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

Gray matter gamma-hydroxy-butyric acid and glutamate reflect beta-amyloid burden at old age

Gamma-hydroxy-butyric acid (GABA) and glutamate are neurotransmitters with essential importance for cognitive processing. Here, we investigate relationships between GABA, glutamate, and brain ß-amyloid (Aß) burden before clinical manifestation of Alzheimer's disease (AD). Thirty cognitively healthy adults (age 69.9 ± 6 years) received high-resolution atlas-based 1H-magnetic resonance spectroscopic imaging (MRSI) at ultra-high magnetic field strength of 7 Tesla for gray matter-specific assessment of GABA and glutamate. We assessed Aß burden with positron emission tomography and risk factors for AD. Higher gray matter GABA and glutamate related to higher Aß-burden (ß = 0.60, p < 0.05; ß = 0.64, p < 0.02), with positive effect modification by apolipoprotein-E-epsilon-4-allele (APOE4) (p = 0.01-0.03). GABA and glutamate negatively related to longitudinal change in verbal episodic memory performance (ß = -0.48; p = 0.02; ß = -0.50; p = 0.01). In vivo measures of GABA and glutamate reflect early AD pathology at old age, in an APOE4-dependent manner. GABA and glutamate may represent promising biomarkers and potential targets for early therapeutic intervention and prevention.

Highlights

Gray matter-specific metabolic imaging with high-resolution atlas-based MRSI at 7 Tesla.Higher GABA and glutamate relate to ß-amyloid burden, in an APOE4-dependent manner.Gray matter GABA and glutamate identify older adults with high risk of future AD.GABA and glutamate might reflect altered synaptic and neuronal activity at early AD.

Simultaneous multi-region detection of GABA+ and Glx using 3D spatially resolved SLOW-editing and EPSI-readout at 7T

GABA+ and Glx (glutamate and glutamine) are widely studied metabolites, yet the commonly used magnetic resonance spectroscopy (MRS) techniques have significant limitations, including sensitivity to B0 and B1+-inhomogeneities, limited bandwidth of MEGA-pulses, high SAR which is accentuated at 7T. To address these limitations, we propose SLOW-EPSI method, employing a large 3D MRSI coverage and achieving a high resolution down to 0.26 ml. Simulation results demonstrate the robustness of SLOW-editing for both GABA+ and Glx against B0 and B1+-inhomogeneities within the range of [-0.3, +0.3] ppm and [40 %, 250 %], respectively. Two protocols, both utilizing a 70 mm thick FOV slab, were employed to target distinct brain regions in vivo, differentiated by their orientation: transverse and tilted. Protocol 1 (n = 11) encompassed 5 locations (cortical gray matter, white matter, frontal lobe, parietal lobe, and cingulate gyrus). Protocol 2 (n = 5) involved 9 locations (cortical gray matter, white matter, frontal lobe, occipital lobe, cingulate gyrus, caudate nucleus, hippocampus, putamen, and inferior thalamus). Quantitative analysis of GABA+ and Glx was conducted in a stepwise manner. First, B1+/B1--inhomogeneities were corrected using water reference data. Next, GABA+ and Glx values were calculated employing spectral fitting. Finally, the GABA+ level for each selected region was compared to the global Glx within the same subject, generating the GABA+/Glx_global ratio. Our findings from two protocols indicate that the GABA+/Glx_global level in cortical gray matter was approximately 16 % higher than in white matter. Elevated GABA+/Glx_global levels acquired with protocol 2 were observed in specific regions such as the caudate nucleus (0.118±0.067), putamen (0.108±0.023), thalamus (0.092±0.036), and occipital cortex (0.091±0.010), when compared to the cortical gray matter (0.079±0.012). Overall, our results highlight the effectiveness of SLOW-EPSI as a robust and efficient technique for accurate measurements of GABA+ and Glx at 7T. In contrast to previous SVS and 2D-MRSI based editing sequences with which only one or a limited number of brain regions can be measured simultaneously, the method presented here measures GABA+ and Glx from any brain area and any arbitrarily shaped volume that can be flexibly selected after the examination. Quantification of GABA+ and Glx across multiple brain regions through spectral fitting is achievable with a 9-minute acquisition. Additionally, acquisition times of 18-27 min (GABA+) and 9-18 min (Glx) are required to generate 3D maps, which are constructed using Gaussian fitting and peak integration.

