Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies

[EN] Quantitative multinuclear high-resolution magic angle spinning (HRMAS) was performed in order to determine the tissue pH values of and the absolute metabolite concentrations in 33 samples of human brain tumour tissue. Metabolite concentrations were quantified by 1D 1 H and 31P HRMAS using the electronic reference to in vivo concentrations (ERETIC) synthetic signal. 1 H–1 H homonuclear and 1 H–31P heteronuclear correlation experiments enabled the direct assessment of the 1 H–31P spin systems for signals that suffered from overlapping in the 1D 1 H spectra, and linked the information present in the 1D 1 H and 31P spectra. Afterwards, the main histological features were determined, and high heterogeneity in the tumour content, necrotic content and nonaffected tissue content was observed. The metabolite profiles obtained by HRMAS showed characteristics typical of tumour tissues: rather low levels of energetic molecules and increased concentrations of protective metabolites. Nevertheless, these characteristics were more strongly correlated with the total amount of living tissue than with the tumour cell contents of the samples alone, which could indicate that the sampling conditions make a significant contribution aside from the effect of tumour development in vivo. The use of methylene diphosphonic acid as a chemical shift and concentration reference for the 31P HRMAS spectra of tissues presented important drawbacks due to its interaction with the tissue. Moreover, the pH data obtained from 31P HRMAS enabled us to establish a correlation between the pH and the distance between the N(CH3)3 signals of phosphocholine and choline in 1 H spectra of the tissue in these tumour samples.The authors acknowledge the SCSIE-University of Valencia Microscopy Service for the histological preparations. They also acknowledge Martial Piotto (Bruker BioSpin, France) for providing the ERETIC synthetic signal. Furthermore, they acknowledge financial support from the Spanish Government project SAF2007-6547, the Generalitat Valenciana project GVACOMP2009-303, and the E.U.'s VI Framework Programme via the project "Web accessible MR decision support system for brain tumor diagnosis and prognosis, incorporating in vivo and ex vivo genomic and metabolomic data" (FP6-2002-LSH 503094). CIBER-BBN is an initiative funded by the VI National R&D&D&i Plan 2008-2011, Iniciativa Ingenio 2010, Consolider Program, CIBER Actions, and financed by the Instituto de Salud Carlos III with assistance from the European Regional Development Fund.Esteve Moya, V.; Celda, B.; Martínez Bisbal, MC. (2012). Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies. Analytical and Bioanalytical Chemistry. 403:2611-2625. https://doi.org/10.1007/s00216-012-6001-zS26112625403Cheng LL, Chang IW, Louis DN, Gonzalez RG (1998) Cancer Res 58:1825–1832Opstad KS, Bell BA, Griffiths JR, Howe FA (2008) Magn Reson Med 60:1237–1242Sjobakk TE, Johansen R, Bathen TF, Sonnewald U, Juul R, Torp SH, Lundgren S, Gribbestad IS (2008) NMR Biomed 21:175–185Martinez-Bisbal MC, Marti-Bonmati L, Piquer J, Revert A, Ferrer P, Llacer JL, Piotto M, Assemat O, Celda B (2004) NMR Biomed 17:191–205Erb G, Elbayed K, Piotto M, Raya J, Neuville A, Mohr M, Maitrot D, Kehrli P, Namer IJ (2008) Magn Reson Med 59:959–965Wilson M, Davies NP, Brundler MA, McConville C, Grundy RG, Peet AC (2009) Mol Cancer 8:6Martinez-Bisbal MC, Monleon D, Assemat O, Piotto M, Piquer J, Llacer JL, Celda B (2009) NMR Biomed 22:199–206Martínez-Granados B, Monleón D, Martínez-Bisbal MC, Rodrigo JM, del Olmo J, Lluch P, Ferrández A, Martí-Bonmatí L, Celda B (2006) NMR Biomed 19:90–100Hubesch B, Sappey-Marinier D, Roth K, Meyerhoff DJ, Matson