Simultaneous detection of valine and lactate using MEGA-PRESS editing in pyogenic brain abscess

Atlas-based GABA mapping with 3D MEGA-MRSI: Cross-correlation to single-voxel MRS

The purpose of this work is to develop and validate a new atlas-based metabolite quantification pipeline for edited magnetic resonance spectroscopic imaging (MEGA-MRSI) that enables group comparisons of brain structure-specific GABA levels. By using brain structure masks segmented from high-resolution MPRAGE images and coregistering these to MEGA-LASER 3D MRSI data, an automated regional quantification of neurochemical levels is demonstrated for the example of the thalamus. Thalamic gamma-aminobutyric acid + coedited macromolecules (GABA+) levels from 21 healthy subjects scanned at 3 T were cross-validated both against a single-voxel MEGA-PRESS acquisition in the same subjects and same scan sessions, as well as alternative MRSI processing techniques (ROI approach, four-voxel approach) using Pearson correlation analysis. In addition, reproducibility was compared across the MRSI processing techniques in test-retest data from 14 subjects. The atlas-based approach showed a significant correlation with SV MEGA-PRESS (correlation coefficient r [GABA+] = 0.63, P < 0.0001). However, the actual values for GABA+, NAA, tCr, GABA+/tCr and tNAA/tCr obtained from the atlas-based approach showed an offset to SV MEGA-PRESS levels, likely due to the fact that on average the thalamus mask used for the atlas-based approach only occupied 30% of the SVS volume, ie, somewhat different anatomies were sampled. Furthermore, the new atlas-based approach showed highly reproducible GABA+/tCr values with a low median coefficient of variance of 6.3%. In conclusion, the atlas-based metabolite quantification approach enables a more brain structure-specific comparison of GABA+ and other neurochemical levels across populations, even when using an MRSI technique with only cm-level resolution. This approach was successfully cross-validated against the typically used SVS technique as well as other different MRSI analysis methods, indicating the robustness of this quantification approach.

Big GABA: Edited MR spectroscopy at 24 research sites

Magnetic resonance spectroscopy (MRS) is the only biomedical imaging method that can noninvasively detect endogenous signals from the neurotransmitter γ-aminobutyric acid (GABA) in the human brain. Its increasing popularity has been aided by improvements in scanner hardware and acquisition methodology, as well as by broader access to pulse sequences that can selectively detect GABA, in particular J-difference spectral editing sequences. Nevertheless, implementations of GABA-edited MRS remain diverse across research sites, making comparisons between studies challenging. This large-scale multi-vendor, multi-site study seeks to better understand the factors that impact measurement outcomes of GABA-edited MRS. An international consortium of 24 research sites was formed. Data from 272 healthy adults were acquired on scanners from the three major MRI vendors and analyzed using the Gannet processing pipeline. MRS data were acquired in the medial parietal lobe with standard GABA+ and macromolecule- (MM-) suppressed GABA editing. The coefficient of variation across the entire cohort was 12% for GABA+ measurements and 28% for MM-suppressed GABA measurements. A multilevel analysis revealed that most of the variance (72%) in the GABA+ data was accounted for by differences between participants within-site, while site-level differences accounted for comparatively more variance (20%) than vendor-level differences (8%). For MM-suppressed GABA data, the variance was distributed equally between site- (50%) and participant-level (50%) differences. The findings show that GABA+ measurements exhibit strong agreement when implemented with a standard protocol. There is, however, increased variability for MM-suppressed GABA measurements that is attributed in part to differences in site-to-site data acquisition. This study's protocol establishes a framework for future methodological standardization of GABA-edited MRS, while the results provide valuable benchmarks for the MRS community.

Inhibitory motor dysfunction in parkinson's disease subtypes

BACKGROUND

Parkinson's disease (PD) is divided into postural instability gait difficulty (PIGD) and tremor-dominant (TD) subtypes. Increasing evidence has suggested that the GABAergic neurotransmitter system is involved in the pathogenesis of PD.

PURPOSE

To evaluate the differences of GABA levels between PD motor subtypes using MEscher-GArwood Point Resolved Spectroscopy (MEGA-PRESS).

STUDY TYPE

COHORT.: SUBJECTS: PD patients were classified into PIGD (n = 13) and TD groups (n = 9); 16 age- and sex-matched healthy controls were also recruited. All subjects were right-handed.

SEQUENCE

All subjects underwent an magnetic resonance spectroscopy scan including MEGA-PRESS at 3.0T.

ASSESSMENT

The detected GABA signal also contains signal from macromolecules (MM) and homocarnosine, so it is referred to as GABA+. GABA + levels and Creatine (Cr) levels were quantified in the left basal ganglia (BG) using Gannet 2.0 by Tao Gong.

STATISTICAL TESTS

Differences in GABA + levels between the three groups were analyzed using analysis of covariance. The relationship between GABA levels and a unified PD rating scale (UPDRS) was also analyzed.

RESULTS

GABA + levels were significantly lower in left BG regions of PD patients compared with healthy controls (P < 0.001). In PD patients, the GABA concentration was lower in the TD group than the PIGD group (P = 0.019). Cr levels in PIGD and TD were lower than controls (P = 0.020; P = 0.002). A significant negative correlation was found in PIGD between GABA levels and UPDRS (r = -0.572, P = 0.041), while no correlation was found in TD (r = -0.339, P = 0.372).

DATA CONCLUSION

Low BG GABA levels in PD patients, and differences between PIGD/TD patients, suggest that GABAergic dysfunction may play an important role in the pathogenesis of Parkinson's disease.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1610-1615.