Multi-Vendor Implementation and Comparison of Density Weighted Concentric Ring Trajectory Magnetic Resonance Spectroscopic Imaging

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Multi-Vendor Implementation and Comparison of Density Weighted Concentric Ring
Trajectory Magnetic Resonance Spectroscopic Imaging
Uzay E Emir , Ralph Noeske , Xin Shen , Antonia Susnjar , Katrinus Keijnemans , Joseph Rispoli , Gregory Tamer, Jr. , Nathan Ooms , Mark Chiew , Albert Thomas , and Vincent O Boer
School of Health Sciences, Purdue University, West Lafayette, IN, United States, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States, Applied Science Laboratory Europe, GE
Healthcare, Berlin, Germany, Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 2 Wellcome Centre
for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom, Department of Radiological Sciences, University of California, Los Angeles, CA, United States
Synopsis
In this study, we have developed and demonstrated a sequence for fast MRSI, using a gradient offset independent adiabatic (GOIA)-semi-LASER
sequence with a density-weighted (DW)-concentric rings trajectory (CRT) with an in plane resolution of 5 mm. The sequence performed robustly
between three different vendor using 3T MRI scanners, within a clinically feasible acquisition time. DW-CRT has been validated in a series of phantom
experiments and its feasibility assessed in a healthy volunteer.
Introduction
Complementary to MRI, magnetic resonance spectroscopy imaging (MRSI) techniques may be utilized to reveal abnormalities before any visible macroscopic
changes in brain anatomy and physiology occur in the disease condition (1). For instance, neurochemicals that can be mapped non-invasively in the human
brain include endogenous neurotransmitters; glutamate (Glu) and gamma-aminobutyric acid (GABA), a marker of neuronal loss/dysfunction; N-acetyl aspartate
(NAA), a marker for deficits in energy metabolism; Creatine (Cr), a marker for cell membrane turnover; Choline (Cho) and an oncometabolite; 2-Hydroxyglutarate
(2-HG). The major barrier to the widespread use of 1H-MRS imaging (MRSI) is the lack of harmonization of acquisition and post-processing protocols between
different MR-system vendors (1). Different pulse sequences on MR scanners from different vendors result in a lack of reproducibility in quantitative MRSI results
from different sites. Identical MRSI protocols between sites would allow reference measurements for concentrations and corresponding standard deviations of
neurochemicals, like was recently established for single-voxel MRS sequences using high-quality short TE semi-LASER localization (2). This effort however is
highly challenging due to the large differences in hardware and software between vendors. Therefore, the aim of this study was to harmonize data acquisition
and post-processing of short TE 2D 1H-MRSI using the semi-LASER sequence with density-weighted concentric trajectory (DW-CRT) (3) at 3T across three
different vendors (Philips, Siemens, and GE), and to determine metabolite distributions, accuracy, and reproducibility in metabolite levels in the “braino”
phantom and an adult human brain.
Methods
Data were acquired using 3T scanners equipped with an MR console from Philips, Siemens, and GE. 32 channel receive-only coil was used at the GE and
Philips scanners. A 64 channel receive-only coil was used at the Siemens scanner. Two healthy volunteers (one on Philips, one on both GE and Siemens)
participated in the study, written informed consent was obtained from the volunteers according to the local ethical guidelines. 2D MRSI scans were collected
from a single slice. The imaging box was positioned inside the brain, to cover the entire motor cortex bilaterally (Figure 1). A 2D density-weighted concentric k-
space trajectory with 96 unique rings was used to sample polar k-space data (3). A high in-plane resolution (5 mm x 5 mm) with thickness 10 mm was achieved
using FOV = 240 mm x 240 mm , gradient offset independent adiabatic (GOIA)-semi-LASER (2) localization = 145 mm × 120 mm × 10 mm, TR = 2000 ms, TE = 32 ms
(Figure 2). The acquisition duration was 192 ms, using 64 (Siemens), 66 (GE) and 250 (Philips) points per ring with an effective spectral bandwidth of 1250 Hz.
Second-order shimming was used in all cases. An additional unsuppressed water scan was acquired to remove residual eddy current effects and to combine
the phased‐array coil spectra. VAPOR was used for water suppression. the outer volume saturation pulses were only used for Siemens and GE. The MRSI
sequences were also tested on "briano" phantom for all vendors. Reconstruction algorithms were implemented in MATLAB (MathWorks, Natick, MA, USA).
NUFFT gridding was performed without using any posthoc density compensation (4), as this is not required for DW-CRT data.
Results
The acquisition and preprocessing enabled the construction of high-resolution MRSI data from three different scanners (Philips, Siemens, and GE). Phantom
experiments to assess metabolite spectral quality was performed on a "braino" phantom (GE) (Figure 3) and show similar spectral quality for the three different
vendors, although the water image shows the remaining differences in the spatial localization using DW-CRT MRSI. Similarly, in vivo measurements were
performed to evaluate the localization accuracy and spectral quality (Figure 4). Again, some level of image variation between the vendors is seen, but good
spectral quality could be reached in all three scans.
Discussion
Despite large differences in hardware and the software between the three used vendors, we have developed and demonstrated a fast MRSI sequence with
good localization performance using a GOIA-semi-LASER sequence with DW-CRT that performs at 3 Tesla of Philips, Siemens, and GE and within a clinically
feasible acquisition time. DW-CRT has been validated in a series of phantom experiments and its feasibility assessed in a healthy volunteer with an in-plane
resolution of 5×5 mm . Future work will focus on evaluating and improving the accuracy and reproducibility obtained with the semi-LASER MRSI sequence in
this multi-center, multi-vendor setting, including accurate gradient mapping to identify k-space trajectory differences between the different sets of hardware.
Acknowledgements
No acknowledgement found.
References
1. Wilson M, Andronesi O, Barker PB, et al. Methodological consensus on clinical proton MRS of the brain: Review and recommendations. Magn Reson Med
2019
2. Berrington A, Deelchand D, Joers J, Považan Michal, Schär M, Gillen J, Barker P, Öz G. Cross-vendor standardization of a 3 T MRS protocol with semi-
LASER. In: Proc Intl Soc Mag Reson Med 27. ; 2018.
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2. 11/6/2019 https://submissions2.mirasmart.com/ISMRM2020/ViewSubmission.aspx?sbmID=6638
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3. Chiew M, Jiang W, Burns B, et al. Density‐weighted concentric rings k‐space trajectory for 1H magnetic resonance spectroscopic imaging at 7 T. NMR
Biomed 2018;31.
4. Fessler JA, Sutton BP. Nonuniform fast Fourier transforms using min‐max interpolation. IEEE Transactions on Signal Processing 2003.
Figures
Figure 1: The imaging box was positioned inside the brain, to cover the entire motor cortex bilaterally.
Figure 2: GOIA-semiLASER localization with DW-CRT k-space trajectory.
Figure 3: Braino phantom: Water images and 4×4 spectra from positions marked by the yellow box.
Figure 4: In vivo: Water images and 4×4 spectra from positions marked by the yellow box.