GB, Weiner MW (1990) Radiology 174:401–409Albers MJ, Krieger MD, Gonzalez-Gomez I, Gilles FH, McComb JG, Nelson MD Jr, Bluml S (2005) Magn Reson Med 53:22–29Wijnen JP, Scheenen TW, Klomp DW, Heerschap A (2010) NMR Biomed 23:968–976Podo F (1999) NMR Biomed 12:413–439Griffiths JR, Cady E, Edwards RH, McCready VR, Wilkie DR, Wiltshaw E (1983) Lancet 1:1435–1436Robitaille PL, Robitaille PA, Gordon Brown G, Brown GG (1991) J Magn Reson 92:73–84, 1969Griffiths JR (1991) Br J Cancer 64:425–427Payne GS, Troy H, Vaidya SJ, Griffiths JR, Leach MO, Chung YL (2006) NMR Biomed 19:593–598De Silva SS, Payne GS, Thomas V, Carter PG, Ind TE, deSouza NM (2009) NMR Biomed 22:191–198Wang Y, Cloarec O, Tang H, Lindon JC, Holmes E, Kochhar S, Nicholson JK (2008) Anal Chem 80:1058–1066Lehnhardt FG, Rohn G, Ernestus RI, Grune M, Hoehn M (2001) NMR Biomed 14:307–317Srivastava NK, Pradhan S, Gowda GA, Kumar R (2010) NMR Biomed 23:113–122Akoka S, Barantin L, Trierweiler M (1999) Anal Chem 71:2554–2557Albers MJ, Butler TN, Rahwa I, Bao N, Keshari KR, Swanson MG, Kurhanewicz J (2009) Magn Reson Med 61:525–532Ben Sellem D, Elbayed K, Neuville A, Moussallieh FM, Lang-Averous G, Piotto M, Bellocq JP, Namer IJ (2011) J Oncol 2011:174019Bourne R, Dzendrowskyj T, Mountford C (2003) NMR Biomed 16:96–101Martinez-Bisbal MC, Esteve V, Martinez-Granados B, Celda B (2011) J Biomed Biotechnol 2011:763684, Epub 2010 Sep 5Celda B, Montelione GT (1993) J Magn Reson B 101:189–193Esteve V, Celda B (2008) Magn Reson Mater Phys MAGMA 21:484–484Collins TJ (2007) Biotechniques 43:25–30Govindaraju V, Young K, Maudsley AA (2000) NMR Biomed 13:129–153Fan TW-M (1996) Prog Nucl Magn Reson Spectrosc 28:161–219Ulrich EL, Akutsu H, Doreleijers JF, Harano Y, Ioannidis YE, Lin J, Livny M, Mading S, Maziuk D, Miller Z, Nakatani E, Schulte CF, Tolmie DE, Kent Wenger R, Yao H, Markley JL (2008) Nucleic Acids Res 36:D402–D408Kriat M, Vion-Dury J, Confort-Gouny S, Favre R, Viout P, Sciaky M, Sari H, Cozzone PJ (1993) J Lipid Res 34:1009–1019Subramanian A, Shankar Joshi B, Roy AD, Roy R, Gupta V, Dang RS (2008) NMR Biomed 21:272–288Daykin CA, Corcoran O, Hansen SH, Bjornsdottir I, Cornett C, Connor SC, Lindon JC, Nicholson JK (2001) Anal Chem 73:1084–1090Griffin JL, Lehtimaki KK, Valonen PK, Grohn OH, Kettunen MI, Yla-Herttuala S, Pitkanen A, Nicholson JK, Kauppinen RA (2003) Cancer Res 63:3195–3201Petroff OAC, Prichard JW (1995) In: Kraicer J, Dixon SJ (eds) Methods in neurosciences. Academic, San DiegoBarton S, Howe F, Tomlins A, Cudlip S, Nicholson J, Anthony Bell B, Griffiths J (1999) Magn Reson Mater Phys Biol Med 8:121–128Sitter B, Sonnewald U, Spraul M, Fjosne HE, Gribbestad IS (2002) NMR Biomed 15:327–337Coen M, Hong YS, Cloarec O, Rhode CM, Reily MD, Robertson DG, Holmes E, Lindon JC, Nicholson JK (2007) Anal Chem 79:8956–8966Russell D, Rubinstein LJ (1998) Russel and Rubinstein's pathology of tumors of the nervous system. Arnold, LondonTynkkynen T, Tiainen M, Soininen P, Laatikainen R (2009) Anal Chim Acta 648:105–112Kjaergaard M, Brander S, Poulsen F (2011) J Biomol NMR 49:139–149Robert O, Sabatier J, Desoubzdanne D, Lalande J, Balayssac S, Gilard V, Martino R, Malet-Martino M (2011) Anal Bioanal Chem 399:987–999Chadzynski GL, Bender B, Groeger A, Erb M, Klose U (2011) J Magn Reson 212:55–63Weljie AM, Jirik FR (2011) Int J Biochem Cell Biol 43:981–989Barba I, Cabanas ME, Arus C (1999) Cancer Res 59:1861–1868Liimatainen T, Hakumaki JM, Kauppinen RA, Ala-Korpela M (2009) NMR Biomed 22:272–279Opstad KS, Bell BA, Griffiths JR, Howe FA (2008) NMR Biomed 21:677–685Schmitz JE, Kettunen MI, Hu D, Brindle KM (2005) Magn Reson Med 54:43–50Glunde K, Artemov D, Penet MF, Jacobs MA, Bhujwalla ZM (2010) Chem Rev 110:3043–3059Hertz L (2008) Neuropharmacology 55:289–309Takahashi T, Otsuguro K, Ohta T, Ito S (2010) Br J Pharmacol 161:1806–181

Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy

Contains fulltext : 75361.pdf (publisher's version ) (Open Access)14 p

Quantitative In Vivo Magnetic Resonance Spectroscopy Using Synthetic Signal Injection

Accurate conversion of magnetic resonance spectra to quantitative units of concentration generally requires compensation for differences in coil loading conditions, the gains of the various receiver amplifiers, and rescaling that occurs during post-processing manipulations. This can be efficiently achieved by injecting a precalibrated, artificial reference signal, or pseudo-signal into the data. We have previously demonstrated, using in vitro measurements, that robust pseudo-signal injection can be accomplished using a second coil, called the injector coil, properly designed and oriented so that it couples inductively with the receive coil used to acquire the data. In this work, we acquired nonlocalized phosphorous magnetic resonance spectroscopy measurements from resting human tibialis anterior muscles and used pseudo-signal injection to calculate the Pi, PCr, and ATP concentrations. We compared these results to parallel estimates of concentrations obtained using the more established phantom replacement method. Our results demonstrate that pseudo-signal injection using inductive coupling provides a robust calibration factor that is immune to coil loading conditions and suitable for use in human measurements. Having benefits in terms of ease of use and quantitative accuracy, this method is feasible for clinical use. The protocol we describe could be readily translated for use in patients with mitochondrial disease, where sensitive assessment of metabolite content could improve diagnosis and treatment

Metabolite profiling in retinoblastoma identifies novel clinicopathological subgroups

BACKGROUND: Tumour classification, based on histopathology or molecular pathology, is of value to predict tumour behaviour and to select appropriate treatment. In retinoblastoma, pathology information is not available at diagnosis and only exists for enucleated tumours. Alternative methods of tumour classification, using noninvasive techniques such as magnetic resonance spectroscopy, are urgently required to guide treatment decisions at the time of diagnosis. METHODS: High-resolution magic-angle spinning magnetic resonance spectroscopy (HR-MAS MRS) was undertaken on enucleated retinoblastomas. Principal component analysis and cluster analysis of the HR-MAS MRS data was used to identify tumour subgroups. Individual metabolite concentrations were determined and were correlated with histopathological risk factors for each group. RESULTS: Multivariate analysis identified three metabolic subgroups of retinoblastoma, with the most discriminatory metabolites being taurine, hypotaurine, total-choline and creatine. Metabolite concentrations correlated with specific histopathological features: taurine was correlated with differentiation, total-choline and phosphocholine with retrolaminar optic nerve invasion, and total lipids with necrosis. CONCLUSIONS: We have demonstrated that a metabolite-based classification of retinoblastoma can be obtained using ex vivo magnetic resonance spectroscopy, and that the subgroups identified correlate with histopathological features. This result justifies future studies to validate the clinical relevance of these subgroups and highlights the potential of in vivo MRS as a noninvasive diagnostic tool for retinoblastoma patient stratification

Magnetic Resonance Spectroscopy (MRS)-Based Methods for Examining Cancer Metabolism in Response to Oncogenic Kinase Drug Treatment.

