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Abstract #0025

Validation of the estimation of the macrovascular contribution in multi-timepoint arterial spin labeling MRI using a two-component model

Merlijn van der Plas1, Sophie Schmid1, Martin Craig2, Michael Chappell2,3, and Matthias van Osch1
1Radiology, C.J. Gorter Center for High Field MRI, Leiden, Netherlands, 2Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, 3Institute of Biomedical Engineering, Research Council UK (EP/P012361/1), University of Oxford, Oxford, United Kingdom

A two-component kinetic model allows for the separation of the macrovascular and tissue signal. This model relies on the availability of multi-timepoint data and generates cerebral blood flow, arterial blood volume and arterial transit time maps. The goal of this study was to validate this separation of the macrovascular and tissue signal. A 4D-ASL angiography and densely sampled ASL data were acquired and fitted with different model settings. Fitting the 4D-ASL angiography with a macrovascular component showed the best fit for the model with gamma dispersion included but with limited freedom to change the dispersion parameters.

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