Keywords: Perfusion, Quantitative Imaging, Whole brain blood flow simulation, perfusion modeling
Motivation: While experimental phantoms are useful for validating perfusion modeling, they lack the complexity of organs.
Goal(s): To construct an in-silico whole brain perfusion model and use it for assessing the estimation errors of a two-compartment perfusion model.
Approach: A large vessel segmentation obtained in a human subject is combined simulated arteries, veins and capillaries and their flow. Two-compartment modeling is then performed on the corresponding concentration maps computed and compared with the known ground truth.
Results: The data demonstrate an underestimation of flow (mean of -18.40%), likely due to the delay and dispersion effects related to the choice of a global AIF.
Impact: We demonstrate a detailed in-silico perfusion model that allows the investigate the accuracy of perfusion modeling methods.
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