Magnetic resonance spectroscopy (MRS) is an analytical technique that has been extensively used to examine reprogrammed metabolism and treatment response in cancer cells and solid tumors both in vivo and ex vivo. High-resolution MRS (HR-MRS) is one of the best methods for metabolic profiling, as it is highly quantitative, robust, and reproducible. The protocols for dual-phase extraction of cancer cells and tumors and sample preparations for high-resolution 1H and 31P HR-MRS analysis are described here. Descriptions of spectra acquisition and analysis are also included in this chapter

Magnetic resonance spectroscopy and imaging on fresh human brain tumor biopsies at microscopic resolution

[EN] The metabolic compn. and concn. knowledge provided by magnetic resonance spectroscopy (MRS) liq. and high-resoln. magic angle spinning spectroscopy (HR-MAS) has a relevant impact in clin. practice during magnetic resonance imaging (MRI) monitoring of human tumors. In addn., the combination of morphol. and chem. information by MRI and MRS has been particularly useful for diagnosis and prognosis of tumor evolution. MRI spatial resoln. reachable in human beings is limited for safety reasons and the demanding necessary conditions are only applicable on exptl. model animals. Nevertheless, MRS and MRI can be performed on human biopsies at high spatial resoln., enough to allow a direct correlation between the chem. information and the histol. features obsd. in such biopsies. Although HR-MAS is nowadays a well-established technique for spectroscopic anal. of tumor biopsies, with this approach just a mean metabolic profile of the whole sample can be obtained and thus the high histol. heterogeneity of some important tumors is mostly neglected. The value of metabolic HR-MAS data strongly depends on a wide statistical anal. and usually the microanatomical rationale for the correlation between histol. and spectroscopy is lost. We present here a different approach for the combined use of MRI and MRS on fresh human brain tumor biopsies with native contrast. This approach has been designed to achieve high spatial (18 × 18 × 50 m) and spectral (0.031 L) resoln. in order to obtain as much spatially detailed morphol. and metabolical information as possible without any previous treatment that can alter the sample. The preservation of native tissue conditions can provide information that can be translated to in vivo studies and addnl. opens the possibility of performing other techniques to obtain complementary information from the same sample.The authors acknowledge the SCSIE-University of Valencia Microscopy Service for the histological preparations. They also acknowledge financial support from the Spanish Government project SAF2007-6547, the Generalitat Valenciana project GVACOMP2009-303, and the E.U.s VI Framework Program via the project "Web accessible MR decision support system for brain tumor diagnosis and prognosis, incorporating in vivo and ex vivo genomic and metabolomic data" (FP6-2002-LSH 503094).Martínez-Bisbal, M.; Martínez-Granados, B.; Rovira, V.; Celda, B.; Esteve, V. (2015). Magnetic resonance spectroscopy and imaging on fresh human brain tumor biopsies at microscopic resolution. Analytical and Bioanalytical Chemistry. 