Tangi Roussel1, Jens T. Rosenberg2, Samuel Colles Grant2,3, and Lucio Frydman1,2
1Chemical Physics, Weizmann Institute of Science, Rehovot, Israel, 2Center for Interdisciplinary MR, National High Magnetic Field Laboratory, Tallahassee, FL, United States, 3Chemical & Biomedical Engineering, Florida State University, Tallahassee, FL, United States
Synopsis
This study explores new
opportunities that ultra-high field combined with non-water-suppressed 1H MRS
methodologies make possible regarding the profiling of signals that resonate
downfield from the water peak. Studies were carried out on rats using a 21.1-T ultra-widebore system, and focused on quantitatively analyzing the metabolic
concentration changes for ischemic stroke and glioblastoma tissues. A general
decrease in the relative metabolic concentrations were observed for both
pathologies, certain molecules depart from this trend: lactate, glutathione
(stroke), choline and UDP-Nacetyl hexosamines (glioma). Potential explanations
for these features and new research avenues opened by these types of
measurements are discussed.Purpose
Improvements in the MR acquisition hardware
coupled to the growing availability of ultra-high field magnets, are enabling
the acquisition of in vivo MR spectra without water suppression.
1,2 Moreover, the use of selective spectral
excitations allows one to exploit the abundant reservoir of magnetically
unperturbed spins, to enhance the longitudinal recovery of the excited
metabolic or macromolecular sites.
3,4 Several
of the peaks resonating downfield from the water resonance originate from
exchangeable protons of -NH and -OH groups present in metabolites
5, and become visible only when avoiding water
suppression. Previous studies have detected downfield histidine, homocarnosine
and phenylalanine peaks in human and mouse brain
6; glucose (Glc), glutathione (GSH) and NAD+ were
also unambiguously assigned.
7,8,9 Based
on chemical shifts databases, attempts have been made to assign resonances
observed in the 6-9 ppm region to additional metabolites such as adenosine
triphosphate (ATP), N-acetyl aspartate (NAA), glutamine (Gln), histamine, tyrosine
and tryptophan.
10 This paper explores the use of Relaxation
Enhanced (RE) MRS techniques using selective pulses to avoid water suppression
and to record
in vivo localized spectra from the downfield
1H region at
21.1 T. The study was carried out on rats subjected to cerberal ischemia or glioblastoma.
Methods
Brain ischemia model. To mimic brain ischemia, middle
cerebral artery occlusion (MCAO) was performed on six Sprague-Dawley rats for
1.5 h followed by re-perfusion. The animals were imaged 24 h following the
occlusion.
Glioblastoma
model. 9L glioma rat cells were cultured and expanded in DMEM+10%FBS.
100,000 9L glioma rat cells were injected at 2 mm anterior, 2.5 mm lateral and
3.5 mm deep with respect to Bregma. Five male Sprague-Dawley rats were used.
MRS acquisitions. All experiments were performed at
the NHMFL using an ultra-wide bore 21.1-T vertical magnet, a Bruker Avance III
MRI console and a home-built probe incorporating a transmit/receive quadrature
surface coil. in vivo 1H
RE-MRS experiments were performed using a localized spin-echo sequence (Figure
1) for which spectrally selective pulses were employed to excite and refocus
the 5.5-9.5 ppm range. The excitation was performed using a 5.55-ms, 10-lobe sinc pulse, and a 4-ms refocusing
Shinnar-LeRoux pulse. Spatial localization was carried out using 3D LASER11 incorporating six consecutive 5-ms adiabatic
180° pulses leading to a minimum echo time of 55 ms. The upfield spectral region
(0-4 ppm) also was explored by adjusting frequency offsets. 512 to 1024
averages were acquired (TR=1.5-2.5 s) from two different voxel localizations
(Figure 2) with an average volume of 90 µL, centered on diseased and healthy
regions.
Data quantification. The spectroscopic data were
processed and quantified with customized MATLAB software; the quantification
stage relied on a GAMMA-library-based algorithm12 originally developed for in vivo 2D
MRS time-domain quantification.13 This
fitting model incorporates a predefined set of 1D metabolic spectral traces
with known frequency shifts, keeping concentrations and linewidths as
adjustable parameters. As most of the potential metabolites contributing to the
downfield spectral region have too low a concentration to be detectable
(≤100 µM), the metabolite basis set used here contained only ATP, Gln, GSH and
NAA--all of these present at ≥1 mM concentrations--and four broad gaussian
resonances to model the spectral baseline.
Results
in vivo downfield
1H
spectra show rich metabolic information. Figure 3 compares upfield and
downfield spectral regions acquired on normal and diseased tissues. An average
SNR of 40 was calculated on the 7.8-ppm peak. The result of a typical spectral
quantification is displayed in Figure 4; this procedure was applied to all spectra.
Discussion
Concentrations appear to be
globally lower in ischemic and glioma tissue than in normal brain tissue for
all metabolites (Figure 5). Exceptions in this trend are given by (i) GSH,
whose 23% increase in ischemic tissue could reflect a neuroprotective measure
against oxidative stress; and (ii) Cho, whose 30% increase in glioma tissue is
probably a consequence of tumor cell proliferation. Moreover, a 5.9-ppm peak
shows a marked, statistically significant increase (45%) in the tumor tissue.
Previous NMR studies on cells
14,15 assigned this resonance to UDP-NAc, which is
known to be an abundant metabolite upon cancer proliferation.
Conclusion
By avoiding water excitation, the
RE-MRS sequence led to high quality, spectra with well-resolved resonances and
low spectral baseline distortions--not only for the classical upfield peaks but
also for the more elusive downfield resonances. The method’s main limitation is
its relatively long echo time, a consequence of B
1 power limitations. This potential bias
notwithstanding, led to quantifiable
1H downfield MR spectra that highlighted
systematic differences between healthy and non-healthy tissues, which could
serve as potential biomarkers as well as providing better understanding of
disease development.
Acknowledgements
The authors wish to thank
Professor Cathy Levenson for providing 9L glioma cells and advice on the
surgical procedure. This work was performed at the National High Magnetic Field
Laboratory (NHMFL), which is supported by NSF DMR-1157490 and the State of Florida.
Funding was also provided by the NHMFL User Collaboration Grant Program and the
American Heart Association Grant-In-Aid program (10GRNT3860040) (to SCG). The
authors also wish to thank the Israel Science Foundation (grant 795/13), Helen and Martin Kimmel Institute of Magnetic Resonance (Weizmann Institute)
and generosity of the Perlman Family Foundation (to LF).References
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