Population‐specific modelling of between/within‐subject flow variability in the carotid arteries of the elderly

Toni Lassila, Ali Sarrami‐Foroushani, Seyed Mostafa Hejazi, Alejandro F. Frangi

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Article numbere3271
Pages (from-to)1-13
Number of pages13
JournalInternational Journal for Numerical Methods in Biomedical Engineering
Volume36
Issue number1
Early online date5 Nov 2019
DOIs
Publication statusPublished - 27 Jan 2020

Keywords

  • cerebrovascular disease
  • computational fluid dynamics
  • Gaussian process models
  • patient-specific models
  • uncertainty quantification

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