Comparison of GABA and Glx Quantification from Edited and Unedited MR Spectra – assessment of age effects
Akila Weerasekera1, Diana Sima2, Ronald Peeters3, Tom Dresslaers3, Oron Levin4, Stephan Swinnen4, Sabine Van Huffel2, and Uwe Himmelreich1

1Department of Imaging and Pathology, KU Leuven, leuven, Belgium, 2Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics and Imec, KU Leuven, leuven, Belgium, 3Radiology, Department of Imaging and Pathology, UZ Leuven, leuven, Belgium, 4Movement Control & Neuroplasticity Research Group, KU Leuven, leuven, Belgium


1H-MR spectroscopy (MRS) is a well-established tool to provide in vivo measurement of gamma-aminobutyric acid (GABA), glutamine and glutamine (Glx) concentrations for a variety of conditions1. There is an increasing interest in using spectral editing methods to measure GABA and Glx in the human brain. The commonly used GABA-editing sequence MEGA-PRESS provides filtered GABA signals based on the molecule’s J-coupling2, 3. Nonetheless, quantitative comparison among presently used acquisition and analysis methods is lacking. Here we compare currently available spectral fitting methods to assess the in vivo concentration values for GABA and Glx derived from edited (MEGA-PRESS) and unedited (MEGA-PRESS-OFF) spectra. We have tested our approach to assess the inter-subject variability in neurotransmitter levels arising from age effects.


Spectral editing methods like the MEGA-PRESS technique provide a promising approach for the discrimination of GABA from glutamate and glutamine, but to date no comparison was made of GABA concentrations derived from edited (MEGA-PRESS) and unedited (MEGA-OFF) spectra. Only very few studies have investigated the possible changes of GABA levels with advancing age4, 5 and relatively little is known about the inter-subject variability in neurotransmitter levels arising from age effects. In the present study, we quantify the GABA and Glx concentrations derived with edited/unedited MEGA-PRESS using three different spectral fitting methods (Gannet, jMRUI-AMARES, jMRUI-QUEST) and investigate age related differences in neurotransmitter levels in a group of healthy young and old adults.


Single voxel spectroscopy was performed in the left sensorimotor cortex (SM1) (Figure 1) of 10 young adults (YA) (18 – 45 years, 38.2 ± 8.43) and 10 older adults (OA) (60 – 70 years, 62.8 ± 6.26) using 3T Philips Achieva scanner. Data were acquired using MEGA-PRESS sequence (TE/TR, 68ms/2s, NA=160, 2 kHz spectral width) with a voxel size of 3x3x3 cm3. ON and OFF spectra were acquired in an interleaved order by placing the 14ms editing pulse at 1.9 ppm and 7.46 ppm respectively. Edited spectra were quantified using Gannet 3.0 toolbox6 and jMRUI v6.0-AMARES7 algorithm. MEGA-PRESS-OFF spectra were quantified with jMRUI v6.0-QUEST8 algorithm. Basis sets for QUEST were simulated using NMRScopeB9. No tissue corrections were applied. A water-unsuppressed signal was acquired from the same voxels, such that data is reported as the water-normalized ratios: GABA/H2O and Glx/H2O.


Figures 1, 2 show GABA and Glx concentrations estimated with Gannet, AMARES, and QUEST for the 20 subjects. The differences between values estimated using Gannet, AMARES and QUEST are presented in Table 1 for metabolite concentrations. Positive correlations were found for GABA values estimated with Gannet and QUEST (R2 = 0.95) (Figure 3) and Gannet and AMARES (R2 = 0.69). Edited GABA estimated with AMARES showed significantly lower levels for the older adults. Likewise GABA estimated with Gannet and QUEST (MEGA-OFF) had a trend towards decreasing GABA levels in older adults (P = 0.028, P = 0.067 and P = 0.057 respectively).


The inter-subject variability for GABA levels was lower than that of Glx for all three fitting methods. Almost no difference in values was found for GABA estimated with Gannet (edited) and QUEST (MEGA-OFF). Maximum difference (30%) for GABA was found between Gannet and AMARES. For Glx a 20% difference in values was found between Gannet and QUEST and 47% difference between Gannet and AMARES. The variability in concentration values may be due to differences in T1, T2 relaxation times10, 11, water visibility values (% of water in brain tissue), apodization and editing efficiency values used in each processing tool in estimating the absolute concentration. Even though not many studies reported GABA changes with advancing age, a recent study from Porges et al (2017)12 observed a decrease in GABA levels with advancing age within frontal and parietal locations. Our observation of lower GABA in older as compared to young adults needs further analysis with tissue corrections since the distribution of GABA varies across neural tissue fractions13. The age-related differences in GABA levels we observed may be driven by the gray matter loss rather than altered GABA levels within the gray and white matter tissues.


In conclusion, there is a good agreement between GABA values estimated with Gannet (edited) and QUEST (MEGA-OFF) spectral fitting methods. The strong correlation between the Gannet (edited) and QUEST (MEGA-OFF) may suggest that conventional MRS (PRESS or STEAM) with a TE=68ms may be used to measure GABA levels accurately in the absence of advanced MRS sequences. Furthermore, our results indicate that within the SM1 voxel GABA levels were lower in older as compared to young adults.


No acknowledgement found.


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Figure 2. Glx concentrations of 20 subjects estimated with three spectral fitting methods

Figure 2. Glx concentrations of 20 subjects estimated with three spectral fitting methods

Figure 3. Correlation of Gannet and QUEST for GABA concentrations on edited and edit-OFF spectra from 20 subjects

Table 1. Metabolite concentrations determined by Gannet, AMARES and QUEST (mean ±standard deviation), difference in percentage and p-values.

Figure 4. GABA concentrations for young (n = 10) and old (n = 10) adults estimated with Gannet, QUEST and AMARES.

Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)