Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.800068
Title: Mathematical modelling of calcium ions during ischaemic stroke
Author: Qian, George
ISNI:       0000 0004 8507 3304
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2019
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Abstract:
Stroke is a condition affecting over 100,000 people every year in the UK alone. There are two types of stroke: ischaemic, which is the more common and occurs when blood supply to the brain is blocked and haemorrhagic, where blood vessels in the brain burst, causing bleeding. After the occurrence of an ischaemic stroke, one typically observes three regions being formed, namely the ischaemic core, penumbra and the unaffected region. While cells in the ischaemic core die immediately due to lack of blood supply, there remains a chance to salvage those in the penumbra, as these cells are still supplied temporarily by peripheral vessels. Clinicians, however, still have difficulty identifying the penumbra, despite advances in medical technology. To this end, our goal is to create a mathematical model that uses cell calcium ion concentration as a biomarker to predict in these three regions of the brain, given some decrease in blood flow, which is a clinically measureable input. This would allow our model to be used as a diagnostic tool for clinicians to determine which areas to apply reperfusion. We find that our model is able to portray certain spatial inhomogeneities known as Turing patterns, which arise from one set of equations, with calcium concentration as its sole biomarker. This is a feature that, to our knowledge, has not been investigated in other models. The presence of Turing patterns allows us potentially to model the ischaemic core, penumbra and unaffected regions; however, the spatial inhomogeneities observed in our model simulations do not yet correspond to these regions due to the presence of higher-order modes. We, therefore, suggest ways to improve the model to make it a viable clinical tool.
Supervisor: Payne, Stephen Sponsor: Research Councils UK (RCUK) Digital Economy Programme
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.800068  DOI: Not available
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