Anouk Schrantee1, Chloe Najac2, Chris Jungerius2, Aart J Nederveen1, Vincent O Boer3, Wietske van der Zwaag4, Silvia Mangia5, and Itamar Ronen2
1Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands, 2C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands, 3Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 4Spinoza Centre for Neuroimaging, Royal Netherlands Academy of Arts and Sciences, Amsterdam, Netherlands, 5Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States
Synopsis
Functional magnetic resonance spectroscopy can
non-invasively measure changes in local concentrations of neurometabolites
and has been used to demonstrate changes in lactate and glutamate levels in
response to visual stimulation. However, whether the neurometabolite response
scales with the level of neuronal stimulation like the BOLD response, has not
been extensively investigated. We here show that lactate, but not glutamate levels,
change dependent on visual contrast levels (baseline, 10%, 100% contrast). Although we also demonstrate a significant contrast dependence
in the BOLD response, we do not find a significant association between the
lactate response and the BOLD response.
Introduction
Functional magnetic resonance
spectroscopy (fMRS) is a method for non-invasively measuring the local
concentration of metabolites in the human brain during functional paradigms.
For example, neuronal lactate and glutamate levels in human cortex have been shown
to increase in response to visual stimulation1,2,3.
However, whether the neurometabolite response scales with the intensity of
visual stimulation and how this relates to the hemodynamic response has not
been extensively investigated4.
To better understand this relationship, we measured the metabolite response to
different contrast levels of a visual checkerboard stimulus during an
interleaved fMRS and fMRI acquisition. We hypothesized a dependence of lactate
and glutamate levels on the visual contrast for both the fMRS and functional
magnetic resonance imaging (fMRI) data.Methods
Eight healthy subjects were scanned on
a 7T MR system (Achieva, Philips, Best, the Netherlands) with a dual-channel
transmit coil and a 32-channel receive coil (Nova Medical, Wilmington, USA). Data
were collected in accordance with the guidelines of the local ethics review
board. Figure 1 shows the stimulation paradigm. The stimulus consisted of a
full-field radial checkerboard flickering at 8Hz. The task consisted of two
4-minute stimulation blocks (STIM) at two different black/white contrasts: 10%
and 100%. To prevent neural habituation in V1 to the prolonged stimulus,
each STIM block was subdivided into five sub-blocks of 30s ON and a 20s OFF. During
the REST and OFF period a grey screen was presented (with a central white fixation
point). fMRS data were acquired using a semiLASER sequence with FOCI refocusing
pulses5 and VAPOR water suppression (TR/TE=3600/36ms; bandwidth=3kHz; 1024
data points; voxel size=14x31x14mm). fMRI data were acquired using a 3D-EPI
sequence (TR/TE/FA=1400/30ms/10˚; voxel size=1.875x1.875x1.875mm, matrix
size=128x128x68). fMRS and fMRI were interleaved6 with a combined dynamic scan time of 5s with a total of 226 dynamics (for
spectroscopy, 2 unsuppressed water spectra and 224 water-suppressed metabolite
spectra). We used dynamically alternating linear shims and a shared set of
static second order terms7.
The voxel was placed in the primary visual cortex (V1),
based on a short checkerboard localizer and identification of the calcarine
sulcus on the T1-weighted image. The spectra were corrected
for eddy currents as well as frequency and phase drifts. Subsequently, the second
half of the STIM periods were summed and compared to second half of each REST
period2. The summed spectra per condition were quantified with
LCmodel8 utilizing a basis set of 19 simulated metabolites and a measured macromolecular
baseline. The fMRI data were motion corrected, spatially
smoothed (5mm kernel), high pass filtered (0.002Hz), registered to the
anatomical MRI and fed into a first-level analysis using FSL Feat9. Time courses
and %BOLD signal change were extracted from the MRS voxel location (transformed
into MNI space) and a z-map of the 100%>10% contrast was calculated in a
second-level analysis. One-way analysis of variance (ANOVA) was used to compare
differences between REST, 10% and 100% stimulation, and Pearson’s correlations
were used to compare the fMRS and fMRI responses.Results
The 100% contrast checkerboard induced
a significantly larger hemodynamic response than the 10% contrast (Figure A-C,
p<0.001), with both contrast levels showing significant widespread
activation in visual cortex compared to baseline. For the fMRS, one subject was
removed from the analyses due to poor quality spectra. Lactate levels significantly
differed between the REST, 10% and 100% contrast (F(2,6)=6.2, p=0.01; post-hoc
tests: 100%-vs-REST p=0.01, 10%-vs-REST p=0.18, 100%-vs-10% p=0.08) and followed
a linear trend (p=0.004). Glutamate levels did not significantly differ between
the three conditions (F(2,6)=3.5, p=0.09). SNR was significantly different
between the REST (NSA=64) and the STIM (NSA=24) blocks (p<0.01), but SNR was
not associated with lactate or glutamate levels. Linewidth obtained for all
conditions with linear predictive singular value decomposition (LPSVD) did not differ
between the three conditions (p>0.05), therefore no line broadening was
applied. No correlation between the change in BOLD and the change in lactate (r=0.17; p=0.56) or glutamate (r=0.06; p=0.82) were found. Discussion and Conclusion
We here demonstrate that, similarly to
the BOLD response, changes in lactate are dependent on visual contrast level. Although
one of the strengths of this study is the interleaved measurement of fMRS and
fMRI, we did not find a significant correlation between them. This might be a
consequence of the small sample size. Surprisingly, and opposed to a recent
study investigating the effects of visual contrast on glutamate levels using
MRS, we did not find evidence for a strong dependence of glutamate on contrast
level4.
We averaged our MRS data over longer acquisition blocks (4 min) compared to the
stimulus blocks in the previous study (1 min). Therefore, our future analyses
will examine at what timescale these neurometabolite changes take place and
whether we find evidence for fluctuations in our sub-minute alternations in ON
and OFF during the STIM blocks. This might also shed more light on the origin
of lactate and glutamate fluctuations. Acknowledgements
No acknowledgement found.References
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