Cardiac Modelling Techniques to Predict Future Heart Function and New Biomarkers in Acute Myocardial Infarction
Abstract
Fundamental to treatment planning for patients that have suffered myocardial infarction are predictive biomarkers and risk factors. Important among these in terms of a patient’s treatment plan or prognosis are the contractility of the damaged myofibers, final infarct volume, and poor infarct healing rate. Proposed and developed in this thesis are techniques to predict these biomarkers and risk factors using cardiac biomechanical modelling. One of the developed techniques was a CT compatible shape optimization technique which can predict the contraction force of healthy, and stunned myofibers within 6.3% and the distribution of potentially necrotic myofibers within 10% accuracy. The second study involved development of infarct healing network proposed to reduce the complexity of modeling hearts with myocardial infarction while also staging the healing rate and measure collagen concentration in the infarct region reasonably accurately. Finally, an evaluation of how best to measure cardiac output by indicator dilution theory was executed.