Lassila, T orcid.org/0000-0001-8947-1447, Sarrami-Foroushani, A, Hejazi, S et al. (1 more author) (2020) Population‐specific modelling of between/within‐subject flow variability in the carotid arteries of the elderly. International Journal for Numerical Methods in Biomedical Engineering, 36 (1). e3271. ISSN 2040-7939
Abstract
Computational fluid dynamics models are increasingly proposed for assisting the diagnosis and management of vascular diseases. Ideally, patient‐specific flow measurements are used to impose flow boundary conditions. When patient‐specific flow measurements are unavailable, mean values of flow measurements across small cohorts are used as normative values. In reality, both the between‐subjects and within‐subject flow variabilities are large. Consequently, neither one‐shot flow measurements nor mean values across a cohort are truly indicative of the flow regime in a given person. We develop models for both the between‐subjects and within‐subject variability of internal carotid flow. A log‐linear mixed effects model is combined with a Gaussian process to model the between‐subjects flow variability, while a lumped parameter model of cerebral autoregulation is used to model the within‐subject flow variability in response to heart rate and blood pressure changes. The model parameters are identified from carotid ultrasound measurements in a cohort of 103 elderly volunteers. We use the models to study intracranial aneurysm flow in 54 subjects under rest and exercise and conclude that OSI, a common wall shear‐stress derived quantity in vascular CFD studies, may be too sensitive to flow fluctuations to be a reliable biomarker.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019, John Wiley & Sons, Ltd. This is the peer reviewed version of the following article: Lassila, T, Sarrami‐Foroushani, A, Hejazi, S, Frangi, AF. Population‐specific modelling of between/within‐subject flow variability in the carotid arteries of the elderly. Int J Numer Meth Biomed Engng. 2020; 36:e3271, which has been published in final form at https://doi.org/10.1002/cnm.3271. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. |
Keywords: | cerebrovascular disease; computational fluid dynamics; Gaussian process models; patient‐specific models; uncertainty quantification |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EU - European Union 777119 |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 Oct 2019 16:40 |
Last Modified: | 05 Nov 2020 01:39 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1002/cnm.3271 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:151501 |