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Functional Magnetic Resonance Spectroscopy of the Sensory and Attentional Auditory Processing at 7T
Eduardo Coello1, Nicolas R. Bolo2, George Chiou1, Huijun Liao1, Molly F. Charney1, Tyler C. Starr1, Elisabetta C. Del Re3, Margaret A. Niznikiewicz3, and Alexander P. Lin1

1Radiology, Brigham and Women's Hospital, Boston, MA, United States, 2Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States, 3Psychiatry, Veterans Affairs Boston Healthcare System, Brockton, MA, United States

Synopsis

This work describes a methodology to perform functional MR spectroscopy (fMRS) experiments to study auditory processing at 7T which can be valuable for gaining insight into psychiatric diseases such as schizophrenia. A reconstruction pipeline is proposed to remove distortions in the signal originated from potential temporal variations in the dynamic experiment. The designed experiment was successfully tested in healthy volunteers and metabolite variations were detected.

Introduction

Functional MR Spectroscopy (fMRS) at 7T provides an increased sensitivity and spectral dispersion that enables the detection of dynamic changes in metabolite concentrations in the brain under specific functional tasks. The study of auditory processes in the brain is of great interest for applications in psychiatry, such as schizophrenia, where abnormal auditory sensory and attentional processes have been shown to be prominent1. Specifically, auditory steady-state response has localized these abnormalities to the superior temporal gyrus2. Furthermore, MRS studies have shown metabolic abnormalities in this brain region such as decreased glutamate (Glu) and N-acetyl-aspartate (NAA). This suggests a correlation with neuro-metabolic processes in the brain that can be studied using fMRS. Recently, fMRS experiments performed at 7T have successfully detected changes in metabolite concentrations3. To maximize the sensitivity of these experiments, a high B0-homogeneity, negligible B0-drifts, effective water suppression, reduced eddy currents, and negligible patient motion is required. Special processing is necessary to account for these different external instabilities of the experiment. This work presents an fMRS methodology to investigate metabolic changes in an auditory paradigm with improved sensitivity at 7T. An acquisition protocol for the evaluation of both sensory and attentional tasks was designed. Furthermore, a processing pipeline that corrects for measurement instabilities is presented.

Methods

Data acquisition: The fMRS auditory experiment (Fig-1) was performed in five healthy volunteers at MR 7T scanner (Terra; Siemens, Erlangen, Germany). A 20x40x20mm3 volume located on the left superior temporal gyrus (LSTG) was acquired using STEAM localization and the following parameters: TE/TR=20/3000ms, TM=10ms, 768 signal averages during the full experiment, and a total acquisition time of 38min. Likewise, a visual fMRS experiment was also performed on a healthy volunteer for validation of the methodology using the setup described in Fig-4 and reported in literature3.

Auditory stimuli and fMRS paradigm: The fMRS auditory paradigm (Fig-1) consisted in 8 blocks of STIM frequent (STIM freq), eight blocks of STIM count and 8 blocks with no stimulus (REST), each of 48 MRS averages, total acquisition duration was 38 min. In the STIM freq blocks, 1 kHz pure tones were presented to the subject, in STIM count blocks, 2 kHz pure tones added (30%) among the 1kHz frequent tones (70%). Subjects were asked to keep eyes open during the entire experiment and to silently count the number of 2 kHz tones per STIM count block.

Data Processing and Quantification: The pipeline used for reconstruction of the spectra (Fig-2) was implemented in python using OpenMRSLab4 and included the following steps: (1) coil combination, (2) frequency alignment to water, (3) zero-order phase removal, (4) combination of 4 signal averages (sub-blocks) to increase SNR for processing, (5) water removal at each sub-block using HSVD, (6) frequency alignment to NAA, (7) zero-order phase removal, (8) filtering of the dynamic temporal signal (e.g. sliding window average, Fourier thresholding), and (9) combination of sub-blocks to obtain the desired temporal resolution to match the paradigm. Frequency/phase corrections eliminated distortions caused by external effects that affect the measurement, such as B0-drifts, eddy currents, temperature, or the BOLD effect (Fig-2a and Fig-5a). The reconstructed spectra, corresponding to consecutive time points, were fitted using LCModel with a simulated basis set.

