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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Magn Reson Med. Author manuscript; available in PMC 2013 December 1.
Published in final edited form as:
PMCID: PMC3376665
NIHMSID: NIHMS348669

Metabolite Kinetics in C6 Rat Glioma Model Using MRSI of Hyperpolarized [1-13C]Pyruvate

Abstract

In addition to an increased lactate-to-pyruvate ratio, altered metabolism of a malignant glioma can be further characterized by its kinetics. Spatially resolved dynamic data of pyruvate and lactate from C6-implanted female Sprague-Dawley rat brain were acquired using a spiral chemical shift imaging sequence after a bolus injection of a hyperpolarized [1-13C]pyruvate. Apparent rate constants for the conversion of pyruvate to lactate in three different regions (glioma, normal appearing brain, and vasculature) were estimated based on a two-site exchange model. The apparent conversion rate constant was 0.018±0.004 s-1 (mean ± standard deviation, n=6) for glioma, 0.009±0.003 s-1 for normal brain, and 0.005±0.001 s-1 for vasculature, whereas the lactate-to-pyruvate ratio, the metabolic marker used to date to identify tumor regions, was 0.36±0.07 (mean±std), 0.24±0.07, 0.12±0.02 for glioma, normal brain, and vasculature, respectively. The data suggest that the apparent conversion rate better differentiate glioma from normal brain (P=0.001, n=6) than the lactate-to-pyruvate ratio (P=0.02).

Keywords: hyperpolarized 13C, glioma metabolism, metabolite kinetics, magnetic resonance spectroscopic imaging

Introduction

Glioblastoma multiforme (GBM), one of the most aggressive and common brain tumors, remains a major clinical problem with most patients succumbing within two years after being diagnosed [1]. Although new treatments with improved effectiveness have been actively developed in the last decade [2-4], there is still a need for methods that can be used to optimally gauge treatment response.

Similar to other aggressive cancers, glioma tissues derive a disproportionate amount of energy via glycolysis, which results in high glucose utilization and increased lactate production [5, 6]. This unique metabolism forms the basis of [18F]fluoro-2-deoxyglucose (FDG) using positron emission tomography (PET), which indirectly monitors the altered tumor metabolism through the uptake of FDG into tumor tissue, a technique that has been widely applied to brain tumor detection and monitoring the response to treatment. However, this method is hampered by high FDG uptake in surrounding gray matter [7-9].

Proton (1H) [10-13] and 13C [14, 15] magnetic resonance spectroscopy (MRS) has also been utilized to study elevated lactate and tumor metabolism in vivo. However, the performance of 13C MRS is typically poor due to both low sensitivity and low natural abundance of 13C, resulting in insufficient signal intensities of 13C metabolites to yield localized spectra. 1H MRS has an improved signal-to-noise ratio (SNR) compared to 13C MRS due to the higher gyromagnetic ratio and natural abundance, but still requires a long acquisition time to achieve sufficiently high SNR. As a result, to date, only the steady-state concentration levels of spatially localized metabolites have been typically assessed in vivo.

Dynamic nuclear polarization (DNP) in combination with the recent development of a dissolution process that retains the increased polarization into the liquid state opened new possibilities for the real-time investigation of in vivo metabolism [16, 17]. Metabolic imaging of hyperpolarized compounds, especially [1-13C]pyruvate, shows great potential for cancer detection and treatment monitoring [18-20], which is also illustrated by the initiation of the first human trial using this technology for the evaluation of prostate cancer [0]. More information about the clinical trial can be found at clinicaltrials.gov (NCT01229618: A phase 1 ascending-dose study to assess the safety and tolerability and imaging potential of hyperpolarized pyruvate (13C) injection in subjects with prostate cancer).

