Abstract #1835

Reliability and Reproducibility of Neurochemical Profiles Obtained with sLASER and STEAM at 3T and 7T in Lower and Upper Limb Regions

Zeinab Eftekhari^1,2, Thomas B Shaw^1,3, Dinesh K Deelchand⁴, Małgorzata Marjańska⁴, Wolfgang Bogner⁵, and Markus Barth^1,2,3

¹Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia, ²ARC Training Centre for Innovation in Biomedical Imaging Technology (CIBIT), The University of Queensland, Brisbane, Australia, ³School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia, ⁴Centre for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States, ⁵High-field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria

Synopsis

Keywords: Spectroscopy, Spectroscopy, sLASER, STEAM, 3T and 7T, Longitudinal Reproducibility, High-Field MRI, Ultrahigh-Field MRI, Magnetic Resonance Spectroscopy

Motivation: The test-retest of STEAM and sLASER at both fields using the same subjects has not been investigated.

Goal(s): The aim was to evaluate the reliability using Intraclass Correlation Coefficients(ICC) and reproducibility using Coefficient of Variations (CV%) of Glutamate, Glutamine, and N-acetyl-aspartate quantification at 3T and 7T in the human motor cortex using sLASER and STEAM sequences.

Approach: Subjects were scanned a week apart using both sequences at both field strengths. Voxel locations were in Paracentral Lobule (PCL) and Precentral Gyrus (PrCG).

Results: sLASER, particularly at 7T, demonstrated superior performance in both regions within a reasonable timeframe,making it the recommended sequence for longitudinal studies.

Impact: This study’s findings offer valuable insights for researchers conducting longitudinal studies using MRS. The improved reliability and reproducibility of the sLASER technique, particularly at 7T, enable more precise tracking of disease progression, potentially leading to improved disease tracking.

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