of blood flow from measured pressure contour. The method has great potential for overcoming weaknesses associated with current pressure contour methods for estimating SV. |
format | Online Article Text |
id | pubmed-5404318 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54043182017-04-27 Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement Kamoi, Shun Pretty, Christopher Balmer, Joel Davidson, Shaun Pironet, Antoine Desaive, Thomas Shaw, Geoffrey M. Chase, J. Geoffrey Biomed Eng Online Research BACKGROUND: Pressure contour analysis is commonly used to estimate cardiac performance for patients suffering from cardiovascular dysfunction in the intensive care unit. However, the existing techniques for continuous estimation of stroke volume (SV) from pressure measurement can be unreliable during hemodynamic instability, which is inevitable for patients requiring significant treatment. For this reason, pressure contour methods must be improved to capture changes in vascular properties and thus provide accurate conversion from pressure to flow. METHODS: This paper presents a novel pressure contour method utilizing pulse wave velocity (PWV) measurement to capture vascular properties. A three-element Windkessel model combined with the reservoir–wave concept are used to decompose the pressure contour into components related to storage and flow. The model parameters are identified beat-to-beat from the water-hammer equation using measured PWV, wave component of the pressure, and an estimate of subject-specific aortic dimension. SV is then calculated by converting pressure to flow using identified model parameters. The accuracy of this novel method is investigated using data from porcine experiments (N = 4 Pietrain pigs, 20–24.5 kg), where hemodynamic properties were significantly altered using dobutamine, fluid administration, and mechanical ventilation. In the experiment, left ventricular volume was measured using admittance catheter, and aortic pressure waveforms were measured at two locations, the aortic arch and abdominal aorta. RESULTS: Bland–Altman analysis comparing gold-standard SV measured by the admittance catheter and estimated SV from the novel method showed average limits of agreement of ±26% across significant hemodynamic alterations. This result shows the method is capable of estimating clinically acceptable absolute SV values according to Critchely and Critchely. CONCLUSION: The novel pressure contour method presented can accurately estimate and track SV even when hemodynamic properties are significantly altered. Integrating PWV measurements into pressure contour analysis improves identification of beat-to-beat changes in Windkessel model parameters, and thus, provides accurate estimate of blood flow from measured pressure contour. The method has great potential for overcoming weaknesses associated with current pressure contour methods for estimating SV. BioMed Central 2017-04-24 /pmc/articles/PMC5404318/ /pubmed/28438216 http://dx.doi.org/10.1186/s12938-017-0341-z Text en © The Author(s) 2017 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Kamoi, Shun Pretty, Christopher Balmer, Joel Davidson, Shaun Pironet, Antoine Desaive, Thomas Shaw, Geoffrey M. Chase, J. Geoffrey Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement |
title | Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement |
title_full | Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement |
title_fullStr | Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement |
title_full_unstemmed | Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement |
title_short | Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement |
title_sort | improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5404318/ https://www.ncbi.nlm.nih.gov/pubmed/28438216 http://dx.doi.org/10.1186/s12938-017-0341-z |
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