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Ziegs, T.

Publications and source records attributed to Ziegs, T..

3 recordsLinked to original sources

Mapping of Glutamate Metabolism using 1H FID-MRSI after oral Administration of Glc at 9.4 T

Glutamate is the major excitatory transmitter in the brain and malfunction of the related metabolism is associated with various neurological diseases and disorders. The observation of labeling changes in the spectra after the administration of a 13C labelled tracer is a common tool to gain better insights into the function of the metabolic system. But so far, only a very few studies presenting the labelling effects in more than two voxels to show the spatial dependence of metabolism. In the present work, the labeling effects were measured in a transversal plane in the human brain using ultra-short TE and TR 1H FID-MRSI. The measurement set-up was most simple: The [1-13C]Glc was administered orally instead of intravenous and the spectra were measured with a pure 1H technique without the need of a 13C channel (as Boumezbeur et al. demonstrated in 2004). Thus, metabolic maps and enrichment curves could be obtained for more metabolites and in more voxels than ever before in human brain. Labeling changes could be observed in [4-13C]glutamate, [3-13C]glutamate+glutamine, [2-13C]glutamate+glutamine, [4-13C]glutamine, [2,3-13C]aspartate and [6-13C]N-acetyl aspartate with a high temporal (3.6 min) and spatial resolution (32x32 grid with nominal voxel size of 0.33 L) in five volunteers.

neuroscience↗

Test-retest reproducibility of human brain multi-slice 1H FID-MRSI data at 9.4 T after optimization of lipid regularization, macromolecular model and spline baseline stiffness

* PurposeThis study analyzes the effects of retrospective lipid suppression, a simulated macromolecular prior knowledge and different spline baseline stiffness values on 9.4 T multi-slice proton FID-MRSI data spanning the whole cerebrum of human brain and its reproducibility of metabolite ratio (/tCr) maps for 10 brain metabolites. * MethodsMeasurements were performed twice on five volunteers using a non-accelerated FID MRSI 2D sequence at 9.4 T. The effects of retrospective lipid L2-regularization, macromolecular spectrum and different LCModel baseline flexibilities on SNR, FWHM, fitting residual, CRLB and the concentration ratio maps were investigated. Intra-subject, inter-session coefficient of variation of the mean metabolite ratios (/tCr) of each slice was calculated. * ResultsL2-regularization provided effective suppression of lipid-artifacts, but should be avoided if no artifacts are detected. Transversal, sagittal and coronal of many metabolite ratio maps correspond to anatomically expected concentration relations in gray and white matter for the majority of the cerebrum when using a flexible baseline in LCModel fit. Additionally, results from the second measurements of the same subjects show that slice positioning and data quality correlate significantly to the first measurement. * ConclusionConcentration ratio maps (/tCr) for 4 metabolites (tCho, NAA, Glu, mI) spanning the majority and six metabolites (NAAG, GABA, GSH, Tau, Gln, Asp) covering 32 mm in the upper part of the brain were acquired at 9.4 T using multi-slice FID MRSI with retrospective lipid suppression, a macromolecular spectrum and a flexible LCModel baseline.

neuroscience↗

Dynamic observation of 2H labeled compounds in the human brain with 1H versus 2H magnetic resonance spectroscopy at 9.4T

The metabolic pathway of [6,6-2H2]-labeled glucose was investigated with two different techniques. The first technique used direct detection of deuterium applying Deuterium Metabolic Imaging (DMI). The second technique used the indirect detection of deuterium with proton MR spectroscopy (MRS) called Quantitative Exchanged-label Turnover (QELT) MRS. For the first time, time-resolved data was acquired for both techniques in the same healthy human subjects and directly compared. The time-curves were used in a kinetic model to estimate rates of the metabolic pathway of glucose. Two different kinetic models were compared. One included only DMI data, the second one combined DMI and QELT. For the first model, a tricarboxylic acid (TCA) cycle rate of 0.69 {+/-} 0.10 mol{middle dot}min-1{middle dot}g-1 was determined. For the second model, the estimated TCA cycle rate was 0.68 {+/-} 0.12 mol{middle dot}min-1{middle dot}g-1. In addition, the rate of glutamine synthesis from glutamate could be estimated with model 2 (0.51 {+/-} 0.15 mol{middle dot}min-1{middle dot}g-1). The sensitivity of both methods was evaluated and compared to alternative techniques.

neuroscience↗