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Pediatric Radiology

, Volume 46, Issue 7, pp 952–962 | Cite as

Proton MRS imaging in pediatric brain tumors

  • Maria Zarifi
  • A. Aria TzikaEmail author
Minisymposium: Pediatric MR Spectroscopy

Abstract

Magnetic resonance (MR) techniques offer a noninvasive, non-irradiating yet sensitive approach to diagnosing and monitoring pediatric brain tumors. Proton MR spectroscopy (MRS), as an adjunct to MRI, is being more widely applied to monitor the metabolic aspects of brain cancer. In vivo MRS biomarkers represent a promising advance and may influence treatment choice at both initial diagnosis and follow-up, given the inherent difficulties of sequential biopsies to monitor therapeutic response. When combined with anatomical or other types of imaging, MRS provides unique information regarding biochemistry in inoperable brain tumors and can complement neuropathological data, guide biopsies and enhance insight into therapeutic options. The combination of noninvasively acquired prognostic information and the high-resolution anatomical imaging provided by conventional MRI is expected to surpass molecular analysis and DNA microarray gene profiling, both of which, although promising, depend on invasive biopsy. This review focuses on recent data in the field of MRS in children with brain tumors.

Keywords

Brain Children Magnetic resonance spectroscopy Tumor 

Notes

Compliance with ethical standards

Conflicts of interest

None

References

  1. 1.
    Ries LAG, Melbert D, Krapcho M et al (2007) SEER cancer statistics review, 1975–2004. National Cancer Institute, Bethesda. http://seer.cancer.gov/csr/1975_2004. Accessed 26 Dec 2007
  2. 2.
    Legler JM, Gloeckler Ries LA, Smith MA et al (2000) RESPONSE: brain and other central nervous system cancers: recent trends in incidence and mortality. J Natl Cancer Inst 92:A77–A78CrossRefGoogle Scholar
  3. 3.
    (2007) Cancer facts and figures 2007. American Cancer Society, Atlanta. http://www.cancer.org/acs/groups/content/@nho/documents/document/caff2007pwsecuredpdf.pdf. Accessed 15 Dec 2015
  4. 4.
    Ries LAG, Smith MA, Gurney JG et al (1999) Cancer incidence and survival among children and adolescents: United States SEER program 1975–1995. National Cancer Institute, Bethesda. http://seer.cancer.gov/archive/publications/childhood/childhood-monograph.pdf. Accessed 15 Dec 2015
  5. 5.
    Smith MA, Freidlin B, Ries LA et al (1998) Trends in reported incidence of primary malignant brain tumors in children in the United States. J Natl Cancer Inst 90:1269–1277CrossRefPubMedGoogle Scholar
  6. 6.
    Louis DN, Ohgaki H, Wiestler OD et al (2007) WHO classification of tumours of the central nervous system. IARC, LyonGoogle Scholar
  7. 7.
    Louis DN, Ohgaki H, Otmar D et al (2007) The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol 114:97–109CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Tzika AA, Zarifi MK, Goumnerova L et al (2002) Neuroimaging in pediatric brain tumors: Gd-DTPA-enhanced, hemodynamic, and diffusion MR imaging compared with MR spectroscopic imaging. AJNR Am J Neuroradiol 23:322–333PubMedGoogle Scholar
  9. 9.
    Gill S, Panigrahy A, Arvanitis TN et al (2013) Magnetic resonance spectroscopy of pediatric brain tumors. In: Bluml S, Panigrahy A (eds) MR spectroscopy of pediatric brain disorders. Springer, New York, Heidelberg, Dordrecht, London, pp 45–60CrossRefGoogle Scholar
  10. 10.
    Kurhanewicz J, Vigneron DB, Hricak H et al (1996) Prostate cancer: metabolic response to cryosurgery as detected with 3D H-1 MR spectroscopic imaging. Radiology 200:489–496CrossRefPubMedGoogle Scholar
  11. 11.