407(22):6771-6780. https://doi.org/10.1007/s00216-015-8847-36771678040722Stadlbauer A, Gruber S, Nimsky C, Fahlbusch R, Hammen T, Buslei R, Tomandl B, Moser E, Ganslandt O (2006) Preoperative grading of gliomas by using metabolite quantification with high-spatial-resolution proton MR spectroscopic imaging. Radiology 238:958Howe FA, Barton SJ, Cudlip SA, Stubbs M, Saunders DE, Murphy M, Wilkins P, Opstad KS, Doyle VL, McLean MA, Bell BA, Griffiths JR (2003) Metabolic profiles of human brain tumors using quantitative in vivo 1H magnetic resonance spectroscopy. Magn Reson Med 49:223Castillo M, Kwock L (1999) Clinical applications of proton magnetic resonance spectroscopy in the evaluation of common intracranial tumors. Top Magn Reson Imaging 10:104Howe FA, Opstad KS (2003) 1H MR spectroscopy of brain tumours and masses. NMR Biomed 16:123Martinez-Bisbal MC, Celda B (2009) Proton magnetic resonance spectroscopy imaging in the study of human brain cancer. Q J Nucl Med Mol Imaging 53:618Sibtain NA, Howe FA, Saunders DE (2007) The clinical value of proton magnetic resonance spectroscopy in adult brain tumours. Clin Radiol 62:109Tong Z, Yamaki T, Harada K, Houkin K (2004) In vivo quantification of the metabolites in normal brain and brain tumors by proton MR spectroscopy using water as an internal standard. Magn Reson Imaging 22:1017Hourani R, Brant LJ, Rizk T, Weingart JD, Barker PB, Horska A (2008) Can proton MR spectroscopic and perfusion imaging differentiate between neoplastic and nonneoplastic brain lesions in adults? AJNR Am J Neuroradiol 29:366Hourani R, Horska A, Albayram S, Brant LJ, Melhem E, Cohen KJ, Burger PC, Weingart JD, Carson B, Wharam MD, Barker PB (2006) Proton magnetic resonance spectroscopic imaging to differentiate between nonneoplastic lesions and brain tumors in children. J Magn Reson Imaging 23:99Lai PH, Weng HH, Chen CY, Hsu SS, Ding S, Ko CW, Fu JH, Liang HL, Chen KH (2008) In vivo differentiation of aerobic brain abscesses and necrotic glioblastomas multiforme using proton MR spectroscopic imaging. AJNR Am J Neuroradiol 29:1511Vuori K, Kankaanranta L, Hakkinen AM, Gaily E, Valanne L, Granstrom ML, Joensuu H, Blomstedt G, Paetau A, Lundbom N (2004) Low-grade gliomas and focal cortical developmental malformations: differentiation with proton MR spectroscopy. Radiology 230:703Di Costanzo A, Scarabino T, Trojsi F, Popolizio T, Catapano D, Giannatempo GM, Bonavita S, Portaluri M, Tosetti M, d’Angelo VA, Salvolini U, Tedeschi G (2008) Proton MR spectroscopy of cerebral gliomas at 3 T: spatial heterogeneity, and tumour grade and extent. Eur Radiol 18:1727Law M, Yang S, Wang H, Babb JS, Johnson G, Cha S, Knopp EA, Zagzag D (2003) Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging. AJNR Am J Neuroradiol 24:1989Catalaa I, Henry R, Dillon WP, Graves EE, McKnight TR, Lu Y, Vigneron DB, Nelson SJ (2006) Perfusion, diffusion and spectroscopy values in newly diagnosed cerebral gliomas. NMR Biomed 19:463Devos A, Lukas L, Suykens JA, Vanhamme L, Tate AR, Howe FA, Majos C, Moreno-Torres A, van der Graaf M, Arus C, Van