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Increase in Glutamate concentration during motor activation measured using functional Magnetic Resonance Spectroscopy (fMRS) at 3T.
Osnat Volovyk1 and Assaf Tal1

1Chemical Physics, Weizmann Institute of Science, Rehovot, Israel

Synopsis

In the presented study we've demonstrated that small changes in Glutamate concentration associated with performing simple motor task can be reliably detected with 3T system using functional 1H MR spectroscopy. Comparison between two differently timed paradigms for motor activation revealed a clear preference for longer-block designs. This suggests that motor activity-induced changes in Glutamate concentration are of minutes-long time-scale.

Purpose

Functional MR spectroscopy (fMRS) provides the means to investigate the metabolic response of the brain to stimulation, by acquiring continuously MR spectra during a functional task, and by that enhances our knowledge of brain metabolic circles. Recent studies at high field (7T) have reported small metabolites' concentrations changes, in particular increase of glutamate (Glu) concentration by 2-4% during visual1-4 and motor5 stimulation. Our goal was to investigate the metabolite changes during motor activation at 3T and to compare the effect of two functional activation paradigms.

Methods

Functional task: 40 healthy volunteers participated in this study (17 male /23 female, mean age 30). Volunteers were asked to execute a rubber air-filled balloon (BIOPAC Clench Force Bulb transducer, BIOPAC Systems, CA, USA) squeezing task with right hand according to the displayed instructions (press\rest). We've compared 2 block-designed interleaved schemes, comprised of rapidly squeezing/releasing the ball and rest: a short-cycled design (20 subjects, 10 blocks of 64 sec. activation/32 sec rest, following 4.3 min initial rest period, total scan time 20 min), and a long-cycled design (20 subjects, 2 blocks of 5.3 min activation/5.3 min rest, following 4.3 min initial rest, total scan time 25.6 min). During the rest period, the subject was asked to keep the hand static in the same position.

MR Spectroscopy: All experiments were performed at Siemens 3T Tim Trio (Erlangen, Germany) scanner, using vendor provided 32-channel phased array receive-only head matrix coil for signal detection, and embedded body coil capable of peak B1+ of ~20mT for signal transmission. 1H MR Spectra were continuously acquired using the PR-STRESS6 sequence (TR/TE=2000/15ms, Volume of Interest (VOI)=2x2x1.5 cm3, 608 excitations in Short-cycled task and 768 in Long-cycled task, 2 kHz bandwidth, 2048 complex points) from a voxel placed in the left sensorimotor cortex (Fig. 1). We've employed PR-STRESS sequence for this task as it showed certain benefits as compared to other methods, most importantly lower min TE, while maintaining sufficient SNR to ensure accurate quantification 6. Unsuppressed water spectra were acquired prior to the beginning of the task to be used for phasing, eddy current correction and as reference for metabolites quantification. One noise scan with all RF pulses turned off was acquired for coil sensitivity calculation. Voxel placement was confirmed by short BOLD-fMRI motor acquisition (Fig. 1): subject was asked to pump the balloon for 30 sec followed by 30 sec rest for 5 cycles (5 min); data was acquired using multi-slice EPI sequence. Data processing: Average spectra were created by summing up the data of all volunteers after phasing, frequency drift correction and normalization with a moving window of 16 excitations. Metabolites were quantified with LCModel (Version 6.3-1L, Copyright: S.W.Provencher7) in institutional units (I.U.) relative to the unsuppressed water collected from the same VOI. BOLD activation maps were calculated from EPI data using General Linear Model in Matlab (R2017a, Mathworks, MA, USA). The distributions of metabolites’ concentrations during task and rest periods were compared using a two-sample t-test.

Results

In case of the Short-cycled task, the changes in any of the quantified metabolites did not reach the level of significance. Fig. 2 shows the timecourses of Glx=Glutamate+Glutamine (Gln) and Glu during Short-cycled task, each data point in these plots was produced by fitting a spectrum averaged over 20 volunteers and 16 excitations. The fluctuations in the obtained concentrations do not correlate with the task/rest paradigm. Analysis of Long-cycled task revealed a statistically significant (p=0.006) increase in Glx and Glu concentrations of 1.9%±0.2% and 2.3%±0.2% respectively, during task periods as compared to rest. Average CRLB of Glx and Glu were 3% and 4% respectively. No changes in any of other metabolites’ concentrations were observed. Fig. 3 shows the timecourses of Glu, Glx, N-acetylaspartate (NAA) and Creatine (Cr) during Long-cycled task. Table 1 summarizes quantification results of major metabolites, percent of change in concentrations, p-values and average CRLB%.

