Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.631827
Title: Development of an in silico methodology for the multiscale modelling of atherosclerosis
Author: Di Tomaso, G.
ISNI:       0000 0004 5357 8412
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2014
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Abstract:
Atherosclerosis is the main cause of mortality and morbidity in Western World, causing more death and disability than all the types of cancer. Given its high potential danger it is of major importance to better understand the causes of atherosclerosis, which are linked to both the lipoprotein metabolism and haemodynamics in arteries. Together with in vivo and in vitro experiments, in silico models and simulations allow for a better insight and understanding of the mechanisms of atherosclerosis formation. A multiscale model coming from the integration of a fluid dynamics model, and a biochemical model is here presented for the modelling of atherosclerosis at its early stage. An artery-specific approach was used in the fluid dynamics model for modelling the interaction between arterial endothelium and blood flow. The low density Lipoprotein (LDL) oxidation leading to immune-response (cytokines, monocytes/macrophages) and foam cell formation and accumulation at the basis of plaque formation was described in the biochemical model. Integration of these modelling approaches led to the creation of an effective tool for the modelling of atherosclerosis plaque development, the atherosclerosis remodelling cycle. The impact on the disease development of different mean blood LDL concentrations and arterial geometries was analysed. The atherosclerosis remodelling cycle was applied for patient-specific simulation of plaque formations in a patient presenting with atherosclerosis formations in the aorta and peripheral arteries. When compared with the multi-slice computed tomography (MSCT) images, the model highlighted atherosclerosis-prone areas, where plaques were found in vivo, with 91.7% accuracy and replicated 41.7% of the plaques presenting in the patients.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.631827  DOI: Not available
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