Distributions of proton MR-detected metabolites have been mapped throughout the brain in a group of normal subjects using a volumetric MR spectroscopic imaging (MRSI) acquisition with an interleaved water reference. Data were processed with intensity and spatial normalization to enable voxel-based analysis methods to be applied across a group of subjects. Results demonstrate significant regional, tissue, and genderdependent variations of brain metabolite concentrations, and variations of these distributions with normal aging. The greatest alteration of metabolites with age was observed for whitematter choline and creatine. An example of the utility of the normative metabolic reference information is then demonstrated for analysis of data acquired from a subject who suffered a traumatic brain injury. This study demonstrates the ability to obtain proton spectra from a wide region of the brain and to apply fully automated processing methods. Proton MR spectroscopy (MRS) enables the detection of a number of tissue metabolites that provide sensitive markers of disease or injury, making these techniques of considerable interest for clinical diagnostic purposes and particularly for studies in the brain. The acquisition and analysis of MRS data have several technical challenges that compromise the spatial resolution and accuracy of the resultant metabolite values. Furthermore, metabolic changes with disease and injury can frequently be subtle and diffuse, with the result that metabolite images may not be visually interpretable in the sense of a structural MRI. Therefore, the analysis of MRS data greatly benefits from comparison against a known reference signal.Since in vivo MRS measurements are dependent on the acquisition method used, the reference data must be acquired in an identical manner to that of the data under analysis. It is also necessary to take into account normal variations in metabolite concentrations; for example, variations in metabolite concentrations between tissue type, across different brain regions, and changes with age are well documented (1-14). Other reports have indicated differences in metabolite concentrations with gender, lateralization (15), intelligence quotient (IQ) (16), and associations with smoking and alcohol consumption (17). To account for these factors, results are commonly compared against data obtained from the same location in a group of control subjects matched to the study group under investigation. However, although many studies have reported metabolite values from normal control subjects, these values can rarely be used as the reference information for other investigations. For example, published values using single-voxel spectroscopy (SVS) measurements are limited to only a few brain regions, and acquisition parameters, analysis methods, and subject selection criteria, such as age, vary considerably, making it unlikely that existing data can be used as reference information for a new investigation. Additionally, a sufficient number of measurements must be acquired to accoun...

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The reproducibility of serial measurements using a volumetric proton MR Spectroscopic Imaging (MRSI) acquisition implemented at 3 Tesla and with lipid suppression by inversion-recovery has been evaluated. Data were acquired from two subjects at five time points, and processed using fully-automated procedures that included rigid registration between studies. This data were analyzed to determine coefficients of variance (COV) for each metabolite and for metabolite ratio images based on an individual voxel analysis, as well as for average and grey-matter and whitematter values from atlas-defined brain regions. The volumetric MRSI acquisition was found to obtain data of sufficient quality for analysis over 70±6% of the total brain volume, and spatial distributions of the resultant COV values were found to reflect the known distributions of susceptibility-induced magnetic field inhomogeneity. Median values of the resultant voxel-based COVs were 6.2%, 7.2%, and 9.7% for N-acetylaspartate, creatine, and choline respectively. The corresponding mean values obtained following averaging over lobar-scale brain regions within the cerebrum were 3.5%, 3.7%, and 5.2%. These results indicate that longitudinal volumetric MRSI studies with post-acquisition registration can provide an intra-subject reproducibility for voxelbased analyses that is comparable to previously-reported single-voxel MRS measurements, while additionally enabling increased sensitivity by averaging over larger tissue volumes.

Purpose The aim of this study was to evaluate volumetric proton magnetic resonance spectroscopic imaging (MRSI) for localization of epileptogenic foci in neocortical epilepsy. Methods Twenty-five subjects reporting seizures considered to be of neocortical origin were recruited to take part in a 3-Tesla MR study that included high-resolution structural MRI and a whole-brain MRSI acquisition. Using a fully-automated MRSI processing protocol, maps for signal-intensity normalized N-Acetylaspartate (NAA), creatine, and choline were created, together with the relative volume fraction of grey-matter, white-matter, and CSF within each MRSI voxel. Analyses were performed using visual observation of the metabolite and metabolite ratio maps; voxel-based calculation of differences in these metabolite maps relative to normal controls; comparison of average grey- and white-matter metabolite values over each lobar volume; and examination of relative left-right asymmetry factors by brain region. Results Data from fourteen subjects were suitable for inclusion in the analysis. Eight subjects had MRI-visible pathologies that were associated with decreases in NAA/Creatine, which extended beyond the volume indicated by the MRI. Five subjects demonstrated no significant metabolic alterations using any of the analysis methods, and one subject had no findings on MRI or MRSI. Conclusions This proof of principle study supports previous evidence that alterations of MR-detected brain metabolites can be detected in tissue areas affected by neocortical seizure activity, while additionally demonstrating advantages of the volumetric MRSI approach.