Discussion

Our results are in good agreement with previous reports of Glu dynamics during motor activation, acquired at higher field systems1-5. Glu changes could be attributed to the higher energy demands of the brain region during task performance. The lack of statistically significant changes in the Short-cycled task indicates the timescales involved in the metabolic alterations are on the order of minutes, favouring longer block designs with fewer, prolonged elements.

Conclusion

Our study demonstrated the adequate sensitivity of 3T system and PR-STRESS MRS sequence to detect small changes in the Glx/Glu concentrations attributed to brain activation during motor task.

Acknowledgements

We are grateful to Dr. Edna Haran and the Weizmann MRI technician team, for assistance in the human scans, and to S.W. Provencher for supplying the fitting basis sets for STEAM and PRESS.We acknowledge the support of the Monroy-Marks Career Development Fund, the Carolito Stiftung Fund, the Leona M. and Harry B. Helmsley Charitable Trust, the Sylvia Schaefer Alzheimer’s Research Fund, National Institute of Neurological Disorders and Stroke and the historic generosity of the Harold Perlman Family.

References

[1] Mangia S, Tkáč I, Gruetter R, Van De Moortele PF, Giove F, Maraviglia B, Uğurbil K, Sensitivity of single-voxel 1H-MRS in investigating the metabolism of the activated human visual cortex at 7 T, Magnetic Resonance Imaging. 2006;24(4):343-348.

[2] Lin Y, Stephenson MC, Xin L, Napolitano A, Morris PG, Investigating the Metabolic Changes due to Visual Stimulation using Functional Proton Magnetic Resonance Spectroscopy at 7 T, Journal of Cerebral Blood Flow & Metabolism. 2012;32(8):1484-1495.

[3] Schaller B, Mekle R, Xin L, Kunz N, Gruetter R, Net increase of lactate and glutamate concentration in activated human visual cortex detected with magnetic resonance spectroscopy at 7 tesla, Journal of Neuroscience Research. 2013;91(8):1076-1083.

[4] Betina I, Berrington A, Hess AT, Parker AJ, Emir UE, Bridge H, Combined fMRI-MRS acquires simultaneous glutamate and BOLD-fMRI signals in the human brain, NeuroImage, 2017;155:113-119.

[5] Schaller B, Xin L, O'Brien K, Magill AW, Gruetter R, Are glutamate and lactate increases ubiquitous to physiological activation? A 1H functional MR spectroscopy study during motor activation in human brain at 7 tesla, NeuroImage, 2014;93(1):138-145.

[6] Volovyk O, Tal A, Application of phase rotation to STRESS localization scheme at 3T. Magn Res Med. 2017.

[7] Provencher SW, Automatic quantitation of localized in vivo 1H spectra with LCModel, NMR in Biomedicine, 2001;14(4):260-264.

Figures

fMRI motor localizer experiment: top: BOLD activation map overlay on EPI Ax images, bottom left: z-score plot of averaged timecourse of the activated pixels (blue line) and the block designed model: 30s ON/30s OFF, 5 cycles (red line); bottom right: T1w anatomical images showing the voxel placement (red box) for MRS scan.

The timecourses of concentrations of Glx (left) and Glu (right) in Short-cycled motor task. Each data point is produced by LCModel fit of averaged over 20 volunteers and 16 excitations spectrum. Error bars represent a moving standard deviation. Task ON periods are marked as light blue rectangles.

The timecourses of concentrations of Glx (A), Glu (B), total NAA (C) and Cr (D) in the Long-cycled motor task. Each data point was produced by averaging the spectra over 20 subjects and 16 consecutive excitations, and subsequently fitting using LCModel. Error bars represent a moving standard deviation. Task ON periods are marked as light blue rectangles.

Table 1. Results summary for Long-cycled task (left) and Short-cycled task (right): average concentrations of major metabolites during task/rest periods, percentage of change, p-values and average CRLBs are shown. * marked are metabolites with statistically significant difference in task/rest concentrations (p<0.05).

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