Overview of mathematical modeling of myocardial blood flow regulation.

The oxygen consumption by the heart and its extraction from the coronary arterial blood are the highest among all organs. Any increase in oxygen demand due to a change in heart metabolic activity requires an increase in coronary blood flow. This functional requirement of adjustment of coronary blood flow is mediated by coronary flow regulation to meet the oxygen demand without any discomfort, even under strenuous exercise conditions.

Effects of myocardial function and systemic circulation on regional coronary perfusion.

Cardiac-coronary interaction and the effects of its pathophysiological variations on spatial heterogeneity of coronary perfusion and myocardial work are still poorly understood. This hypothesis-generating study predicts spatial heterogeneities in both regional cardiac work and perfusion that offer a new paradigm on the vulnerability of the subendocardium to ischemia, particularly at the apex. We propose a mathematical and computational modeling framework to simulate the interaction of left ventricular mechanics, systemic circulation, and coronary microcirculation.

Morphometric Reconstruction of Coronary Vasculature Incorporating Uniformity of Flow Dispersion.

Experimental limitations in measurements of coronary flow in the beating heart have led to the development of models of reconstructed coronary trees. Previous coronary reconstructions relied primarily on anatomical data, including statistical morphometry (e.g.

Integrative model of coronary flow in anatomically based vasculature under myogenic, shear, and metabolic regulation.

Coronary blood flow is regulated to match the oxygen demand of myocytes in the heart wall. Flow regulation is essential to meet the wide range of cardiac workload. The blood flows through a complex coronary vasculature of elastic vessels having nonlinear wall properties, under transmural heterogeneous myocardial extravascular loading.

Reliability of structure tensors in representing soft tissues structure.

Structure tensors have been applied as descriptors of tissue morphology for constitutive modeling. Here the reliability of these tensors in representing tissues structure is investigated by model simulations of a few examples of generated and measured planar fiber orientation distributions. Reliability was evaluated by comparing the data with the orientation density distribution recovered from the structure tensor representation, and with a orientation density recovered from an alternative representation by Fourier series of spherical harmonics.