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Abstract #4205

Q-space Trajectory Imaging with tensor-valued diffusion encoding for clinical usage in temporal lobe epilepsy

Jan Malte Oeschger1,2, Francisco J. Fritz2, Luke J. Edwards3, Markus Nilsson 4, Filip Szczepankiewicz4, Arthur Chakwizira4, Ileana Jelescu5, Quentin Uhl5, and Siawoosh Mohammadi1,2,3
1Institute for Neuroradiology, Lübeck University, Lübeck, Germany, 2Institute of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 3Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 4Department of Medical Radiation Physics, Lund University, Lund, Sweden, 5Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland

Synopsis

Keywords: Microstructure, Diffusion Modeling, QTI, free waveform, Epilepsy

Motivation: Drug-resistant temporal lobe epilepsy requires reliable identification of epileptogenic brain regions for surgical planning, here Q-space Trajectory Imaging (QTI) could provide microstructural information complementary to clinical MRI.

Goal(s): Assessing the reproducibility of key QTI parameters (µFA, MKA, MKI) across two distinct protocols to determine future protocol choice.

Approach: Four subjects underwent QTI imaging on a 3T MRI scanner, including one scan-rescan. Two protocols were compared to evaluate variability across subjects, regions, and scan-rescan.

Results: Protocol 2, with higher SNR, showed lower scan-rescan variability, while Protocol 1’s elevated MKI values in certain regions suggested potential false positives, highlighting the need for careful protocol selection.

Impact: This study helps scientists select more reliable QTI diffusion protocols for TLE imaging, possibly enabling more accurate identification of epileptogenic brain regions for surgical intervention. It is demonstrated that small changes in acquisition parameters can significantly impact parameter estimates.

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