Huffel S (2004) Classification of brain tumours using short echo time 1H MR spectra. J Magn Reson 170:164Burtscher IM, Skagerberg G, Geijer B, Englund E, Stahlberg F, Holtas S (2000) Proton MR spectroscopy and preoperative diagnostic accuracy: an evaluation of intracranial mass lesions characterized by stereotactic biopsy findings. AJNR Am J Neuroradiol 21:84Ishimaru H, Morikawa M, Iwanaga S, Kaminogo M, Ochi M, Hayashi K (2001) Differentiation between high-grade glioma and metastatic brain tumor using singlevoxel proton MR spectroscopy. Eur Radiol 11:1784Sjobakk TE, Johansen R, Bathen TF, Sonnewald U, Kvistad KA, Lundgren S, Gribbestad IS (2007) Metabolic profiling of human brain metastases using in vivo proton MR spectroscopy at 3T. BMC Cancer 7:141Stadlbauer A, Nimsky C, Buslei R, Pinker K, Gruber S, Hammen T, Buchfelder M, Ganslandt O (2007) Proton magnetic resonance spectroscopic imaging in the border zone of gliomas: correlation of metabolic and histological changes at low tumor infiltration—initial results. Investig Radiol 42:218Law M, Cha S, Knopp EA, Johnson G, Arnett J, Litt AW (2002) High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MR imaging. Radiology 222:715Schlemmer HP, Bachert P, Herfarth KK, Zuna I, Debus J, van Kaick G (2001) Proton MR spectroscopic evaluation of suspicious brain lesions after stereotactic radiotherapy. AJNR Am J Neuroradiol 22:1316Weybright P, Sundgren PC, Maly P, Hassan DG, Nan B, Rohrer S, Junck L (2005) Differentiation between brain tumor recurrence and radiation injury using MR spectroscopy. AJR Am J Roentgenol 185:1471Stadlbauer A, Moser E, Gruber S, Buslei R, Nimsky C, Fahlbusch R, Ganslandt O (2004) Improved delineation of brain tumors: an automated method for segmentation based on pathologic changes of 1H-MRSI metabolites in gliomas. Neuroimage 23:454Dowling C, Bollen AW, Noworolski SM, McDermott MW, Barbaro NM, Day MR, Henry RG, Chang SM, Dillon WP, Nelson SJ, Vigneron DB (2001) Preoperative proton MR spectroscopic imaging of brain tumors: correlation with histopathologic analysis of resection specimens. AJNR Am J Neuroradiol 22:604Benveniste H, Blackband S (2002) MR microscopy and high resolution small animal MRI: applications in neuroscience research. Prog Neurobiol 67:393Benveniste H, Blackband SJ (2006) Translational neuroscience and magneticresonancemicroscopy. Lancet Neurol 5:536Thelwall PE, Shepherd TM, Stanisz GJ, Blackband SJ (2006) Effects of temperature and aldehyde fixation on tissue water diffusion properties, studied in an erythrocyte ghost tissue model. Magn Reson Med 56:282Fatterpekar GM, Naidich TP, Delman BN, Aguinaldo JG, Gultekin SH, Sherwood CC, Hof PR, Drayer BP, Fayad ZA (2002) Cytoarchitecture of the human cerebral cortex: MR microscopy of excised specimens at 9.4 Tesla. AJNR Am J Neuroradiol 23:1313Yushkevich PA, Avants BB, Pluta J, Das S, Minkoff D, Mechanic-Hamilton D, Glynn S, Pickup S, Liu W, Gee JC, Grossman M, Detre JA (2009) A high-resolution computational atlas of the human hippocampus from postmortem magnetic resonance imaging at 9.4 T. Neuroimage 44:385Blackwell ML, Farrar CT, Fischl B, Rosen BR (2009) Target-specific contrast