Impact of tissue correction strategy on GABA-edited MRS findings.

Tissue composition impacts the interpretation of magnetic resonance spectroscopy metabolite quantification. The goal of applying tissue correction is to decrease the dependency of metabolite concentrations on the underlying voxel tissue composition. Tissue correction strategies have different underlying assumptions to account for different aspects of the voxel tissue fraction. The most common tissue correction is the CSF-correction that aims to account for the cerebrospinal fluid (CSF) fraction in the voxel, in which it is assumed there are no metabolites. More recently, the α-correction was introduced to account for the different concentrations of GABA+in gray matter and white matter. In this paper, we show that the selected tissue correction strategy can alter the interpretation of results using data from a healthy aging cohort with GABA+ measurements in a frontal and posterior voxel. In a frontal voxel, we show an age-related decline in GABA+ when either no tissue correction (R2 = 0.25, p < 0.001) or the CSF-correction is applied (R2 = 0.08, p < 0.01). When applying the α-correction to the frontal voxel data, we find no relationship between age and GABA+ (R2 = 0.02, p = 0.15). However, with the α-correction we still find that cognitive performance is correlated with GABA+ (R2 = 0.11, p < 0.01). These data suggest that in healthy aging, while there is normal atrophy in the frontal voxel, GABA+ in the remaining tissue is not decreasing on average. This indicates that the selection of tissue correction can significantly impact the interpretation of MRS results.

Tissue correction for GABA-edited MRS: Considerations of voxel composition, tissue segmentation, and tissue relaxations.

PURPOSE: To develop a tissue correction for GABA-edited magnetic resonance spectroscopy (MRS) that appropriately addresses differences in voxel gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) fractions. MATERIALS AND METHODS: Simulations compared the performance of tissue correction approaches. Corrections were then applied to in vivo data from 16 healthy volunteers, acquired at 3T. GM, WM, and CSF fractions were determined from T1 -weighted images. Corrections for CSF content, GM/WM GABA content, and water relaxation of the three compartments are combined into a single, fully corrected measurement. RESULTS: Simulations show that CSF correction increases the dependence of GABA measurements on GM/WM fraction, by an amount equal to the fraction of CSF. Furthermore, GM correction substantially (and nonlinearly) increases the dependence of GABA measurements on GM/WM fraction, for example, by a factor of over four when the voxel GM tissue fraction is 50%. At this tissue fraction, GABA is overestimated by a factor of 1.5. For the in vivo data, correcting for voxel composition increased measured GABA values (P < 0.001 for all regions), but did not reduce intersubject variance (P > 0.5 for all regions). Corrected GABA values differ significantly based on the segmentation procedure used (P < 0.0001) and tissue parameter assumptions made (P < 0.0001). CONCLUSION: We introduce a comprehensive tissue correction factor that adjusts GABA measurements to correct for different voxel compositions of GM, WM, and CSF.

Frequency and phase correction of GABA-edited magnetic resonance spectroscopy using complex-valued convolutional neural networks.

PURPOSE: To determine the significance of complex-valued inputs and complex-valued convolutions compared to real-valued inputs and real-valued convolutions in convolutional neural networks (CNNs) for frequency and phase correction (FPC) of GABA-edited magnetic resonance spectroscopy (MRS) data. METHODS: An ablation study using simulated data was performed to determine the most effective input (real or complex) and convolution type (real or complex) to predict frequency and phase shifts in GABA-edited MEGA-PRESS data using CNNs. The best CNN model was subsequently compared using both simulated and in vivo data to two recently proposed deep learning (DL) methods for FPC of GABA-edited MRS. All methods were trained using the same experimental setup and evaluated using the signal-to-noise ratio (SNR) and linewidth of the GABA peak, choline artifact, and by visually assessing the reconstructed final difference spectrum. Statistical significance was assessed using the Wilcoxon signed rank test. RESULTS: The ablation study showed that using complex values for the input represented by real and imaginary channels in our model input tensor, with complex convolutions was most effective for FPC. Overall, in the comparative study using simulated data, our CC-CNN model (that received complex-valued inputs with complex convolutions) outperformed the other models as evaluated by the mean absolute error. CONCLUSION: Our results indicate that the optimal CNN configuration for GABA-edited MRS FPC uses a complex-valued input and complex convolutions. Overall, this model outperformed existing DL models.

Relationship between GABA levels and task-dependent cortical excitability in children with attention-deficit/hyperactivity disorder.

OBJECTIVE: Compared to typically developing (TD) peers, children with attention deficit hyperactivity disorder (ADHD) manifest reduced short interval cortical inhibition (SICI) in the dominant motor cortex measured with transcranial magnetic stimulation (TMS). This multimodal study investigates the inhibitory neurophysiology and neurochemistry by evaluating the relationship between SICI and γ-amino butyric acid (GABA+) levels, measured with magnetic resonance spectroscopy (MRS). METHODS: Across two sites, 37 children with ADHD and 45 TD children, ages 8-12 years, participated. Single and paired pulse TMS to left motor cortex quantified SICI during REST and at times of action selection (GO) and inhibition (STOP) during a modified Slater-Hammel stop signal reaction task. MRS quantified GABA+ levels in the left sensorimotor cortex. Relationships between SICI and GABA+, as well as stopping efficiency and clinical symptoms, were analyzed with correlations and repeated-measure, mixed-models. RESULTS: In both groups, higher GABA+ levels correlated with less SICI. In TD children only, higher GABA+ levels correlated with larger TMS motor evoked potentials (MEPs) at REST. In GO and STOP trials, higher GABA+ was associated with smaller MEP amplitudes, for both groups. Overall, GABA+ levels did not differ between groups or correlate with ADHD clinical symptoms. CONCLUSIONS: In children with higher motor cortex GABA+, motor cortex is less responsive to inhibitory TMS (SICI). Comparing the relationships between MRS-GABA+ levels and responses to TMS at REST vs. GO/STOP trials suggests differences in inhibitory neurophysiology and neurotransmitters in children with ADHD. These differences are more prominent at rest than during response inhibition task engagement. SIGNIFICANCE: Evaluating relationships between GABA+ and SICI may provide a biomarker useful for understanding behavioral diagnoses.

Reductions in GABA following a tDCS-language intervention for primary progressive aphasia.

Transcranial direct current stimulation (tDCS) has shown efficacy in augmenting the effects of language therapy in primary progressive aphasia (PPA). The mechanism of action of tDCS is not understood, but preliminary work in healthy adults suggests it modulates γ-aminobutyric acid (GABA) levels to create an environment optimal for learning. It is unknown if this proposed mechanism translates to aging or neurodegenerative conditions. This study tested the hypothesis that tDCS reduces GABA at the stimulated tissue in PPA. We applied GABA-edited magnetic resonance spectroscopy to quantify GABA levels before and after a sham-controlled tDCS intervention with language therapy in PPA. All participants showed improvements but those receiving active tDCS showed significantly greater language improvements compared to sham both immediately after the intervention and at 2-month follow-up. GABA levels in the targeted tissue decreased from baseline after the intervention and remained decreased 2 months after the intervention. This work supports the hypothesis that tDCS modulates GABAergic inhibition to augment learning and is clinically useful for PPA combined with language therapy.