Abstract #1401

Validation of an ASL processing pipeline accounting for low SNR and the presence of an EPI artifact, using simulated and real data.

Maria-Eleni Dounavi^1,2, Aneurin J. Kennerley^2,3, Esben Thade Petersen^4,5, and Iain D. Wilkinson^1,2

¹Academic Unit of Radiology, University of Sheffield, Sheffield, United Kingdom, ²Neuroimaging in Cardiovascular Disease (NICAD) Network, University of Sheffield, Sheffield, United Kingdom, ³Department of Psychology, University of Sheffield, Sheffield, United Kingdom, ⁴Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital, Hvidovre, Denmark, ⁵Center for Magnetic Resonance, DTU Elektro, Technical University of Denmark, Lyngby, Denmark

This study aimed to optimize a processing pipeline for QUASAR ASL. We have focused on 3 aspects: the assignment of AIFs in voxels; dealing with voxels having excessive values potentially due to an EPI artifact; and minimization of partial volume effects. Simulations showed that GM CBF values closer to the ground truth are obtained by using AIFs in a distance double than the nearest-neighbor AIF to every voxel. In terms of an EPI artifact present in the analysis, we have shown that identification and exclusion of influenced voxels with a developed algorithm, results in values closer to the expected ones.

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