agents for magnetic resonance microscopy. Neuroimage 46:382Shenkar R, Venkatasubramanian PN, Zhao JC, Batjer HH, Wyrwicz AM, Awad IA (2008) Advanced magnetic resonance imaging of cerebral cavernous malformations: part I. High-field imaging of excised human lesions. Neurosurgery 63:782Gonzalez-Segura A, Morales JM, Gonzalez-Darder JM, Cardona-Marsal R, Lopez-Gines C, Cerda-Nicolas M, Monleon D (2011) Magnetic resonance microscopy at 14 Tesla and correlative histopathology of human brain tumor tissue. PLoS One 6, e27442Shepherd TM, Flint JJ, Thelwall PE, Stanisz GJ, Mareci TH, Yachnis AT, Blackband SJ (2009) Postmortem interval alters the water relaxation and diffusion properties of rat nervous tissue—implications for MRI studies of human autopsy samples. Neuroimage 44:820Brazilian Aging Brain Study Group, Grinberg LT, Amaro E Jr, Teipel S, dos Santos DD, Pasqualucci CA, Leite RE, Camargo CR, Goncalves JA, Sanches AG, Santana M, Ferretti RE, Jacob-Filho W, Nitrini R, Heinsen H (2008) Assessment of factors that confound MRI and neuropathological correlation of human postmortem brain tissue. Cell Tissue Bank 9:195Tkac I, Starcuk Z, Choi IY, Gruetter R (1999) In vivo 1H NMR spectroscopy of rat brain at 1 ms echo time. Magn Reson Med 41:649Pfeuffer J, Tkac I, Provencher SW, Gruetter R (1999) Toward an in vivo neurochemical profile: quantification of 18 metabolites in short-echo-time (1) H NMR spectra of the rat brain. J Magn Reson 141:104Pfeuffer J, Tkac I, Choi IY, Merkle H, Ugurbil K, Garwood M, Gruetter R (1999) Localized in vivo 1H NMR detection of neurotransmitter labeling in rat brain during infusion of [1-13C] D-glucose. Magn Reson Med 41:1077Gruetter R (1993) Automatic, localized in vivo adjustment of all first- and secondorder shim coils. Magn Reson Med 29:804Zoula S, Herigault G, Ziegler A, Farion R, Decorps M, Remy C (2003) Correlation between the occurrence of 1H-MRS lipid signal, necrosis and lipid droplets during C6 rat glioma development. NMR Biomed 16:199Russell D, Rubinstein LJ (1998) Russel and Rubinstein’s Pathology of Tumors of the Nervous System. Arnold, LondonLevin VA, Leibel SA, Gutin PH (1997) In: De Vita VTj, Hellman S, Rosenberg SA (eds) Cancer principles and practice of oncology, 5th edn. Lippincott-Raven, PhiladelphiaCha S (2006) Update on brain tumor imaging: from anatomy to physiology. AJNR Am J Neuroradiol 27:475Steinberg JD, Velan SS (2012) Measuring glucose concentrations in the rat brain using echo-time-averaged point resolved spectroscopy at 7 Tesla. Magnetic Resonance in Medicine:n/aSimoes RV, Garcia-Martin ML, Cerdan S, Arus C (2008) Perturbation of mouse glioma MRS pattern by induced acute hyperglycemia. NMR Biomed 21:251Thorsen F, Jirak D, Wang J, Sykova E, Bjerkvig R, Enger PO, van der Kogel A, Hajek M (2008) Two distinct tumor phenotypes isolated from glioblastomas show different MRS characteristics. NMR Biomed 21:830Liimatainen T, Hakumaki J, Tkac I, Grohn O (2006) Ultra-short echo time spectroscopic imaging in rats: implications for monitoring lipids in glioma gene therapy. NMR Biomed 19:554Liimatainen TJ, Erkkila AT, Valonen P, Vidgren H, Lakso M, Wong G, Grohn OH, Yla-Herttuala