Hyperpolarized [1-13C]pyruvate has also been used for single-time and dynamic metabolic imaging of healthy rat brains [22, 23] and, more recently, it has been applied to rat brain with human xenografts, U-251 MG and U-87 MG, by Park et al. [24] using a single-time point magnetic resonance spectroscopic imaging (MRSI) and dynamic MRS. Park et al. [25] further investigated the response of the U-87 MG to temozolomide treatment using single-time MRSI. Moreover, Day et al. [26] evaluated the treatment response of C6 rat glioma to radiotherapy using single-time MRSI and dynamic MRS, and observed early changes in tumor metabolism. In these studies, single-time 13C MRSI was able to differentiate tumor from normal brain using lactate-to-pyruvate peak ratio.

This paper applied dynamic MRSI to measure spatially-resolved apparent rate constants for the conversion of pyruvate to lactate, kPL, in a rat glioma model using a spiral chemical shift imaging (CSI) sequence [27], and compared kPL with the lactate-to-pyruvate ratio as a metric to differentiate glioma from normal brain tissue.

Methods

Animal model and polarization procedure

Six female Sprague-Dawley rats were implanted with one million C6 glioma cells, derived from an N-methyl-N-nitrosourea (MNU)-induced tumor [28] into the right striatum as previously described [29, 30]. Additionally, a healthy Sprague-Dawley rat was used to verify the apparent conversion rate constants and lactate-to-pyruvate ratio of normal brain and vasculature. Table 1 summarizes the animals' body weight, tumor growth, and the number of injections that each animal received. Tumor size was estimated by measuring hyper-intense regions from contrast-enhanced T1-weighted proton images.

Table 1
Animal preparation Characteristics of the six animals with glioma cell implantation (G1-G6) and a healthy rat (H1). Tumor volumes were estimated by measuring the hyper-intense regions in contrast-enhanced T1-weighted proton images.

Eight to ten days after tumor implantation, animals were anesthetized with 1.5-3.0 % isoflurane in oxygen (~1.5 L/min) and a catheter was inserted into the tail vein for intravenous administration of the hyperpolarized substrate. Respiration, temperature, heart rate, and oxygen saturation were monitored throughout the duration of the MR experiments. Temperature was maintained at 37 °C using a temperature-controlled warm water blanket underneath the animal. A HyperSense DNP system (Oxford Instruments Molecular Biotools, Oxford, UK) was used to produce an 80-mM solution of hyperpolarized [1-13C]pyruvate (for details of the polarization and dissolution procedure, see [31]). Based on the solid-state polarization and independent calibration experiments, the liquid-state polarization was calculated to be approximately 25 %. A volume of 2.2-3.0 mL of the solution with a pH of approximately 7.5 was injected through the tail vein catheter at a rate of 0.25 mL/s followed by a flush of 0.5 mL of saline with 1 % heparin to clear the line. The amount of injected solution was adjusted to maintain a dose of 1 mmol/kg body weight. The time interval from dissolution to injection ranged from 19 to 22 s. All procedures were approved by the local Institutional Animal Care and Use Committee.

Imaging and histology protocol

All experiments were performed on a 3 T Signa MR scanner (GE Healthcare, Waukesha, WI) equipped with a high performance insert gradient coil operating at a maximum amplitude of 500 mT/m with a slew rate of 1865 mT/m/ms [32]. A custom-built dual-tuned 13C-1H quadrature volume radio frequency (RF) coil (Ø=50mm) [33] operating at 32.1 MHz and 127.7 MHz, respectively, was used for both RF excitation and signal reception. Single-shot fast spin echo (FSE) images (pulse repetition time (TR)/ echo time (TE) = 1492/38.6 ms, slice thickness = 2 mm, in-plane resolution = 0.47 mm) with up to 45 slices were acquired for anatomical reference in axial, coronal, and sagittal planes. A dual-echo T2-weighted FSE sequence (TR/TE1/TE2 = 5000/11.3/56.7 ms, slice thickness = 1 mm, in-plane resolution = 0.25 mm, matrix size = 256x192, echo train length = 8) in axial plane was used to determine the location of the tumor. The homogeneity of the B0 field over the region of the brain that included the tumor was manually optimized with a point-resolved spectroscopy sequence by minimizing the line width of the unsuppressed water signal using the linear shim currents.

