Layla Tabea Riemann1, Christoph Stefan Aigner1, Ralf Mekle2, Sebastian Schmitter1,3,4, Bernd Ittermann1, and Ariane Fillmer1
1Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany, 2Center for Stroke Research Berlin, Charité Universitätsmedizin, Berlin, Germany, 3Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States, 4Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
Synopsis
For simultaneous
multi-voxel spectroscopy (sMVS), it is necessary to optimize the B0
shimming and the B1+ adjustment simultaneously for two
voxels. The impact of these adjustments on the smallest possible distance for
simultaneous two-voxel MRS acquisitions is determined by Bloch simulations, and
the influence on the spectral quality is assessed for three
different brain regions. To this
end, the previously introduced 2 spin-echo full-intensity acquired localization (2SPECIAL) sequence and the voxel-GeneRalized Autocalibrating Partial Parallel Acquisition (vGRAPPA)
decomposition algorithm are utilized to simultaneously acquire and retrospectively decompose in vivo brain 1H-MRS
data from two voxels at short echo times at 7T.
Introduction
In single-voxel MRS, the
advantage of a compact point spread function1 and an improved metabolite SNR at short
measurement times compared to MRSI is accompanied by the disadvantage of only measuring
the signal of a single region2. To address this issue, several methods for simultaneous multi-voxel spectroscopy (sMVS) measurement and retrospective decomposition have
been proposed3–5.
In this work, we assess the impact of the B0 and
B1+-adjustments on both the smallest feasible distance between voxels for a particular sMVS technique, as well as on the simultaneous B0-shim and B1+-optimization of two
voxels for three different human brain regions, measured in vivo at 7T. Therefore, data was acquired utilizing the 2 spin-echo full-intensity acquired localization
(2SPECIAL) sequence6–8, employing a multi-banded (MB) wideband, uniform
rate, smooth truncation (WURST) pulse9, and it was decomposed using the voxel-GeneRalized
Autocalibrating Partial Parallel Acquisition (vGRAPPA)10–13 algorithm.Methods
Sequence and Bloch
Simulations
The MB hyperbolic secant adiabatic
inversion pulse, previously introduced into the 2SPECIAL sequence, was now replaced by an
MB WURST pulse14. The smallest feasible edge-to-edge distance between two voxels, i.e., the distance between the FWHMs of both inversion profiles, was
evaluated by Bloch simulations of B1+ and the
off-resonance ΔB0 (Fig.1).
Data Acquisition
All
measurements were performed on a 7T scanner (Magnetom, Siemens Healthineers,
Erlangen, Germany) using a 1Tx/32Rx head coil (NOVA Medical, Wilmington, USA).
In vivo measurements were performed on twelve healthy volunteers
(aged 32±12 y, 4:7:1 male:female:nonbinary). Spectra of ten
volunteers were obtained from the left and right motor cortex (Fig.2a). Additional
spectra were obtained in the anterior and posterior cingulate cortex of one
subject (ACC/PCC, Fig.3b), and in an anterior gray- and a posterior white
matter-rich region of another (GM/WM, Fig.3d). MP2RAGE15 images were acquired for voxel positioning.
Voxel-based 2nd-order B0-shimming was performed using an
in-house shimtool16,17 implemented in MATLAB, which was adapted to
allow optimizing shim adjustments for both voxels simultaneously. First, SVS
was performed for both voxels each using an SVS WURST-SPECIAL sequence and the individually
optimized B0-shim and reference voltage (SVSind).
Subsequently, the reference transmitter voltage for the sMVS acquisition was set to the mean of both single-voxel optimized reference voltages,
and a two-voxel optimized B0-shim was obtained. These adjustments
were then used to acquire SVS spectra (SVScomb) using SPECIAL and to
obtain sMVS spectra using 2SPECIAL8. An additional outer volume
saturation (OVS) band was added throughout the interleaved water suppression16 and OVS scheme for 2SPECIAL to also saturate the volume between the two
voxels. The protocol
and scan parameters are displayed in Tab.1.
vGRAPPA Decomposition
and Spectral Reconstruction
The previously introduced vGRAPPA
algorithm13 was applied to decompose the sMVS data to their respective regions. Both the
separated sMVS spectra and the SVS spectra, were post-processed by summation of
the even and odd averages for full localization, frequency correction, weighted
and phase-corrected coil combination, and averaging. Metabolite
quantification was performed with LCModel17.
Bland-Altman plots
Bland-Altman plots18 of the tissue- and relaxation-time-corrected
concentrations were obtained for both voxels in the motor cortices for the most prominent
metabolites (NAA, Glu, tCr, and tCho), comparing the vGRAPPA
decomposed sMVS spectra to 1) the SVSind and 2) the SVScomb data.Results and Discussion
The minimum
distance between two voxels was found to be 10mm, as an artificial partial
inversion outside the voxels appeared below that distance for B1+-intensities 1.5-2 times above the nominal one (Fig.1). Moreover, at distances below
10mm, the inversion profiles become increasingly susceptible to B0-inhomogeneities.
Hence, for voxel distances below 10mm, alternative approaches like exciting one large voxel covering the entire region should be considered.
The differences in
water linewidth and SNR between SVScomb and SVSind-adjustments depend on the brain region: For
the given data and voxel locations, the impact is smaller in the motor cortices than in dorsal/ventral
regions (Tab.2). Due to the absence of symmetry in the B0-distribution
of the frontal and posterior cortex, this result was expected, whereas the
symmetry between the lateral areas of the brain gives rise to a somewhat symmetrical
B0-distribution, which can be more easily compensated by conventional
spherical-harmonic B0-shim hardware.
This is in line with the results of the metabolite quantification: No
significant differences between the metabolite concentrations of the
vGRAPPA-decomposed sMVS spectra and neither SVScomb nor SVSind
for Glu, NAA, tCr, and tCho were observed (Fig.2b-e) in the motor cortex voxels,
while the obtained concentration differences in the
dorsal/ventral regions vary up to -16.2% for tCho in the GM-rich voxel between
SVScomb and SVSind (Fig.3a/c). Conclusion
In
conclusion, we have demonstrated, that an sMVS application with the investigated pulse and a distance of
10mm or more is feasible and not impaired by B1+-effects
on the inversion profile of the MB pulse. Furthermore, simultaneous optimization of B0 and B1+-adjustments does not significantly hamper the quantification in a region with a
somewhat symmetrical and benign B0-distribution, such as the motor
cortices. In a dorsal/ventral region, on the other hand, the results regarding
linewidth, SNR, and metabolite concentration quantification accuracy indicate
the need for more sophisticated, and most likely hardware-based, B0
and B1+-optimization solutions, to avoid reduced data
quality in sMVS applications in these more challenging, non-symmetrical
regions.Acknowledgements
No acknowledgement found.References
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