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Monitoring treatment response in a murine lymphoma with Deuterium Metabolic Imaging and Spectroscopy1Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom, 2Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom
Synopsis
We investigated whether Deuterium Metabolic Imaging (DMI) with 2H-labeled glucose can be used to monitor treatment response in a pre-clinical murine lymphoma model (EL4). Localized 2H spectra were acquired from tumors, with a time resolution of ~1min, following a bolus injection of labeled glucose. These showed inhibition of lactate labeling following treatment of the tumors with etoposide. 2D chemical shift images (2D CSI) were acquired from the tumors, but imaging treatment response may need faster image acquisition. Studies with a respiratory chain inhibitor in vitro suggested that labeling of water in EL4 tumor cells may be due, at least in part, to TCA cycle activity.
Introduction
Deuterium Metabolic Imaging (DMI), which has recently been introduced as a tool for mapping tissue metabolism in vivo1,2, has great potential for quantitative imaging of tumor metabolism. We are currently working on a DMI-based method to assess tumor treatment response. In initial experiments we have used serial acquisition of localized 2H spectra, following a bolus injection of d-[6,6’-2H2]glucose, to monitor tumor glycolysis before and after treatment. These rapidly acquired spectra gave detailed kinetic data for glucose, lactate and water labelling, which was then used to optimize timing of 2D chemical shift image acquisitions.Methods
MRSI in vivo: EL4 tumor-bearing mice were imaged under 2-3% isoflurane anesthesia in a 9.4 T MRI scanner (Agilent, Palo Alto, California, USA). Proton reference images were acquired with a volume coil and 2H spectra were acquired using a home-built 18 mm diameter surface coil. Sequential 2H spectra (256 transients, TR=260 ms) were acquired from a 10 mm slice through the tumor (Fig. 1A) following injection of 2 g/kg d-[6,6’-2H2]glucose. The 2H pulse power was adjusted, prior to glucose injection, to give a maximum natural abundance HOD signal. The injection was started following acquisition of the first spectrum. The mice (n=3) were then, after they had recovered from the anaesthesia, treated with an intraperitoneal injection of 67 mg etoposide per kg body weight. A second series of 2H spectra was acquired 48 h later. All procedures were carried out under the authority of project and personal licenses issued by the UK Home Office.
The 2D CSI sequence used Hamming window weighting for the number of averages per kspace point (Fig. 4). The FOV was 36x36x10 mm3 with a matrix size of 12x12. The TR was 260 ms and a total of 12388 excitations gave an acquisition time of 54 min. Peaks were fitted individually for each voxel using an AMARES implementation in MATLAB3. The 2H images, containing the fitted peak amplitudes, were zero-filled to 256x256 data points to match the resolution of the 1H Fast Spin Echo reference images (number of averages = 16, TR= 1s, and echo train length = 8, echo time = 20ms).
NMR spectroscopy in vitro: To establish what part of the increase in the HOD peak after the injection of [6,6’-2H2]glucose was due to loss of label in glycolysis and what part was due to TCA cycle activity we modulated TCA cycle activity using the respiratory chain inhibitor rotenone. d-[6,6’-2H2]glucose (2 mg/ml) was added to two EL4 cell cultures at a density of ~0.2 million cells per ml. Rotenone (10 nM) was added to one of the cultures and at several timepoints after glucose addition, 500 μl samples were taken, centrifuged to remove cells and 2H NMR spectra acquired (2000 Hz spectral width, 2048 data points, TR=2 s, 1024 averages).
Results
A typical time course for labeling of EL4 tumor metabolites following intravenous injection of 2 g/kg d-[6,6’-2H2]glucose is shown in Fig 1. First the glucose and then the lactate signals increased and then both of the labeled metabolites were flushed out of the tumor. The HOD peak increased throughout the experiment, which may represent wash in of labeled water from other tissues. Looking at the sum spectrum for each acquisition (256x30=7680 averages), there were significant decreases in the lactate/HOD and lactate/glucose ratios 48 h after etoposide treatment and an increase in the HOD /glucose ratio. Treatment of EL4 tumor cells in vitro with the Complex I inhibitor, rotenone, inhibited water labeling (Fig. 3) suggesting that this arises from TCA cycle activity. 2D chemical shift (CS) images show labeled glucose, lactate and water metabolite maps in the sensitive region of the surface coil, which covers the tumor (Fig. 5).Discussion
Serial spectra from the tumors showed the expected decrease in lactate labeling following etoposide treatment, which we have observed previously with hyperpolarized [1-13C]pyruvate4 and hyperpolarized [U-2H, U-13C]glucose5. Initial experiments with the respiratory chain inhibitor rotenone suggest that water labeling from d-[6,6’-2H2]glucose arises, at least in part, from TCA cycle activity. Why water labeling in the tumor would increase post etoposide treatment is unclear, although this may represent wash in from other tissues. The 2D chemical shift images demonstrate that maps of tumor metabolite labeling can be produced, although the 54 min acquisition time will need to be substantially shortened if these are to capture the kinetics of labeling.Conclusion
Localized 2H spectroscopy following administration of d-[6,6’-2H2]glucose can be used to detect early evidence of treatment response in a murine lymphoma model. 2H images can be acquired from these tumors but detection of treatment response using DMI may require some acceleration of image acquisition.Acknowledgements
FK received founding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 642773 (EUROPOL).References
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2. Lu M, Zhu X-H, Zhang Y, Mateescu G, Chen W. Quantitative assessment of brain glucose metabolic rates using in vivo deuterium magnetic resonance spectroscopy. J Cereb Blood Flow Metab. 2017;37(11):3518-3530.
3. Purvis LAB, Clarke WT, Biasiolli L, Valkovič L, Robson MD, Rodgers CT. OXSA: An open-source magnetic resonance spectroscopy analysis toolbox in MATLAB. PLoS One. 2017;12(9):1-10.
4. Day SE, Kettunen MI, Gallagher F a, et al. Detecting tumor response to treatment using hyperpolarized 13C magnetic resonance imaging and spectroscopy. Nat Med. 2007;13(11):1382-1387.
5. Rodrigues TB, Serrao EM, Kennedy BWC, Hu D-E, Kettunen MI, Brindle KM. Magnetic resonance imaging of tumor glycolysis using hyperpolarized 13C-labeled glucose. Nat Med. 2014;20(1):93-97.
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