Robert Borowiak1,2, Wilfried Reichardt1,2, Dmitry Kurzhunov1, Christian Schuch3, Jochen Leupold1, Thomas Lange1, Marco Reisert1, Axel Krafft1,2, Elmar Fischer1, and Michael Bock1
1University Medical Center Freiburg, Dept. of Radiology - Medical Physics, Freiburg, Germany, 2German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany, 3NUKEM Isotopes Imaging GmbH, Alzenau, Germany
Synopsis
In
this work, we demonstrate the feasibility of monitoring glucose uptake in mouse
brain using direct 17O-MRS at 9.4 Tesla for the first time. Time-resolved
17O-MRS spectra (temporal resolution: 42 s) are acquired in vivo after injection of D-glucose with
17O-labeled hydroxyl groups. The cerebral rate of glucose metabolism
CMRGlc is estimated using a pharmacokinetic model in an anesthetized
(1.25% isoflurane) mouse to 0.43 ± 0.21 µmol/g/min,
which is of the same order of
magnitude as reported by 18F-FDG PET.Introduction
Altered
glucose uptake is associated with altered pathologies - malignant tumors, for
example, gain energy by anaerobic glycolysis (Warburg effect [1]). The clinical
gold standard to monitor metabolic rates of glucose is FDG-PET, which uses the radioactively
labeled [18F]-fluordeoxyglucose (FDG). As a non-radioactive alternative
to FDG-PET we propose to use dynamic 17O-MRS of 17O-labeled
D-glucose [2-4] to assess the metabolic glucose pathway.
Material & Methods
To optimize the acquisition parameters for dynamic 17O-MRS
in mouse brain, phantom experiments (Fig. 1) were conducted with 17O-labeled
D-glucose (Nukem Isotopes Alzenau, Germany) on a 9.4 Tesla animal MR system
(Bruker BioSpin). For RF excitation and signal reception a two-turn 2 cm
diameter surface coil tuned to the 17O frequency (54.271 MHz) was
built, and spectra were acquired with an FID sequence.
Animal preparation:
Each mouse was anesthetized (4% induction/1.25% continous rate of isoflurane) prior to introducing a catheter into the tail vein.
During the MRS experiment the mouse was continously anesthetized with 1.25% isoflurane, breathing rate and body temperature were monitored
and kept as stable as possible.
After placing the surface coil on the mouse brain,
baseline spectra were acquired over 27 min. The following MRS parameters
were used: spectral bandwidth 62.5 kHz, pulse length 62.5µs, acquisition
delay 25µs, TE = 56µs, TR = 5.4ms,
flip angle α ≈ 90, 5791 averages, Tacq = 5ms, 313 points
were sampled with a dwell time of 16µs. Then, a solution was injected through
the catheter which consisted of 80mg of either 17O-labeled 1-glucose,
1,6-glucose, 6-glucose, or unlabeled glucose dissolved in 200µl 0.9% NaCl,
and 17O spectra were acquired over the course of up to 163 min (temporal
resolution: 42 s). Glucose uptake was measured from the signal change
of the H217O water peak.
In the phantom, the 17O spectra (Fig.1) were
quantified in the time domain using the HLSVD algorithm of JMRUI [5]. In the
dynamic in vivo spectra, at first the
H217O peak was separated from the short-T2
glucose peak at -11 ppm by discarding initial points from the FID emulating an echo time
of TE = 216ms.
H217O signal intensities were quantified from the peak
height of the magnitude spectra, and converted into absolute H217O
concentrations by normalizing to the natural abundance of 17O (assuming
a mouse brain weight of 0.4g and water content of 73%). The dynamics of 1-glucose
and 6-glucose peaks were plotted after suppressing the water peak with HLSVD
(Fig. 2).
Since the anomeric 1-OH position has a temperature and
pH-dependent chemical exchange with unlabeled water in solution [6,7], only the
time course of the 6-glucose experiment was chosen to further investigate glucose
metabolism. Using a pharmacokinetic model [8], the time course of the H217O
data was fitted yielding cerebral rates of glucose metabolism CMRGlc (Fig. 3).
Glucose enrichment factor α in blood was estimated from separated measurement
of blood sugar concentration and included as constant fit-parameter. Note that,
the model was modified by considering that 1mol 6-glucose is converted into 1mol
H217O.
Results & Discussion
In the phantom spectra the following line widths and chemical
shifts relative to the water peak (FWHM =2 ppm) were obtained:
Δf
1-OH = 40±2 ppm / FWHM
1-OH = 27ppm, Δf
6-OH = -11 ± 2 ppm /
FWHM
6-OH =13ppm. The chemical shifts of the 1-OH and 6-OH
position are in good agreement with literature [2], if a mixture of 36% α and
64% β glucose is assumed.
In vivo line widths and chemical shifts were similar
to those of the phantom measurements. In all
in vivo experiments with labeled glucose
a H
217O signal increase of about 12-47% was observed, whereas no increase of H
217O
signal was seen with unlabeled glucose. From the model fit, a CMR
Glc of 0.43 ± 0.21 µmol/g/min
was found which is about 65% higher
than literature value of 0.26 ± 0.10
µmol/g/min measured with
18F-FDG PET in mouse under 1.0% isoflurane
[9]. The delay of about 13 min between bolus injection and signal increase
in glucose-6 experiment is 56% longer compared to a
13C glucose bolus
experiment performed in humans without anesthetic [10].
In this work, dynamic
17O-MRS spectra are
acquired
in vivo in mouse brain for the
first time. From the concentration time courses metabolic rates were obtained
which indicate that the labelled oxygen in glucose is transformed into H
217O
water by glycolysis. The deviations from literature values can be a result of
uncertainties in the model fit, or chemical exchange processes that occur
before glycolysis.These measurements are a first step towards a MR-based
method for the quantification of glucose metabolism.
Acknowledgements
Authors would like to thank Prof. Dr. Dieter Leibfritz for fruitful discussion. Financial support from NUKEM Isotopes Imaging GmbH is gratefully acknowledged.
References
[1] Warburg O Science (1956) 123: 309-314
[2] Gerothanassis IP et al. JMR
(1982) 48: 431-446
[3] Schulte J et al.
JMR (1993) 101:95-97
[4] de Graaf R et al. JMR (2008) 193:63-67
[5] Naressi A Magma et al. (2001) 12:141-152
[6] Risley JM et al. Biochemistry (1982) 21: 6360-6365
[7] Mega TL et al. J.Org.Chem. (1990) 55: 522-528
[8] Atkinson IC et al. NeuroImage (2010) 51: 723-733
[9] Tomayo H et al. (2004) J Nucl Med. 45: 1398-1405
[10] Mason GF et al. (2003) Brain Research Protocols.
10: 181-190