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Background The manifestation of chronic pain and psychological impairments are related to alterations of neurotransmitter metabolism in cerebral pain processing regions, e.g., anterior cingular cortex (ACC), insula. Magnetic resonance spectroscopy ((1)H-MRS) enables in vivo quantification of neurotransmitters in the brain and was applied in this study to examine the hypothesized chronic pain-related imbalance between excitatory (glutamatergic) and inhibitory (GABA-ergic) neurotransmitter turnovers in the brain of patients with nonspecific chronic pain. Materials and methods A total of 19 patients with nonspecific chronic (> 3 months) back pain and 19 age- and gender-matched healthy subjects participated in this study. Glutamate and GABA as well as glutamate/GABA ratios were determined in the ACC and insula using (1)H-MRS. Sociodemographic, psychological, and pain-related features were measured with standardized questionnaires. Results There was a strong variance of glutamate/GABA ratios for both patients and healthy subjects with no significant difference between the two groups. Regression analysis revealed certain significant predictors, such as anxiety as causal variable for reduced glutamate and depression and age as predictors for reduced GABA in ACC. In the patient group, intensity of pain was a significant predictor for glutamate and GABA levels in the insula. Conclusions Despite the uniform diagnosis of nonspecific chronic back pain, we observed a strong variance of neurotransmitters in cerebral pain processing regions. It is necessary to include psychological as well as clinical parameters (e.g., intensity of pain or depression) for a proper interpretation of neurotransmitter turnovers.

Referencing metabolite intensities to the tissue water intensity is commonly applied to determine metabolite concentrations from in vivo (1)H-MRS brain data. However, since the water concentration and relaxation properties differ between grey matter, white matter and cerebrospinal fluid (CSF), the volume fractions of these compartments have to be considered in MRS voxels.The impact of partial volume correction was validated by phantom measurements in voxels containing mixtures of solutions with different NAA and water concentrations as well as by analyzing in vivo (1)H-MRS brain data acquired with various voxel compositions.Phantom measurements indicated substantial underestimation of NAA concentrations when assuming homogeneously composed voxels, especially for voxels containing solution, which simulated CSF (error: ≤ 92%). This bias was substantially reduced by taking into account voxel composition (error: ≤ 10%). In the in vivo study, tissue correction reduced the overall variation of quantified metabolites by up to 35% and revealed the expected metabolic differences between various brain tissues.Tissue composition affects extraction of metabolite concentrations and may cause misinterpretations when comparing measurements performed with different voxel sizes. This variation can be reduced by considering the different tissue types by means of combined analysis of spectroscopic and imaging data.