Single-shot spiral CSI with spectral undersampling (spectral bandwidth = 280 Hz) was used for dynamic metabolic imaging of hyperpolarized [1-13C]pyruvate and its metabolic products [1-13C]lactate, [1-13C]alanine, and 13C-bicarbonate. The 13C transmit RF power was calibrated over the targeted slice using a reference phantom placed on top of the animal's head (8-M solution of 13C urea for rat IDs: G1, G2, G3, H1, and 3.4-M solution of [1-13C]lactate for rat IDs: G4, G5, G6). The urea phantom was removed prior to the injection because its aliased resonance would partially overlap with the [1-13C]pyruvate peak. Data were acquired from a 5-mm slice with a nominal in-plane resolution of 2.7 mm × 2.7 mm (FOV = 43.5 mm, matrix size = 16 × 16, spectral points = 32). Following a delay of 9 s after start of the injection, 16 data sets were acquired at 3-s intervals. A variable flip angle scheme [34, 35], θi=tan1(1/16i), was employed where the flip angle was progressively increased from 14.5° to 90°. Further details of the pulse sequence are described in [31]. Up to three injections per animal with a time interval of 1.5-2 h between injections were performed to assess intra-subject variability and to increase SNR. After the last 13C injection, T1-weighted proton spin-echo images (TE/TR = 12/700 ms, 29 slices, slice thickness = 1 mm, NEX = 6, FOV = 87 mm, matrix size = 256 × 256, scan time = 9:02 min) were acquired both prior to and after the injection of 0.9 mL of a 1:2-mixture of Gadolinium and saline.

Following the imaging experiments, the rats were perfused transcardially with 4% paraformaldehyde (Sigma, MO, USA) in phosphate-buffered saline (PBS, pH 7.4) and their brains harvested for further histological examination. After overnight fixation at 4°C, brains were cryosectioned at a slice thickness of 40 μm. Hematoxylin and eosin (H&E) staining was performed to delineate the tumor morphology in the sections for validation of the MR results.

Data processing

All 13C data sets were first corrected for differences in polarization and dissolution-to-injection time, and then processed using MATLAB (Mathworks Inc., Natick, MA) as described in [31]. Briefly, the k-space data of each time-point were apodized by a 10-Hz Gaussian filter and zero-filled by a factor of 4 in the spectral dimension and by a factor 2 in both spatial dimensions. After a fast Fourier transform (FFT) was carried out in the frequency domain, the chemical shift artifact along the readout direction was removed followed by gridding onto a Cartesian grid and a 2D FFT in the spatial domains.

The time courses of pyruvate and lactate averaged over regions of interest (ROIs) in glioma, normal appearing brain, and vasculature were analyzed using a variant of the two-site exchange model that accounts for the applied RF scheme. In the model, the observed pyruvate signal (pyrobs) from each ROI at the nth time-point was first corrected for the respective excitation flip angle,

pyrRFcor,n=(pyrobs,n/sinθn)Cn,
[1]

where Cn is a correction factor that takes into account prior RF sampling losses. Then, lactate signal (lacn) produced within the nth TR was calculated from the RF-corrected pyruvate signal with an apparent conversion rate constant kPL ,

lacn=((pyrRFcor,n+pyrRFcor,n1)/2)TRkPL/(1TRkPL).
[2]

Backward reaction from lactate to pyruvate, kLP, was not explicitly included in the model. The accumulated lactate signal (lacacm, n) was estimated by adding up lacn, taking into account the apparent lactate decay rate T1 and RF sampling losses.

lacacm,n=lacn+lacn1eTR/T1cosθn1+lacn2e2TR/T1cosθn1cosθn2+
[3]

Finally, the values for kPL and T1 were estimated by minimizing the χ2-error between measured lactate (lacobs) and calculated lactate (lacacm). More details are presented in [36]. The lactate-to-pyruvate ratio was calculated as a measured signal in each ROI of time-averaged lactate image divided by that of time-averaged pyruvate image.

