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Title: Quantitative computational evaluation of cardiac and coronary physiology
Author: Sciola, Martina Ignazia
ISNI:       0000 0004 7428 160X
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2017
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Background: Coronary artery disease (CAD) is a clinical condition characterised by an obstruction of the blood flow to the myocardium. Coronary angiography is the gold standard clinical procedure to assess the coronary stenosis based on the vessel anatomy. Fractional flow reserve (FFR) describes the physiological severity of the stenosis during maximum coronary flow, induced by adenosine infusion. Hypothesis Mathematical models can be used to represent the cardiovascular system and be employed as investigative and predictive tools to assess CAD in individual patients. Aims: To support the computational estimation of coronary FFR (vFFR) by characterising and predicting the response to the administration of adenosine in terms of the myocardial resistance and by investigating correlations between patient parameters and myocardial resistance. Methods & Results: 1) A zero-dimensional (0D) cardiovascular model has been developed starting from published models to simulate adenosine-induced hyperaemia as a function and is shown to reproduce qualitatively the effects described in the literature using generic parameters. A sensitivity analysis was performed to introduce and test assumptions, including the decoupling of the systemic model from the local coronary compartment, which later facilitates the process of tuning model parameters to individual patient data. 2) Clinical data from patients with CAD have been used to personalise the systemic cardiovascular system and subsequently, at a coronary level, to represent the individualspecific response to adenosine. The 0D coronary model included representation of a vessel stenosis, characterised by a computational fluid dynamics analysis, and the myocardial impedance. The nature of the response of individual patients to the administration of adenosine was quantitatively characterised in terms of the underlying parameters described by the model. The myocardium adenosine concentration profile and resistance were used to identify correlation with patient parameters. No statistically significant associations were found between the type of response and observations in the clinical records. 3) Considering the lack of consensus on the definition of FFR under hyperaemia, an algorithm has been developed to objectively identify stable and minimum FFR. Conclusions: It is possible to use a 0D model to support the individual characterisation of the response to adenosine, and thus to provide insight into the nature of the physiological response to this drug. However, this approach does not support the reliable prediction of this response in individuals with CAD from baseline measurements that are made in the routine clinical pathway. Arising from this work, a robust algorithm has been developed to identify the stable and minimum FFR, which can be used to improve clinical decision making.
Supervisor: Hose, Rodney ; Lawford, Patricia ; Gunn, Julian Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available