    Nelson SJ, Huhn S, Vigneron DB et al (1997) Volume MRI and MRSI techniques for the quantitation of treatment response in brain tumors: presentation of a detailed case study. J Magn Reson Imaging 7:1146–1152CrossRefPubMedGoogle Scholar
  12. 12.
    Wald LL, Nelson SJ, Day MR et al (1997) Serial proton magnetic resonance spectroscopy imaging of glioblastoma multiforme after brachytherapy. J Neurosurg 87:525–534CrossRefPubMedGoogle Scholar
  13. 13.
    Nelson SJ (2001) Analysis of volume MRI and MR spectroscopic imaging data for the evaluation of patients with brain tumors. Magn Reson Med 46:228–239CrossRefPubMedGoogle Scholar
  14. 14.
    Dillon WP, Nelson S (1999) What is the role of MR spectroscopy in the evaluation and treatment of brain neoplasms? AJNR Am J Neuroradiol 20:2–3PubMedGoogle Scholar
  15. 15.
    Nelson SJ, Vigneron DB, Dillon WP (1999) Serial evaluation of patients with brain tumors using volume MRI and 3D 1H MRSI. NMR Biomed 12:123–138CrossRefPubMedGoogle Scholar
  16. 16.
    Graves EE, Nelson SJ, Vigneron DB et al (2000) A preliminary study of the prognostic value of proton magnetic resonance spectroscopic imaging in gamma knife radiosurgery of recurrent malignant gliomas. Neurosurgery 46:319–326CrossRefPubMedGoogle Scholar
  17. 17.
    Graves EE, Nelson SJ, Vigneron DB et al (2001) Serial proton MR spectroscopic imaging of recurrent malignant gliomas after gamma knife radiosurgery. AJNR Am J Neuroradiol 22:613–624PubMedGoogle Scholar
  18. 18.
    Tzika AA, Cheng LL, Goumnerova L et al (2002) Biochemical characterization of pediatric brain tumors by using in vivo and ex vivo magnetic resonance spectroscopy. J Neurosurg 96:1023–1031CrossRefPubMedGoogle Scholar
  19. 19.
    Tzika AA, Vajapeyam S, Barnes PD (1997) Multivoxel proton MR spectroscopy and hemodynamic MR imaging of childhood brain tumors: preliminary observations. AJNR Am J Neuroradiol 18:203–218PubMedGoogle Scholar
  20. 20.
    Nelson SJ, Vigneron DB, Star-Lack J et al (1997) High spatial resolution and speed in MRSI. NMR Biomed 10:411–422CrossRefPubMedGoogle Scholar
  21. 21.
    Vigneron D, Bollen A, McDermott M et al (2001) Three-dimensional magnetic resonance spectroscopic imaging of histologically confirmed brain tumors. Magn Reson Imaging 19:89–101CrossRefPubMedGoogle Scholar
  22. 22.
    Wald LL, Moyher SE, Day MR et al (1995) Proton spectroscopic imaging of the human brain using phased array detectors. Magn Reson Med 34:440–445CrossRefPubMedGoogle Scholar
  23. 23.
    Li X, Lu Y, Pirzkall A et al (2002) Analysis of the spatial characteristics of metabolic abnormalities in newly diagnosed glioma patients. J Magn Reson Imaging 16:229–237CrossRefPubMedGoogle Scholar
  24. 24.
    Lazareff JA, Bockhorst KH, Curran J et al (1998) Pediatric low-grade gliomas: prognosis with proton magnetic resonance spectroscopic imaging. Neurosurgery 43:809–817CrossRefPubMedGoogle Scholar
  25. 25.
    Lazareff JA, Gupta RK, Alger J (1999) Variation of post-treatment H-MRSI choline intensity in pediatric gliomas. J Neurooncol 41:291–298CrossRefPubMedGoogle Scholar
  26. 26.
    Taylor JS, Ogg RJ, Langston JW (1998) Proton MR spectroscopy of pediatric brain tumors. Neuroimaging Clin N Am 8:753–779PubMedGoogle Scholar
  27. 27.
    Gonen O, Wang Z, Viswanathan A et al (1999) Three-dimensional multivoxel proton MR spectroscopy of the brain in children with neurofibromatosis type 1. AJNR Am J Neuroradiol 20:1333–1341PubMedGoogle Scholar
  28. 28.
    Tzika AA, Astrakas LG, Zarifi MK et al (2004) Spectroscopic and perfusion magnetic resonance imaging predictors of progression in pediatric brain tumors. Cancer 100:1246–1256CrossRefPubMedGoogle Scholar
  29. 29.
