Computational biophysical modelling for the optimisation of cardiac magnetic resonance perfusion imaging protocols

Myocardial infarction (MI) is a severe condition that occurs when blood flow is restricted or stopped to a part of the heart, causing damage to the heart muscle. Resulting injury to the heart can include fibrosis and necrosis of myocytes, which overtime can affect the ability of the heart to pump efficiently, ultimately leading to heart failure in some, but not all, patients. Thus, there is a need to understand the processes that are responsible for causing this damage, and to consequently understand the differing clinical outcomes that are observed. This then provides an opportunity for deriving patient-specific treatments that will limit these negative outcomes.
This project will employ mathematical modelling and computational simulation of the various cellular processes that occur during MI, with the aims of providing a proof of principle of a metric or computational tool that will provide diagnostic support to clinicians when treating patients with suspected MI.
It is proposed to use ordinary differential equation models of the cellular processes, and where appropriate partial differential equation models of cardiac mechanics, which will be parameterised by data collected from a series of porcine experiments performed by collaborators at the Translational Biomedical Research Centre, University of Bristol. This data will comprise both blood biomarker and quantitative imaging data, and as the data collection will occur both during the MI and the subsequent period, the data will provide ample means to validate these models' predictive capabilities. A broader aim of this project is to create models that can be validated using larger data sets initially, and ultimately be taken forward to test using clinical data.