Computational Modelling of Branching Arteriolar Networks using Constrained Constructive Optimization
Abstract
The microcirculation plays a critical role in tissue blood flow distribution and is thus a topic of importance for understanding organ pathophysiology. As an alternative to experimental investigations of microvasculature, this thesis introduces a computational algorithm based on constrained constructive optimization (CCO) which aims to generate visually and statistically realistic branching arteriolar network architecture in healthy skeletal muscle tissue. The algorithm includes a list of user-specified adjustable model parameters to generate networks characteristic of different skeletal muscle tissues. Geometric (including mean vessel diameters, lengths, and numbers of bifurcations per order, Horton’s Law ratios, and fractal dimension) and hemodynamic (Murray’s Law exponent and hematocrit) properties of the generated networks matched experimental values from literature when compared for validation. The resulting algorithm is a valuable tool for investigating network architecture and blood flow in various skeletal muscles.