The ROIs were selected based on the contrast-enhanced T1-weighted proton images with the ROI for normal appearing brain placed in the contralateral hemisphere at approximately the same position as the tumor while trying to minimize contributions from the adjacent glioma and vasculature voxels. To explore how the choice of the normal-appearing brain ROI affects the estimation of kPL and metabolite ratios, in a single animal (rat ID: G2) the analysis was performed on two additional ROIs (#1 and #2 in Figure 3d) in the contralateral hemisphere.

Figure 3
Representative time-averaged images (rat ID: G2) of (a) total 13C-labeled metabolites, (b) pyruvate, and (c) lactate. (d) ROIs of glioma (green), normal brain (blue), and vasculature (red) selected based on contrast-enhanced T1-weighted proton image. ...

A paired student's t-test was used to evaluate the ability of the metrics, kPL and lactate-to-pyruvate ratio, to differentiate between glioma and normal appearing tissue in brain. The SNR of lactate in the tumor was calculated as the mean signal in the glioma ROI in the time-averaged image divided by the standard deviation of the background signal. Likewise, contrast-to-noise ratio (CNR) was calculated as the difference of averaged [1-13C]lactate signals from tumor ROI and normal appearing brain ROI divided by the standard deviation of the background signal.

The measurements were complemented by simulations to investigate how the shape of the injected pyruvate bolus affects the calculated metabolite ratios. Data were simulated for three different bolus shapes and a series of kPL ranging from 0.005 s-1 to 0.030 s-1 assuming T1 of 11 s, which is similar to the estimated for the measured data. The same RF sampling scheme as applied in the in vivo experiments was used in the simulations.

Results

Tumor growth was confirmed with contrast-enhanced T1-weighted proton images and histology as well as hyperpolarized 13C images eight to ten days post cell implantation. A T1-weighted image of a representative animal (rat ID: G2) and histology of the corresponding slice are shown in Figure 1. The hyper-intense tissue indicates the breakdown of the blood-brain barrier (BBB) due to tumor growth. Post-mortem histology revealed hemorrhagic regions, which are commonly demonstrable in tumor tissues. A time series of metabolic images for both pyruvate and lactate from the same animal are shown in Figure 2. The data from three injections were averaged and the color bars (arbitrary unit) on the right side of each metabolite's first image (t=9 s) indicate that the maximum pyruvate signal was about 6.7 times higher than the maximum lactate signal. The regions with high pyruvate included the internal carotid arteries and the basilar artery, whereas the highest lactate signal was located in the tumor. Time-averaged images with higher SNR of each metabolite are shown in Figure 3a-c. The total carbon image (Figure 3a), which is the sum of the metabolic images from pyruvate and its metabolic products, illustrates the perfusion of the substrate. In addition to increased lactate (Figure 3c), the time-averaged pyruvate (Figure 3b) and total carbon images evinced the increased perfusion of 13C-labeled metabolites in the tumor, which was due to BBB breakdown. The T1-weighted proton image in Figure 3d indicates the position of the ROIs used to calculate the metabolic time-curves in Figure 3e-f. Figure 3e shows that the highest pyruvate signal was from vasculature time-curve, and the pyruvate time-curve in glioma was higher than in normal appearing brain due to the BBB breakdown. The maximum in the pyruvate time courses for all three ROIs was reached at about 15 s after beginning of injection with a second peak approximately 6 s later that resulted from the flush of 0.5 mL saline. Maxima in the lactate curves appeared at around 30 s after the start of injection, but lasted longer than pyruvate.

Figure 1
(a) Contrast-enhanced T1-weighted proton image from an axial slice of a rat head (rat ID: G2) 10 days after C6 cell implantation. The hyper-intense region within brain connotes tumor; (b) Histological image (hematoxylin and eosin stained) of the corresponding ...
Figure 2
Representative time-resolved images (rat ID: G2) of (a) pyruvate and (b) lactate at 16 time-points with a temporal resolution of 3 s, starting 9 s after the beginning of [1-13C]pyruvate injection. 13C images are superimposed on the contrast-enhanced T ...

