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Quantitative perfusion maps of cerebral blood flow, cerebral blood volume, and transit time generated using dynamic imaging data enable physicians to evaluate and prescribe the optimal plan of care for stroke patients. Validation is needed to increase the accuracy and reproducibility of this data, which can vary depending on the scanning technique and post-processing algorithm. In this work, we expand the XCAT brain phantom to incorporate a realistic model of the contrast agent dynamics in the cerebral vasculature and establish the ground truth to which the perfusion maps can be compared. For a specific stroke case, each tissue region's flow demand is calculated and used to determine the feeding flow in the upstream arteries and draining flow in the downstream veins. Using the flow values and a contrast agent injection curve, the model calculates the input and output concentration curves for each structure in the brain. The concentration curve within each structure is then calculated as the difference between the total amount of contrast agent that has entered and exited the structure up until that timepoint. A dynamic simulation framework utilizes the curves to define the contrast agent concentration within the phantom at each time point and generates simulated CT perfusion imaging data sets compatible with commercially available post-processing software. This development provides a realistic set of ground truth test data that enables quantitative validation and optimization of perfusion imaging and post-processing methods for stroke assessment.
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