The goal of this study is to better simulate microscopic and voxel-based dynamic contrast enhancement in magnetic resonance imaging. Specifically, errors imposed by the traditional two-compartment model are reduced by introducing a novel Kroghcylinder network. The two-compartment model was developed for macroscopicpharmacokinetic analysis of dynamic contrast enhancement and generalizing it to voxeldimensions, due to the significant decrease in scale, imposes physiologically unrealisticassumptions. In the project, a system of microscopic exchange between plasma andextravascular-extracellular space is built while numerically simulating the local contrastagent flow between and inside image elements. To do this, tissue parameter maps were created, contrast agent was introduced to the tissue via a flow lattice, and various data sets were simulated. The effects of sources, tissue heterogeneity, and the contribution of individual tissue parameters to an image are modeled. Further, the study attempts to demonstrate the effects of a priori flow maps on image contrast, indicating that flow data is as important as permeability data when analyzing tumor contrast enhancement. In addition, the simulations indicate that it may be possible toobtain tumor-type diagnostic information by acquiring both flow and permeability data.
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Using a voxel-based krogh cylinder array to simulate microvascular contrast enhancement