    Warren KE (2004) NMR spectroscopy and pediatric brain tumors. Oncologist 9:312–318CrossRefPubMedGoogle Scholar
  30. 30.
    Urenjak J, Williams SR, Gadian DG et al (1992) Specific expression of N-acetylaspartate in neurons, oligodendrocyte-type-2 astrocyte progenitors, and immature oligodendrocytes in vitro. J Neurochem 59:55–61CrossRefPubMedGoogle Scholar
  31. 31.
    Barker P, Glickson J, Bryan R (1993) In vivo magnetic resonance spectroscopy of brain tumors. Top Magn Reson Imaging 5:32–45CrossRefPubMedGoogle Scholar
  32. 32.
    Miller BL, Chang L, Booth R et al (1996) In vivo 1H MRS choline: correlation with in vitro chemistry/histology. Life Sci 58:1929–1935CrossRefPubMedGoogle Scholar
  33. 33.
    Daly PF, Lyon RC, Faustino PJ et al (1987) Phospholipid metabolism in cancer cells monitored by 31P NMR spectroscopy. J Biol Chem 262:14875–14878PubMedGoogle Scholar
  34. 34.
    Gillies RJ, Barry JA, Ross BD (1994) In vitro and in vivo 13C and 31P NMR analyses of phosphocholine metabolism in rat glioma cells. Magn Reson Med 32:310–318CrossRefPubMedGoogle Scholar
  35. 35.
    Shimizu H, Kumabe T, Shirane R et al (2000) Correlation between choline level measured by proton MR spectroscopy and Ki-67 labeling index in gliomas. AJNR Am J Neuroradiol 21:659–665PubMedGoogle Scholar
  36. 36.
    Tamiya T, Kinoshita K, Ono Y et al (2000) Proton magnetic resonance spectroscopy reflects cellular proliferative activity in astrocytomas. Neuroradiology 42:333–338CrossRefPubMedGoogle Scholar
  37. 37.
    Bhakoo KK, Williams SR, Florian CL et al (1996) Immortalization and transformation are associated with specific alterations in choline metabolism. Cancer Res 56:4630–4635PubMedGoogle Scholar
  38. 38.
    Cheng LL, Anthony DC, Comite AR et al (2000) Quantification of microheterogeneity in glioblastoma multiforme with ex vivo high-resolution magic-angle spinning (HRMAS) proton magnetic resonance spectroscopy. Neuro Oncol 2:87–95PubMedPubMedCentralGoogle Scholar
  39. 39.
    Chang L, McBride D, Miller BL et al (1995) Localized in vivo 1H magnetic resonance spectroscopy and in vitro analyses of heterogeneous brain tumors. J Neuroimaging 5:157–163CrossRefPubMedGoogle Scholar
  40. 40.
    Mahmood U, Alfieri AA, Thaler H et al (1994) Radiation dose-dependent changes in tumor metabolism measured by 31P nuclear magnetic resonance spectroscopy. Cancer Res 54:4885–4891PubMedGoogle Scholar
  41. 41.
    Aiken N, Gillies RJ (1996) Phosphomonoester metabolism as a function of cell proliferative status and exogenous precursors. Anticancer Res 16:1393–1397PubMedGoogle Scholar
  42. 42.
    Aboagye EO, Bhujwalla ZM (1999) Malignant transformation alters membrane choline phospholipid metabolism of human mammary epithelial cells. Cancer Res 59:80–84PubMedGoogle Scholar
  43. 43.
    Ackerstaff E, Pflug BR, Nelson JB et al (2001) Detection of increased choline compounds with proton nuclear magnetic resonance spectroscopy subsequent to malignant transformation of human prostatic epithelial cells. Cancer Res 61:3599–3603PubMedGoogle Scholar
  44. 44.
    Alger JR, Frank JA, Bizzi A et al (1990) Metabolism of human gliomas: assessment with H-1 MR spectroscopy and F-18 fluorodeoxyglucose PET. Radiology 177:633–641CrossRefPubMedGoogle Scholar
  45. 45.
    Herholz K, Heindel W, Luyten PR et al (1992) In vivo imaging of glucose consumption and lactate concentration in human gliomas. Ann Neurol 31:319–327CrossRefPubMedGoogle Scholar
  46. 46.
    Tugnoli V, Tosi MR, Tinti A et al (2001) Characterization of lipids from human brain tissues by multinuclear magnetic resonance spectroscopy. Biopolymers 62:297–306CrossRefPubMedGoogle Scholar
  47. 47.