S, Hakumaki JM (2008) 1H MR spectroscopic imaging of phospholipase-mediated membrane lipid release in apoptotic rat glioma in vivo. Magn Reson Med 59:1232Liimatainen T, Hakumaki JM, Kauppinen RA, Ala-Korpela M (2009) Monitoring of gliomas in vivo by diffusion MRI and (1) H MRS during gene therapy-induced apoptosis: interrelationships between water diffusion and mobile lipids. NMR Biomed 22:272Griffin JL, Lehtimaki KK, Valonen PK, Grohn OH, Kettunen MI, Yla-Herttuala S, Pitkanen A, Nicholson JK, Kauppinen RA (2003) Assignment of 1H nuclear magnetic resonance visible polyunsaturated fatty acids in BT4C gliomas undergoing ganciclovir-thymidine kinase gene therapy-induced programmed cell death. Cancer Res 63:3195Provent P, Benito M, Hiba B, Farion R, Lopez-Larrubia P, Ballesteros P, Remy C, Segebarth C, Cerdan S, Coles JA, Garcia-Martin ML (2007) Serial in vivo spectroscopic nuclear magnetic resonance imaging of lactate and extracellular pH in rat gliomas shows redistribution of protons away from sites of glycolysis. Cancer Res 67:7638Doblas S, He T, Saunders D, Hoyle J, Smith N, Pye Q, Lerner M, Jensen RL, Towner RA (2012) In vivo characterization of several rodent glioma models by 1H MRS. NMR Biomed 25:685Ziegler A, von Kienlin M, Decorps M, Remy C (2001) High glycolytic activity in rat glioma demonstrated in vivo by correlation peak 1H magnetic resonance imaging. Cancer Res 61:5595Garcia-Martin ML, Herigault G, Remy C, Farion R, Ballesteros P, Coles JA, Cerdan S, Ziegler A (2001) Mapping extracellular pH in rat brain gliomas in vivo by 1H magnetic resonance spectroscopic imaging: comparison with maps of metabolites. Cancer Res 61:6524Hakumaki JM, Poptani H, Sandmair AM, Yla-Herttuala S, Kauppinen RA (1999) 1H MRS detects polyunsaturated fatty acid accumulation during gene therapy of glioma: implications for the in vivo detection of apoptosis. Nat Med 5:1323Martinez-Bisbal MC, Esteve V, Martinez-Granados B, Celda B (2011) Magnetic resonance microscopy contribution to interpret high-resolution magic angle spinning metabolomic data of human tumor tissue. J Biomed Biotechnol 2011:763684Esteve V, Celda B, Martinez-Bisbal MC (2012) Use of (1) H and (31)P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies. Anal Bioanal ChemMartinez-Bisbal MC, Marti-Bonmati L, Piquer J, Revert A, Ferrer P, Llacer JL, Piotto M, Assemat O, Celda B (2004) 1H and 13C HR-MAS spectroscopy of intact biopsy samples ex vivo and in vivo 1H MRS study of human high grade gliomas. NMR Biomed 17:191Cheng LL, Ma MJ, Becerra L, Ptak T, Tracey I, Lackner A, Gonzalez RG (1997) Quantitative neuropathology by high resolution magic angle spinning proton magnetic resonance spectroscopy. Proc Natl Acad Sci U S A 94:6408Cheng LL, Anthony DC, Comite AR, Black PM, Tzika AA, Gonzalez RG (2000) Quantification of microheterogeneity in glioblastoma multiforme with ex vivo highresolution magic-angle spinning (HRMAS) proton magnetic resonance spectroscopy. Neuro-Oncology 2:87Sitter B, Bathen TF, Tessem M, Gribbestad IS (2009) High-resolution magic angle spinning (HR MAS) MR spectroscopy in metabolic characterization of human cancer. Prog Nucl Magn Reson Spectrosc 54:23