Intra-subject variability

Multiple injections were performed on some animals to assess the variability of the measurements and kPL estimates, and the k-space data were averaged to increase the image SNR. From a representative animal (rat ID: G2) shown in Table 2, estimated kPL's were 0.021±0.001 s-1 (mean ± standard deviation, n=3) for glioma, 0.011±0.001 s-1 for normal appearing brain, and 0.005±0.0003 s-1 for vasculature. As expected, through averaging in k-space, smoother time-courses were obtained, SNR was improved, and more reliable apparent conversion rates were calculated with reduced χ2 fitting errors. After averaging, SNR and CNR were increased by 47.0 % and 57.3 %, respectively, and χ2 fitting error of tumor, normal brain, and vasculature ROIs were decreased by 51.5 %, 89.8 %, and 80.2 % respectively, while maintaining their apparent conversion rate constants. Moreover, the high repeatability of the measurements was further demonstrated by relatively small variability in the consistent lactate-to-pyruvate ratio, which was 0.47±0.02 for glioma, 0.27±0.03 for normal appearing brain, and 0.12±0.01 for vasculature. When the analysis was performed with the data from the two additional ROIs in normal appearing brain as defined in Figure 3d, kPL's were 0.010 s-1 and 0.009 s-1, and lactate-to-pyruvate ratios were 0.22 and 0.21. For comparison, the corresponding values for the normal appearing brain ROI in the contralateral region of the glioma ROI were 0.011 s-1 and 0.27, respectively. The difference is most likely due to brain heterogeneity and pyruvate contributions from the vasculature as those ROIs were closer to vascular ROI.

Table 2
Intra-subject repeatability kPL's, the corresponding χ2 errors, and lactate-to-pyruvate ratios of three injections from a representative rat (rat ID: G2). Signal-to-noise ratio of glioma and contrast-to-noise ratio were used to evaluate the intra-subject ...

Metabolic kinetic comparisons of tumor, normal brain, and vasculature

Each animal's kPL and lactate-to-pyruvate ratio for the glioma and normal brain ROIs are summarized in Figure 4. The apparent conversion rate constant was 0.018±0.004 s-1 (n=6) for glioma, 0.009±0.003 s-1 for normal brain, and 0.005±0.001 s-1 for vasculature. The control animal (rat ID: H1) without tumor had a kPL of 0.009 s-1 for brain and 0.005 s-1 for vasculature, which were both consistent with the values for corresponding ROIs of the tumor-bearing animals. The lactate-to-pyruvate ratio was 0.36±0.07 for glioma, 0.24±0.07 for normal appearing brain, and 0.12±0.02 for vasculature. For the case of the control rat, lactate-to-pyruvate ratios were 0.22 for brain and 0.13 for vasculature. As indicated in Figure 4, glioma and normal appearing brain were better differentiated by kPL (P = 0.001) than by lactate-to-pyruvate ratios (P = 0.02).

Figure 4
(a) Apparent conversion rate constants (kPL) and (b) Lactate-to-pyruvate ratio of glioma and normal appearing brain from all tumor-bearing animals. Lactate-to-pyruvate ratio was calculated from time-averaged pyruvate and lactate images of each animal. ...

Discussion

The intra-subject multi-injection experiments with an interval of 1.5-2h between injections demonstrated that hyperpolarized [1-13C]pyruvate can be applied to detect metabolic differences between glioma and normal brain repeatedly with reliable lactate production estimates. In a dog study with multiple large-dose injections of [1-13C]pyruvate, which are comparable to the 3-mL doses used in the rats, there was no cumulative effect of pyruvate or lactate in blood samples drawn at intervals of 1.5 h [35, 37]. Although it is possible that lactate resides in brain for a longer duration than in blood, the small variations in kPL and lactate-to-pyruvate peak ratio for the intra-subject multi-injection experiments suggest that lactate levels went back to baseline in 1.5-2 h.