    Veale MF, Roberts NJ, King GF et al (1997) The generation of 1H-NMR-detectable mobile lipid in stimulated lymphocytes: relationship to cellular activation, the cell cycle, and phosphatidylcholine-specific phospholipase C. Biochem Biophys Res Commun 239:868–874CrossRefPubMedGoogle Scholar
  48. 48.
    Howe FA, Barton SJ, Cudlip SA et al (2003) Metabolic profiles of human brain tumors using quantitative in vivo 1H magnetic resonance spectroscopy. Magn Reson Med 49:223–232CrossRefPubMedGoogle Scholar
  49. 49.
    Di Costanzo A, Scarabino T, Trojsi F et al (2008) Proton MR spectroscopy of cerebral gliomas at 3T: spatial heterogeneity, and tumour grade and extent. Eur Radiol 18:1727–1735CrossRefPubMedGoogle Scholar
  50. 50.
    Castillo M, Smith JK, Kwock L (2000) Correlation of myo-inositol levels and grading of cerebral astrocytomas. AJNR Am J Neuroradiol 21:1645–1649PubMedGoogle Scholar
  51. 51.
    Hattingen E, Raab P, Franz K et al (2008) Myo-inositol: a marker of reactive astrogliosis in glial tumors? NMR Biomed 21:233–241CrossRefPubMedGoogle Scholar
  52. 52.
    Saraf-Lavi E, Bowen BC, Pattany PM et al (2003) Proton MR spectroscopy of gliomatosis cerebri: case report of elevated myoinositol with normal choline levels. AJNR Am J Neuroradiol 24:946–951PubMedGoogle Scholar
  53. 53.
    Tzika A, Zurakowski D, Poussaint T et al (2001) Proton magnetic resonance spectroscopic imaging of the child’s brain: the response of tumors to treatment. Neuroradiology 43:169–177CrossRefPubMedGoogle Scholar
  54. 54.
    Lombardi V, Valko L, Valko M et al (1997) 1H NMR ganglioside ceramide resonance region on the differential diagnosis of low and high malignancy of brain gliomas. Cell Mol Neurobiol 17:521–535CrossRefPubMedGoogle Scholar
  55. 55.
    Kyriakis JM, Avruch J (1996) Protein kinase cascades activated by stress and inflammatory cytokines. Bioessays 18:567–577CrossRefPubMedGoogle Scholar
  56. 56.
    Susin SA, Zamzami N, Castedo M et al (1997) The central executioner of apoptosis: multiple connections between protease activation and mitochondria in Fas/APO-1/CD95- and ceramide-induced apoptosis. J Exp Med 186:25–37CrossRefPubMedPubMedCentralGoogle Scholar
  57. 57.
    Kolesnick RN, Kronke M (1998) Regulation of ceramide production and apoptosis. Annu Rev Physiol 60:643–665CrossRefPubMedGoogle Scholar
  58. 58.
    Schwandner R, Wiegmann K, Bernardo K et al (1998) TNF receptor death domain-associated proteins TRADD and FADD signal activation of acid sphingomyelinase. J Biol Chem 273:5916–5922CrossRefPubMedGoogle Scholar
  59. 59.
    Williams SN, Anthony ML, Brindle KM (1998) Induction of apoptosis in two mammalian cell lines results in increased levels of fructose-1,6-bisphosphate and CDP-choline as determined by 31P MRS. Magn Reson Med 40:411–420CrossRefPubMedGoogle Scholar
  60. 60.
    Ashkenazi A, Dixit VM (1998) Death receptors: signaling and modulation. Science 281:1305–1308CrossRefPubMedGoogle Scholar
  61. 61.
    De Laurenzi V, Melino G (2000) Apoptosis. The little devil of death. Nature 406:135–136CrossRefPubMedGoogle Scholar
  62. 62.
    Tournier C, Hess P, Yang DD et al (2000) Requirement of JNK for stress-induced activation of the cytochrome c-mediated death pathway. Science 288:870–874CrossRefPubMedGoogle Scholar
  63. 63.
    Arle JE, Morriss C, Wang ZJ et al (1997) Prediction of posterior fossa tumor type in children by means of magnetic resonance image properties, spectroscopy, and neural networks. J Neurosurg 86:755–761CrossRefPubMedGoogle Scholar
  64. 64.
    Warren KE, Frank JA, Black JL et al (2000) Proton magnetic resonance spectroscopic imaging in children with recurrent primary brain tumors. J Clin Oncol 18:1020–1026PubMedGoogle Scholar