Ventromedial prefrontal cortex/anterior cingulate cortex Glx, glutamate, and GABA levels in medication-free major depressive disorder

Glutamate (Glu) and gamma-aminobutyric acid (GABA) are implicated in the pathophysiology of major depressive disorder (MDD). GABA levels or GABAergic interneuron numbers are generally low in MDD, potentially disinhibiting Glu release. It is unclear whether Glu release or turnover is increased in depression. Conversely, a meta-analysis of prefrontal proton magnetic resonance spectroscopy (¹H MRS) studies in MDD finds low Glx (combination of glutamate and glutamine) in medicated MDD. We hypothesize that elevated Glx or Glu may be a marker of more severe, untreated MDD. We examined ventromedial prefrontal cortex/anterior cingulate cortex (vmPFC/ACC) Glx and glutamate levels using ¹H MRS in 34 medication-free, symptomatic, chronically ill MDD patients and 32 healthy volunteers, and GABA levels in a subsample. Elevated Glx and Glu were observed in MDD compared with healthy volunteers, with the highest levels seen in males with MDD. vmPFC/ACC GABA was low in MDD. Higher Glx levels correlated with more severe depression and lower GABA. MDD severity and diagnosis were both linked to higher Glx in vmPFC/ACC. Low GABA in a subset of these patients is consistent with our hypothesized model of low GABA leading to glutamate disinhibition in MDD. This finding and model are consistent with our previously reported findings that the NMDAR-antagonist antidepressant effect is proportional to the reduction of vmPFC/ACC Glx or Glu levels.

ECLIPSE utilizing gradient-modulated offset-independent adiabaticity (GOIA) pulses for highly selective human brain proton MRSI

A multitude of extracranial lipid suppression methods exist for proton MRSI acquisitions. Popular and emerging lipid suppression methods each have their inherent set of advantages and disadvantages related to the achievable level of lipid suppression, RF power deposition, insensitivity to B₁⁺ field and lipid T₁ heterogeneity, brain coverage, spatial selectivity, chemical shift displacement (CSD) errors and the reliability of spectroscopic data spanning the observed 0.9-4.7 ppm band. The utility of elliptical localization with pulsed second order fields (ECLIPSE) was previously demonstrated with a greater than 100-fold in extracranial lipid suppression and low power requirements utilizing 3 kHz bandwidth AFP pulses. Like all gradient-based localization methods, ECLIPSE is sensitive to CSD errors, resulting in a modified metabolic profile in edge-of-ROI voxels. In this work, ECLIPSE is extended with 15 kHz bandwidth second order gradient-modulated RF pulses based on the gradient offset-independent adiabaticity (GOIA) algorithm to greatly reduce CSD and improve spatial selectivity. An adiabatic double spin-echo ECLIPSE inner volume selection (TE = 45 ms) MRSI method and an ECLIPSE outer volume suppression (TE = 3.2 ms) FID-MRSI method were implemented. Both GOIA-ECLIPSE MRSI sequences provided artifact-free metabolite spectra in vivo, with a greater than 100-fold in lipid suppression and less than 2.6 mm in-plane CSD and less than 3.3 mm transition width for edge-of-ROI voxels, representing an ~5-fold improvement compared with the parent, nongradient-modulated method. Despite the 5-fold larger bandwidth, GOIA-ECLIPSE only required a 1.9-fold increase in RF power. The highly robust lipid suppression combined with low CSD and sharp ROI edge transitions make GOIA-ECLIPSE an attractive alternative to commonly employed lipid suppression methods. Furthermore, the low RF power deposition demonstrates that GOIA-ECLIPSE is very well suited for high field (≥3 T) MRSI applications.