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 Chappell^2,3, 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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