  65. 65.
    Panigrahy A, Krieger MD, Gonzalez-Gomez I et al (2006) Quantitative short echo time 1H-MR spectroscopy of untreated pediatric brain tumors: preoperative diagnosis and characterization. AJNR Am J Neuroradiol 27:560–572PubMedGoogle Scholar
  66. 66.
    Desprechins B, Stadnik T, Koerts G et al (1999) Use of diffusion-weighted MR imaging in differential diagnosis between intracerebral necrotic tumors and cerebral abscesses. AJNR Am J Neuroradiol 20:1252–1257PubMedGoogle Scholar
  67. 67.
    Garg M, Gupta RK (2004) MR spectroscopy in intracranial infection. In: Gillard JH, Waldman AD, Barker PB (eds) Clinical MR neuroimaging: diffusion, perfusion and spectroscopy. Cambridge University Press, Cambridge, pp 380–406CrossRefGoogle Scholar
  68. 68.
    Saindane AM, Cha S, Law M et al (2002) Proton MR spectroscopy of tumefactive demyelinating lesions. AJNR Am J Neuroradiol 23:1378–1386PubMedGoogle Scholar
  69. 69.
    Chawla S, Zhang Y, Wang S et al (2010) Proton magnetic resonance spectroscopy in differentiating glioblastomas from primary cerebral lymphomas and brain metastases. J Comput Assist Tomogr 34:836–841CrossRefPubMedGoogle Scholar
  70. 70.
    Porto L, Kieslich M, Franz K et al (2010) Spectroscopy of untreated pilocytic astrocytomas: do children and adults share some metabolic features in addition to their morphologic similarities? Childs Nerv Syst 26:801–806CrossRefPubMedGoogle Scholar
  71. 71.
    Xu M, See SJ, Ng WH et al (2005) Comparison of magnetic resonance spectroscopy and perfusion-weighted imaging in presurgical grading of oligodendroglial tumors. Neurosurgery 56:919–926PubMedGoogle Scholar
  72. 72.
    Star-Lack J, Spielman D, Adalsteinsson E et al (1998) In vivo lactate editing with simultaneous detection of choline, creatine, NAA, and lipid singlets at 1.5T using PRESS excitation with applications to the study of brain and head and neck tumors. J Magn Reson 133:243–254CrossRefPubMedGoogle Scholar
  73. 73.
    Tzika AA, Astrakas LG, Zarifi MK et al (2003) Multiparametric MR assessment of pediatric brain tumors. Neuroradiology 45:1–10CrossRefPubMedGoogle Scholar
  74. 74.
    Al-Okaili RN, Krejza J, Wang S et al (2006) Advanced MR imaging techniques in the diagnosis of intraaxial brain tumors in adults. Radiographics 26:S173–S189CrossRefPubMedGoogle Scholar
  75. 75.
    Al-Okaili RN, Krejza J, Woo JH et al (2007) Intraaxial brain masses: MR imaging-based diagnostic strategy — initial experience. Radiology 243:539–550CrossRefPubMedGoogle Scholar
  76. 76.
    Law M, Hamburger M, Johnson G et al (2004) Differentiating surgical from non-surgical lesions using perfusion MR imaging and proton MR spectroscopic imaging. Technol Cancer Res Treat 3:557–565CrossRefPubMedGoogle Scholar
  77. 77.
    (2010) Childhood Cancer Research Group (CCRG). National Registry of Childhood Tumours/Childhood Cancer Research Group. University of Oxford. http://www.ccrg.ox.ac.uk/datasets/nrct.shtml. Accessed 15 Dec 2015
  78. 78.
    Marcus KJ, Astrakas LG, Zurakowski D et al (2007) Predicting survival of children with CNS tumors using proton magnetic resonance spectroscopic imaging biomarkers. Int J Oncol 30:651–657PubMedGoogle Scholar
  79. 79.
    Tarnawski R, Sokol M, Pieniazek P et al (2002) 1H-MRS in vivo predicts the early treatment outcome of postoperative radiotherapy for malignant gliomas. Int J Radiat Oncol Biol Phys 52:1271–1276CrossRefPubMedGoogle Scholar
  80. 80.
    Aria Tzika AA (2008) Proton magnetic resonance spectroscopic imaging as a cancer biomarker for pediatric brain tumors (review). Int J Oncol 32:517–526CrossRefPubMedGoogle Scholar
  81. 81.
