Electronic Thesis and Dissertation Repository

Degree

Master of Science

Program

Medical Biophysics

Supervisor

Jackson, Dwayne N.

2nd Supervisor

Goldman, Daniel

Joint Supervisor

Abstract

The objective of this thesis was to optimize our technique for studying blood flow in arteriolar networks by including capillary resistance and venular network geometry. We aimed to validate our technique using experimental flow measurements and Murray’s law. First, arteriolar and venular networks were reconstructed from intravital videomicroscopy (IVVM) images of the gluteus maximus muscle, and capillary resistance was estimated and distributed to each terminal arteriole (TA) segment according to its diameter. Resistance for small arterioles and venules that were likely missed in our IVVM experiments were also added to each TA segment in our reconstructed networks based on measured branching properties of arteriolar and venular networks. We acquired fluorescent streaks for flow measurements in an arteriolar network, which validated flow simulations from our steady state, two-phase model. We found a strong match between measured arteriolar blood flow and predicted arteriolar flows using capillary resistance, venular geometry, and small-vessel resistance. Experimental data gave a Murray’s law exponent of 2.9, to which we compared predicted values from blood flow simulations. Using n=8 networks, we found a Murray’s law exponent of 2.78. Our results show that our network-oriented approach is moving towards more accurately predicting hemodynamic properties of arteriolar networks under baseline conditions.

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