The main task of the heart is to ensure an adequate blood flow. In order to maintain the blood flow, the heart itself also needs to be supplied with sufficient blood flow. This is done via the left and right coronary arteries. Optimal coronary flow is crucial for maintaining cardiac function. However, coronary blood flow can be impaired due to coronary heart disease (CHD). CHD is characterized by atheromatous plaque formation throughout a long period of time resulting in narrow segments (stenosis) in the coronary arteries. With growing plaque formation the coronary lumen area decreases. As a consequence of the lumen area reduction, additional pressure loss over the stenosis occurs resulting in lower blood flow for the corresponding coronary artery. The consequence of this is that the myocardium fed by the coronary artery receives less blood flow which may increase the risk for ischemia and myocardial infarction. Patients with CHD may show symptoms such as pain on the chest, discomfort during stress and exercise or even at rest for severe cases. Treatment options for CHD depend on things such as stenosis severity, stenosis location and patient history. The goal of the thesis was twofold. First goal is to reduce computational time of models by investigating the feasibility of lower order models. Second goal was investigating the influence of parameter uncertainty on the computed output of interest of coronary models.

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