Abstract #4945

Combined estimation of dispersion and macrovascular signal in multi-PLD pCASL data using a two-component model

Merlijn C.E. van der Plas¹, Michael Chappell^2,3, and Matthias J.P. van Osch¹

¹C.J.Gorter Center for high field MRI, Department of Radiology, Leiden University Medical Center, 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

In pCASL a well-defined, box-shaped bolus is created at the labeling plane and for quantification this shape is assumed to be preserved, however, in reality this shape will be dispersed. With multi-timepoint data, the effects of dispersion can be observed in the macrovascular component, which can be separated from the tissue component using a two-component model. In this study the combined estimation of dispersion and macrovascular signal was investigated. When a gamma distribution dispersion kernel was incorporated into the two-component model, a significant decrease in CBF values was found, while a significant increase in macrovascular signal was observed.

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