The difference in polarization due to difference in dissolution-to-injection time was corrected assuming a pyruvate T1 of 60 s measured at 3T. Recently, Mieville et al. showed that the relaxation is strongly field-dependent and can be accelerated at low field while the syringe with pyruvate solution is delivered from the DNP polarizer to the MR scanner [38]. Therefore, the calculated T1 loss in the fringe field might have been underestimated. However, most of the differences in dissolution-to-injection time probably occurred either by the polarizer or by the scanner, where field strength is high, while handling the syringe. Hence, the actual error in correcting the polarization for these differences should be rather small. But note that, aside from changes in SNR, both metabolite ratio and the estimated kPL are independent of polarization.

Despite variability in tumor size and animal body weight, kPL's of the three ROIs were relatively consistent and well differentiated from one another. The conversion rate constant in glioma was approximately twice as high as compared to normal appearing brain tissue and four times as high as compared to vasculature. The differences could be due to increased flux as well as a larger lactate pool in glioma tissues that results in increased isotopic exchange between pyruvate and lactate pools. The variations of the lactate-to-pyruvate ratios within glioma and normal appearing brain groups were larger, and they were less differentiated than those of kPL. Although all the tumor-bearing rats had larger a lactate-to-pyruvate ratio in glioma than in normal brain, the relative increase of the ratio showed high variability. Except for rat G5, which had the largest tumor, the lactate-to-pyruvate ratio in glioma was 2.1 % - 64 % higher than in normal appearing brain, whereas the conversion rate constant was 33 % - 100 % higher. Rat G5, the only animal whose tumor was larger than the imaging slice, had a 248 % higher lactate-to-pyruvate ratio and 260 % higher kPL in glioma than in normal appearing brain.

The data suggest that estimated kPL is a more robust metric for differentiating glioma from normal tissue than lactate-to-pyruvate ratio. As it is derived from metabolic time courses, it is less sensitive to imaging parameters such as injection time and shape of the pyruvate bolus. This is illustrated by the simulation results shown in Figure 5 as the calculated lactate-to-pyruvate ratio, for a given kPL, varies with the bolus shape. Note that the metabolic ratios for both the measured and simulated data were calculated from time-resolved data. Therefore, the lactate-to-pyruvate ratio calculated from single time-point data would be even more sensitive to such experimental parameters.

Figure 5
Effect of bolus shape (a) on Lac/Pyr (b) simulated for a series of kPL.

Due to the relatively coarse in-plane resolution with its corresponding point spread function and thick slice of the 13C images, the calculation of rate constant estimates was hampered by partial volume effects. As pyruvate perfusion was higher and lactate production was lower in the vasculature than in surrounding brain tissues and muscles, estimated kPL for vasculature was likely over-estimated, particularly considering the ROI for vasculature drawn around a basilar artery was larger than the actual vessel size. Similarly, the kPL from glioma could be under-estimated due to the surrounding normal appearing brain tissue with lower conversion rate. This was in particular a problem for rats G1, G3, and G6 where the tumor comprised only 69 %, 47 %, and 21 %, respectively, of the nominal voxel volume of 37 mm3. Therefore, the differences in kPL's of the three regions could be even larger. Imaging with higher spatial resolution could reduce the partial volume effects and better differentiate glioma, normal appearing brain, and vasculature.

Conclusion

In this paper, we proposed the kPL as a new metric to detect glioma brain tumor by comparing the conversion rates in glioma, normal appearing brain, and basilar vasculature in female Sprague-Dawley rats with C6 glioma cells implanted eight-to-ten days prior to hyperpolarized [1-13C]pyruvate metabolic imaging. The estimated apparent rate constant yielded a better differentiation between the tissue types than the lactate-to-pyruvate ratio, which has been the most common metric used to date. Specifically, elevated kPL in glioma provided better contrast consistently whereas the lactate-to-pyruvate ratio did not show clear difference between glioma and normal brain for some animals with small tumors. Longitudinal studies monitoring lactate-to-pyruvate ratios and apparent pyruvate-to-lactate conversion rate constants are needed to further investigate variations with tumor development and response to treatment.

Acknowledgments

Authors appreciate the following grant sponsors.

National Institutes of Health; Grant numbers: RR09784, AA05965, AA018681, AA13521-INIA, EB009070

The Lucas Foundation, Nadia's Gift Foundation

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