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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 Dounavi1,2, Aneurin J. Kennerley2,3, Esben Thade Petersen4,5, and Iain D. Wilkinson1,2

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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