Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.618408
Title: Patient-specific models of cerebral aneurysm evolution
Author: Selimovic, Alisa
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2013
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Abstract:
A cerebral aneurysm (CA) is an abnormal distension of the wall of an artery in the brain, which results from arterial wall weakening. CAs are poorly understood, but are believed to be the result of a combination of biological and life-style factors. The low incidence of rupture coupled with risks of interventional treatments provide motivation for identifying and treating only those aneurysms at risk of rupture. Computational models of aneurysm evolution may provide great insight into CA disease mechanisms, and guide clinical decision-making. It is well known that vascular cells sense mechanical forces exerted by bloodflow (i.e. haemodynamic forces), which are translated into a myriad of intra- and inter-cellular responses. In this thesis, hypotheses on the role of the patient-specific haemodynamic environment on the evolution of CAs is examined. Arterial geometries are obtained from images of patient-specific vasculature, and the physiological aneurysm is virtually removed and replaced by a novel, fluid-solid-growth (FSG) model. The model incorporates a constitutive model for the artery, growth and remodelling (G&R) hypotheses for arterial wall constituents, and links between G&R and the haemodynamic environment, which is simulated utilising computational fluid dynamics. It is observed that coupling G&R to the patient-specific haemodynamic environment profoundly impacts the shape and size of the evolving aneurysm geometry; in some cases, the model aneurysm is qualitatively similar to the corresponding physiological aneurysm. This provides tentative support for the hypotheses on haemodynamics-induced G&R investigated here, and motivates the need for improved understanding of arterial adaptation to physiological conditions. This will facilitate the improvement and validation of the model, and may ultimately lead to predictive models with clinical application on a patient-specific basis.
Supervisor: Watton, Paul; Ventikos, Yiannis Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.618408  DOI: Not available
Keywords: Biomedical engineering ; cerebral aneurysm ; patient-specific model
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