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27 February 2009Simulation-based validation and arrival-time correction for Patlak analyses of perfusion-CT scans
Blood-brain-barrier (BBB) breakdown is a hypothesized mechanism for hemorrhagic transformation in acute stroke. The
Patlak analysis of a Perfusion Computed Tomography (PCT) scan measures the BBB permeability, but the method
yields higher estimates when applied to the first pass of the contrast bolus compared to a delayed phase. We present a
numerical phantom that simulates vascular and parenchymal time-attenuation curves to determine the validity of
permeability measurements obtained with different acquisition protocols. A network of tubes represents the major
cerebral arteries ipsi- and contralateral to an ischemic event. These tubes branch off into smaller segments that represent
capillary beds. Blood flow in the phantom is freely defined and simulated as non-Newtonian tubular flow. Diffusion of
contrast in the vessels and permeation through vessel walls is part of the simulation. The phantom allows us to compare
the results of a permeability measurement to the simulated vessel wall status. A Patlak analysis reliably detects areas
with BBB breakdown for acquisitions of 240s duration, whereas results obtained from the first pass are biased in areas of
reduced blood flow. Compensating for differences in contrast arrival times reduces this bias and gives good estimates of
BBB permeability for PCT acquisitions of 90-150s duration.
Jörg Bredno,Jason Hom,Thomas Schneider, andMax Wintermark
"Simulation-based validation and arrival-time correction for Patlak analyses of perfusion-CT scans", Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 72620G (27 February 2009); https://doi.org/10.1117/12.810959
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Jörg Bredno, Jason Hom, Thomas Schneider, Max Wintermark, "Simulation-based validation and arrival-time correction for Patlak analyses of perfusion-CT scans," Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 72620G (27 February 2009); https://doi.org/10.1117/12.810959