Results and Discussion

The analysis of the auditory fMRS data showed the presence of BOLD signal when subtracting each STIM block with its nearest REST block (Fig-3a). Variations in metabolite concentrations were observed and enhanced using dynamic filtering. The quantified metabolite concentrations processed with the different methods superimposed with the auditory paradigm are shown (Fig-3b). Similarly, improvements in the signal obtained for the fMRS experiment in the visual cortex were obtained (Fig‑5b). The visual experiment served as a validation for the methodology as it was able to reproduce previously published experiments3.

Conclusion

This work presented a robust fMRS methodology to achieve high sensitivity at 7T. Improved detection of changes in metabolic concentrations was achieved using dynamic filtering compared to standard block averaging. Moreover, fMRS measurements of the auditory cortex were successfully performed, showing differences between activation and rest intervals. Potential applications of this technique include the study of metabolic profiles of the auditory process under normal and psychiatric conditions such as schizophrenia.

Acknowledgements

No acknowledgement found.

References

[1] Taylor S F, et al. GABA abnormalities in schizophrenia: A methodological review of in vivo studies. Schizophr Res. (2015).

[2] Javitt D C, et al. Auditory dysfunction in schizophrenia: integrating clinical and basic features. Nat Rev Neurosci. (2015).

[3] Bednařík P, et al. Neurochemical and BOLD responses during neuronal activation measured in the human visual cortex at 7 Tesla. Journal of Cerebral Blood Flow & Metabolism (2015)

[4] Rowland B, et al. An open-source software repository for magnetic resonance spectroscopy data analysis tools. ISMRM MR Spectroscopy Workshop (2016).

[5] Provencher S. W. Automatic quantitation of localized in vivo 1H spectra with LCModel. NMR in Biomedicine 14, 260–264 (2001).

Figures

Fig. 1. Setup for the auditory fMRS experiments. (a) Location of the measured volume (20x40x20mm3) placed on the left superior temporal gyrus (LSTG). (b) The fMRS paradigm consisted of 8 rest blocks with no stimulus (REST), and 16 blocks with stimulus (STIM). Two different stimuli were used: (1) STIM frequent (freq), where 1kHz pure tones were presented to the subject, and (2) STIM count, where 2kHz pure tones (30%) were added to the frequent tones (70%). Subjects were asked to keep eyes open during the entire experiment and to silently count the number of 2kHz tones per STIM count block.

Fig. 2. Reconstruction pipeline used to process the fMRS raw data. The pipeline started from spectral coil‑combined signals and follow the following steps: (1) frequency alignment to water, (2) zero-order phase removal, (3) combination of 4 signal averages (sub-blocks) to increase SNR, (4) water removal at each sub-block using HSVD, (5) frequency alignment to NAA, (6) zero-order phase removal, (7) filtering of the dynamic temporal signal (*e.g. sliding window averaging, Fourier thresholding), and (9) combination of sub-blocks to obtain the desired temporal resolution to match the paradigm. Subsequently, LCModel quantification is performed to retrieve the dynamic metabolite concentrations.

Fig. 3. fMRS results of the auditory task. (a) Bold effect detected in the measured area during activation, which modulates the linewidth of NAA and Cr. (b) Changes in metabolite concentration followed throughout the auditory paradigm (blue). The light shaded lines correspond to STIM Freq blocks, dark shaded areas correspond to STIM Count blocks, which involve active listening and white areas correspond to REST intervals. Normalized absolute concentration were used to avoid artifacts caused by instabilities of the Cr peak.

Fig. 4. Setup for the visual fMRS experiments. (a) Location of the measured volume (20x20x20mm3) placed on the left superior temporal gyrus (LSTG). (b) The fMRS paradigm used for the experiment. The visual stimulus (STIM) consisted of a flickering checkerboard at 7.5 Hz.

Fig. 5. fMRS results of the visual experiment. (a) Evidence of the BOLD effect in the activated area, which modulates the linewidth of NAA and Cr. (b) Changes in metabolite concentration followed throughout the visual paradigm (blue). The shaded lines correspond to STIM blocks and white areas correspond to REST intervals. Noticeable fluctuations that match the paradigm pattern are observed. During the visual stimulus, NAA, lactate and Glx concentrations increased.

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)
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