    Crawford FW, Khayal IS, McGue C et al (2009) Relationship of pre-surgery metabolic and physiological MR imaging parameters to survival for patients with untreated GBM. J Neurooncol 91:337–351CrossRefPubMedPubMedCentralGoogle Scholar
  82. 82.
    Wilson M, Cummins CL, MacPherson L et al (2013) Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours. Eur J Cancer 49:457–464CrossRefPubMedPubMedCentralGoogle Scholar
  83. 83.
    Astrakas L, Blekas KD, Constantinou C et al (2011) Combining magnetic resonance spectroscopy and molecular genomics offers better accuracy in brain tumor typing and prediction of survival than either methodology alone. Int J Oncol 38:1113–1127PubMedGoogle Scholar
  84. 84.
    Loukas Astrakas L, Tzika AA (2014) Brain tumor typing and therapy using combined ex vivo magnetic resonance spectroscopy and molecular genomics. In: Hayat MA (ed) Tumors of the central nervous system, vol. 12. Springer, New York, Heidelberg, Dordrecht, London, pp 149–158Google Scholar
  85. 85.
    Heiss WD, Raab P, Lanfermann H (2011) Multimodality assessment of brain tumors and tumor recurrence. J Nucl Med 52:1585–1600CrossRefPubMedGoogle Scholar
  86. 86.
    Van den Bent MJ, Vogelbaum MA, Wen PY et al (2009) End point assessment in gliomas: novel treatments limit usefulness of classical [sic] Macdonald’s criteria. J Clin Oncol 27:2905–2908CrossRefPubMedPubMedCentralGoogle Scholar
  87. 87.
    Wen PY, Macdonald DR, Reardon DA et al (2010) Updated response assessment criteria for high-grade gliomas: response assessment in Neuro-Oncology Working Group. J Clin Oncol 28:1963–1972CrossRefPubMedGoogle Scholar
  88. 88.
    Gill SK, Wilson M, Davies NP et al (2014) Diagnosing relapse in children’s brain tumors using metabolite profiles. Neuro Oncol 16:156–164CrossRefPubMedPubMedCentralGoogle Scholar
  89. 89.
    Horská A, Barker P (2010) Imaging of brain tumors: MR spectroscopy and metabolic imaging. Neuroimaging Clin N Am 20:293–310CrossRefPubMedPubMedCentralGoogle Scholar
  90. 90.
    Lee MC, Nelson SJ (2008) Supervised pattern recognition for the prediction of contrast-enhancement appearance in brain tumors from multivariate magnetic resonance imaging and spectroscopy. Artif Intell Med 43:61–74CrossRefPubMedPubMedCentralGoogle Scholar
  91. 91.
    Menze BH, Kelm BM, Weber MA et al (2008) Mimicking the human expert: pattern recognition for an automated assessment of data quality in MR spectroscopic images. Magn Reson Med 59:1457–1466CrossRefPubMedGoogle Scholar
  92. 92.
    Wright AJ, Fellows G, Byrnes TJ et al (2009) Pattern recognition of MRSI data shows regions of glioma growth that agree with DTI markers of brain tumor infiltration. Magn Reson Med 62:1646–1651CrossRefPubMedGoogle Scholar
  93. 93.
    Goo HW (2013) Advanced magnetic resonance imaging for pediatric brain tumors: current imaging techniques and interpretation algorithms. Clin Pediatr Hematol Oncol 20:13–21Google Scholar
  94. 94.
    Panigrahy A, Bluml S (2009) Neuroimaging of pediatric brain tumors: from basic to advanced magnetic resonance imaging (MRI). J Child Neurol 24:1343–1365CrossRefPubMedGoogle Scholar
  95. 95.
    Rossi A, Gandolfo C, Morana G et al (2010) New MR sequences (diffusion, perfusion, spectroscopy) in brain tumours. Pediatr Radiol 40:999–1009CrossRefPubMedGoogle Scholar
  96. 96.
    (2015) Web site. The Pediatric Brain Tumor Consortium (PBTC). http://www.pbtc.org. Accessed 15 Dec 2015

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of RadiologyAghia Sophia Children’s HospitalAthensGreece
  2. 2.Department of Surgery, Massachusetts General HospitalHarvard Medical SchoolBostonUSA
  3. 3.Shriners Burn HospitalBostonUSA

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