Validation of a Non-invasive Inverse Problem-Solving Method for Stroke Volume.
Authors
Bikia, Vasiliki
McEniery, Carmel M
Roussel, Emma Marie
Rovas, Georgios
Pagoulatou, Stamatia
Wilkinson, Ian B
Stergiopulos, Nikolaos
Publication Date
2021Journal Title
Front Physiol
ISSN
1664-042X
Publisher
Frontiers Media SA
Volume
12
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Bikia, V., McEniery, C. M., Roussel, E. M., Rovas, G., Pagoulatou, S., Wilkinson, I. B., & Stergiopulos, N. (2021). Validation of a Non-invasive Inverse Problem-Solving Method for Stroke Volume.. Front Physiol, 12 https://doi.org/10.3389/fphys.2021.798510
Abstract
Stroke volume (SV) is a major biomarker of cardiac function, reflecting ventricular-vascular coupling. Despite this, hemodynamic monitoring and management seldomly includes assessments of SV and remains predominantly guided by brachial cuff blood pressure (BP). Recently, we proposed a mathematical inverse-problem solving method for acquiring non-invasive estimates of mean aortic flow and SV using age, weight, height and measurements of brachial BP and carotid-femoral pulse wave velocity (cfPWV). This approach relies on the adjustment of a validated one-dimensional model of the systemic circulation and applies an optimization process for deriving a quasi-personalized profile of an individual's arterial hemodynamics. Following the promising results of our initial validation, our first aim was to validate our method against measurements of SV derived from magnetic resonance imaging (MRI) in healthy individuals covering a wide range of ages (n = 144; age range 18-85 years). Our second aim was to investigate whether the performance of the inverse problem-solving method for estimating SV is superior to traditional statistical approaches using multilinear regression models. We showed that the inverse method yielded higher agreement between estimated and reference data (r = 0.83, P < 0.001) in comparison to the agreement achieved using a traditional regression model (r = 0.74, P < 0.001) across a wide range of age decades. Our findings further verify the utility of the inverse method in the clinical setting and highlight the importance of physics-based mathematical modeling in improving predictive tools for hemodynamic monitoring.
Keywords
Physiology, vascular aging, cardiac output, mathematical modeling, data assimilation, non-invasive monitoring
Identifiers
External DOI: https://doi.org/10.3389/fphys.2021.798510
This record's URL: https://www.repository.cam.ac.uk/handle/1810/333798
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.
Recommended or similar items
The current recommendation prototype on the Apollo Repository will be turned off on 03 February 2023. Although the pilot has been fruitful for both parties, the service provider IKVA is focusing on horizon scanning products and so the recommender service can no longer be supported. We recognise the importance of recommender services in supporting research discovery and are evaluating offerings from other service providers. If you would like to offer feedback on this decision please contact us on: support@repository.cam.ac.uk