A dynamic computational model of pulsatile brain blood flow.

Saroay, Kajal 2023. A dynamic computational model of pulsatile brain blood flow. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

Declining vessel health in the brain is associated with the development and progression of cerebrovascular disease. As arteries become less compliant with age, their ability to dampen pulsatile energy decreases. A model of blood flow across the cerebrovascular network was developed in this thesis to understand how cardiac pulsatile energy is dissipated in the brain. Existing models are limited in their ability to model local changes in flow following changes in blood volume in compliant vessels. A computational model was developed to simulate dynamic flow in a branched network of cerebral vessels, with the aim of modelling pulsatile flow across the network. An overview of cerebral anatomy and haemodynamics is presented in Chapter 1. In Chapter 2, methods for measuring blood flow are outlined and compared. Existing models are evaluated in Chapter 3. The development of the computational model is described in Chapter 3. An existing model was replicated and extended to incorporate dynamic changes in a network of compliant vessels following changes in pressure across time. The results from steady state simulations, which were carried out as a first step validation are presented in Chapter 5. The development of the Plausible Vessel Network is described in Chapter 6. Results from dynamic simulations, assessing shape changes in flow across the Plausible Vessel Network are presented in Chapter 7. A proof of concept to estimate vessel compliance using MRI data in the model is outlined in Chapter 8. Results presented in this thesis suggest that many parameters need to be set to realistically model blood flow in cerebral vessels including compliance and pulse wave velocity across the network. Further research into setting these parameters will help increase the accuracy, and thus the utility of the model to gain an improved understanding of the deterioration of cerebrovascular health with age and disease.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Schools > Physics and Astronomy
Subjects:	Q Science > QC Physics
Uncontrolled Keywords:	Pulsatility, Pulsatile blood flow, Arterial stiffness, Vessel compliance, Pulse wave velocity, Cerebrovascular health, DIMAC MRI, Computational Modelling
Funders:	Engineering & Physical Sciences Research Council (EPSRC)
Date of First Compliant Deposit:	22 May 2025
Last Modified:	22 May 2025 15:18
URI:	https://orca.cardiff.ac.uk/id/eprint/178424

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