Michal Povazan1,2, Adam P Berrington3, and Peter B Barker1,2
1Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, School of Medicine, Baltimore, MD, United States, 2F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, 3Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
Synopsis
The most common method
for proton MRS quantification is the linear combination of model basis spectra.
Typically, these model spectra are simulated using density matrix formalism. Here
we aimed to compare the quantification using two basis sets with full
localization and real RF pulses and one basis set with non-localized ideal RF
pulses. Statistically significant differences were found
between metabolite concentrations quantified in LCModel with different basis
sets. Whereas two models that used localized real RF pulses were not
significantly different for the major metabolites, the ideal basis set differed
in concentration for all metabolites except NAA.
Aim
To compare quantification of 1H-MRS
brain spectra using basis sets created in two different software packages that fully
simulate spatial localization effects, and a basis set created with ideal RF
pulses without localization.Introduction
Spectral quantification represents a crucial portion of an MRS
experiment. One of the most widespread methods in 1H-MRS involves
fitting the spectrum to a linear combination of model basis spectra that are
typically simulated using the density matrix formalism. Multiple software
packages are available for simulation of MRS basis spectra1–4. These are all capable of importing user-defined RF
pulses and gradient waveforms thus enabling simulations that reflect spatial
variations of the simulated basis spectra within the localized volume. This is
particularly important for quantification of J-coupled metabolites5,6. Whereas the physical principles of all numerical
simulations are the same (i.e. quantum mechanical density matrix formalism), the
implementations vary substantially. In addition, the combination of
individually simulated metabolite moieties into a basis spectrum and the scaling
of the basis spectra is also software-specific and may affect quantified
results. This abstract reports on the comparison of quantification of 1H-MRS
PRESS data using two basis sets created in two different software packages incorporating
spatial localization effects, and also a basis set simulated with non-localized
ideal RF pulses. Methods
Spectra from a mid-parietal voxel (3x3x3 cm3, Fig.1A) were
recorded from 12 healthy volunteers (7M/5F; mean age = 29 yrs) on a 3T Philips Ingenia
scanner with a 1Tx/32Rx head coil using the vendor-supplied PRESS sequence
(Fig.1C) with the following parameters: TE/TR=35/2000ms; spectral width=2kHz;
NT=64; 2048 data points and VAPOR water suppression. Water unsuppressed data
were acquired with similar parameters and NT=8. Spectra were pre-processed
using an automated in-house developed script based on FID-A1 and quantified in the range 0.5 to 4.2 ppm with
LCModel version 6.37. The quantified results were corrected for CSF and
tissue fraction.
RF numerically optimized refocusing pulses (6.9 ms ‘gtst1203’; B1max,13.5μT;bandwidth,1.26kHz) phase cycling, delays and
crusher gradient schemes were implemented based on the experimental PRESS
sequence in FID-A1 and MARSS2. In MARSS, the excitation pulse (7.1 ms asymmetric
sinc) was also part of the simulation. Chemical shifts and J-coupling constants
of 19 metabolites were obtained from Govindaraju8 and Near9. The 30x30x30 mm3 voxel was simulated
with the 5kHz simulation bandwidth and 4096 points at 40x40x40 spatial
locations, which were summed together after simulation. The reference peak at 0
ppm necessary for LCModel analysis was also modeled in the corresponding
packages. Additionally, one ‘non-localized’ basis set was created assuming ideal
(instantaneous) RF pulses using our in-house script.
The mean metabolite concentrations were compared in SPSS 22 with repeated
measures ANOVA with Greenhouse-Geisser correction. A post-hoc test with
Bonferroni correction was used for pairwise comparison.Results
Acquired spectra showed high SNR and low variability between volunteers
(Fig.1B). The profile of the spectral fits was qualitatively similar between “FID-A”
and “MARSS” simulation (Fig.2). More prominent differences were observed for the
ideal simulation, especially for J-coupled metabolites
(Fig.2;glucose,myo-inositol). This is also reflected in the comparison between
average fits, where 4ppm-3.5ppm and 2.9ppm-2.2ppm regions are the most affected
(Fig.3). GABA, glutamine, gluthathione, phosphorylethanolamine and total
choline were significantly different for all three basis sets (all p<0.005)(Fig.4A).
Quantification with the Ideal basis set yielded metabolite levels significantly
different in all but one metabolite (NAA; ideal vs. FID-A, p=0.135; ideal vs.
MARSS, p=0.28). Cramer-Rao Lower Bounds were below 10% for 7 quantified
metabolites (Fig.4B).Discussion
Statistically significant differences were found between metabolite
concentrations quantified in LCModel with basis sets simulated using three
different methods. Results quantified with FID-A and MARSS basis sets were
similar for major metabolites (i.e. tNAA,tCr,mI,Glx,Glu, but not tCho). The ideal
basis set differed in concentration for all but one (NAA) metabolite.
It was previously shown, that an ideal simulation may not be sufficient
for accurate quantification5,10, which may explain the concentration differences of
ideal basis set reported herein. The small bandwidth of the refocusing pulses is
reflected in a relatively high chemical shift displacement (at 3T, 26% between
water and NAA in one direction), which may exacerbate the spatial effects in
the measured spectrum. These effects become more severe at ultra-high fields,
in sequences with more pulses, or with spectrally selective pulses6. The
differences in concentration found for some minor metabolites quantified with
FID-A and MARSS remain unclear. MARSS simulation includes excitation effects
as well, which may better model the chemical shift displacement artefact across
the excitation direction. The difference in scaling of the individual moieties
before construction of the basis set – such as glycerophosphorylcholine and
phosphorylcholine in the signal of total choline may be another factor, but
further investigation is needed. Future work will focus on comparing other
software packages used for basis set simulation as well as better analysis of
the discrepancies found for the compared packages.Acknowledgements
No acknowledgement found.References
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