Reproducibility and effect of tissue composition on cerebellar γ-aminobutyric acid (GABA) MRS in an elderly population.

MRS provides a valuable tool for the non-invasive detection of brain γ-aminobutyric acid (GABA) in vivo. GABAergic dysfunction has been observed in the aging cerebellum. The study of cerebellar GABA changes is of considerable interest in understanding certain age-related motor disorders. However, little is known about the reproducibility of GABA MRS in an aged population. Therefore, this study aimed to explore the feasibility and reproducibility of GABA MRS in the aged cerebellum at 3.0 T and to examine the effect of differing tissue composition on GABA measurements. MRI and (1)H MRS examinations were performed on 10 healthy elderly volunteers (mean age, 75.2 ± 6.5 years) using a 3.0-T Siemens Tim Trio scanner. Among them, five subjects were scanned twice to assess the short-term reproducibility. The MEGA-PRESS (Mescher-Garwood point-resolved spectroscopy) J-editing sequence was used for GABA detection in two volumes of interest (VOIs) in the left and right cerebellar dentate. MRS data processing and quantification were performed with LCModel 6.3-0L using two separate basis sets, generated from density matrix simulations using published values for chemical shifts and J couplings. Raw metabolite levels from LCModel outputs were corrected for cerebrospinal fluid contamination and relaxation. GABA-edited spectra yielded robust and stable GABA measurements with averaged intra-individual coefficients of variation for corrected GABA+ between 4.0 ± 2.8% and 13.4 ± 6.3%, and inter-individual coefficients of variation between 12.6% and 24.2%. In addition, there was a significant correlation between GABA+ obtained with the two LCModel basis sets. Overall, our results demonstrated the feasibility and reproducibility of cerebellar GABA-edited MRS at 3.0 T in an elderly population. This information might be helpful for studies using this technique to study GABA changes in normal or diseased aging brain, e.g. for power calculations and the interpretation of longitudinal observations.