Vivek TIWARI1, Sandeep Ganji, ZhongXu An, and Changho Choi
1UT Southwestern Medical Center, Dallas, TX, United States
Synopsis
Gliomas harboring mutations in
Isocitrate-Dehydrogenase (IDH) 1/2 exhibits a neomorphic-activity resulting in
production of 2-hydroxyglutarate (2HG) by 2-3 orders of magnitude. Non-invasive
detection of 2HG using conventional 1H Magnetic Resonance Spectroscopy
(MRS) is challenging due to extensive overlap with the resonances of
neighboring metabolites. Here we have designed a TE-Averaged PRESS 1H-MRS
that reduces the spectral-overlaps of GABA, Gln, Glu and glutathione signals on
2HG-2.25ppm-resonance that provides a reliable-detection of 2HG. We have also
estimated T2 in each brain-tumor by taking the advantage of multiple-TEs used
in TE-averaging acquisitions, and used patient-specific T2 for estimation of 2HG.
Introduction
Gliomas
harboring mutations in Isocitrate-Dehydrogenase (IDH) 1/2 exhibits a
neomorphic-activity resulting in production of 2-hydroxyglutarate (2HG) by 2-3
orders of magnitude1,2. Noninvasive identification of elevated 2HG
has gained significant clinical use in patient care3,4. Non-invasive
detection of 2HG using conventional 1H Magnetic Resonance Spectroscopy
(MRS) is challenging due to extensive overlap with the resonances of
neighboring metabolites. The 2HG 2.25 ppm resonance is obscured by GABA-C2,
Glutamate-C4 (Glu), and Glutamine-C3 (Gln) signals. Currently one of the well-established point-resolved spectroscopy (PRESS)
1H-MRS strategy for 2HG-detection employs an echo-time (TE) of
97ms3,5 which is also limited by extensive overlaps from neighboring
resonances. The 2HG and interference resonances are all strongly-coupled
consequently, the coherences evolve with TE in complex manners. Constructive or
destructive addition of these coupled signals by averaging the signals from
varied TE may help to diminish the spectral overlaps on 2HG 2.25ppm resonance.
Here we have optimized a TE-Averaged PRESS 1H-MRS that reduces the
spectral-overlaps of GABA, Gln and Glu and glutathione (GSH) signals on 2HG
2.25ppm resonance and provides a reliable detection of 2HG in IDH–mutant gliomas.
Moreover tumors have altered inter/intra-cellular environment thus may have
different Transverse-relaxation time (T2) in different tumor-types and grades which
can significantly influence quantifications of metabolites. Therefore we have
also estimated T2 in each brain tumor by taking the advantage of multiple TEs
used in TE-averaging acquisitions, and have incorporated patient-specific T2
for estimation of metabolites. Methods
Density-Matrix
simulations were performed to obtain signal-pattern and strength of major
metabolites at different TEs of PRESS by varying the TE2. TE1 was fixed at 32ms.
Possible combinations of number of TEs were tested to obtain a reliable 2HG
upright-signal with reduced spectral-overlaps from GABA, Gln and Glu, and GSH.
Optimized combination of TEs were used to obtain In-vivo spectra from Glioma patients. The protocol was approved by
the Institutional-Review Board. 1H MR Experiments were carried
out on a whole-body 3T scanner (Philips Medical Systems). Water-suppressed and unsuppressed water data
was acquired from a FLAIR enhancing region at the optimized train of TEs from a
defined voxel, using TR = 2 s, sweep width = 2500 Hz, sampling-points
= 2048 and number of averages = 16 for each TE. Water signal was suppressed
using a four-pulse scheme. Data was apodized with a 2-Hz exponential filter.
Eddy- current-compensation and frequency-drift corrections were performed using
in-house Matlab programs. Metabolite
signal estimates were calculated using LCModel software. Different basis sets
were prepared for each patients by incorporating T2 values of that specific
tumor, using published chemical shift and J coupling constants with volume-
localization-RF and gradient-pulses. Correlation significance-test was done to
determine if the T2s of Cho and other measurable resonances have any relation
in different tumors. Results and Discussions
Combination of n=12 TEs with fixed TE1=32ms
and variable TE2 with difference of 15ms beginning at TE2=26 ms yielded ~40%, ~39%
and 30% reduction of Glu, GABA, and Gln signals compared to PRESS 97ms signal
strength. TE-Averaged signal of 2HG upon incorporation of T2 of 180 ms was ~43%
of that in PRESS spectra and almost had a flat baseline as the complex positive
and negative overlapping signals from GSH, GABA, Glu and Gln near 2.25ppm got destructively
added due to multiple-TE-averaging (Fig1). T2-incorporated (180 ms) TE-averaged
signal-pattern of calculated-spectra of major coupled resonances was not
different than that obtained without-T2 incorporation, but had substantially
reduced signal strength (Fig.2). Monoexponential fitting of Cho, and Cr signals
yielded mean Cho-T2 of 288±50 ms, and Cr-T2 of 186±20 ms across the 15-glioma
patients. Cho-T2 and Cr-T2 within-tumors were found to be significantly (p=0.0003)
correlated (Fig.3). TE-Averaged spectra from a Low-Grade-Glioma tumor (Fig. 4B)
shows reduced 2HG-Glu, 2HG-Gln and GABA correlation-coefficients compared to TE-97ms
data (Fig4 B and D) indicating the independence of 2HG signals from these-neighboring
metabolites (Fig.4A) compared to PRESS-97ms estimates. Fig.5 shows TE-averaged
data from an IDH-mutant Grade-2 oligodendroglioma with ~30% reduced-CRLB of 2HG
compared to PRESS-97ms, and also exhibits higher 2HG estimate upon
incorporation of patient-specific T2. Further, Gln and GABA signals were almost
nulled in TE-averaged spectra (Fig.5B) thus indicating reliable detection of
2HG without significant contamination from the neighboring resonances compared
to PRESS 97ms estimation.Conclusion
2HG-optimized TE-averaged spectra had minimal
overlap and baseline distortion thus enables precise detection of 2HG. Correlation
coefficients and CRLBs were smaller in TE-averaged spectra, and also Gln, GABA
and GSH signals underneath 2HG were almost nulled indicating the successful application
of optimized TE-averaging method for reliable 2HG estimation.Acknowledgements
National
Cancer Institute of the National Institutes of Health under Award Number
R01CA184584 and by a Cancer Prevention Research Institute of
Texas grant RP130427. References
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