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Positron emission tomography and magnetic resonance spectroscopy in cerebral gliomas

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Abstract

Purpose

Conventional MRI, the gold standard in structural brain imaging, alone has its limitations in pre-operative tumour grading, biopsy targeting, determination of accurate tumour margins prior to surgical resection/radiation therapy, detection of tumour recurrence and determination of early therapeutic response. The aim was to introduce and review two of the recently most discussed adjunct modalities for molecular imaging in glioma: PET and MRS, and the combination of both.

Methods

A PubMed search with a combination of the terms “MRS”, “glioma” and “glioblastoma”, “brain tumour”, “positron emission” and “PET” was carried out. These results were complemented with a search of the authors’ own files. Preclinical in vitro studies as well as animal studies were excluded.

Results

Published single modality data show that 1H-MRS and PET perform similarly in answering clinical questions, which cannot be adequately answered by conventional MR imaging alone. Original articles including patients with gliomas and combining the PET and MRS modalities within the same study were scarce and resulted in 17 research papers. These articles especially point to a spatial correlation between 1H-MRS metabolic ratios and amino acid uptake and a positive relationship with histologically proven cell proliferation markers, indicating diagnostic improvement in the differentiation between glioma and benign lesions, in the delineation of brain tumours and in the differentiation between treatment-related changes and tumour progression.

Conclusion

PET and 1H-MRS have shown their value in the non-invasive diagnosis of gliomas delivering metabolic tumour information in addition to pure structural information from conventional MRI or CT alone. The very few studies, which were conducted evaluating 1H-MRS and PET in combination, indicate a diagnostic benefit from a combined imaging approach in glioma and encourage more systematic investigation—ideally carried out in multicentric settings, in experienced neuroimaging centres (with access to integrated PET/MRI scanners), using standardized imaging- and analysis protocols.

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References

  1. Di Chiro G et al (1982) Glucose utilization of cerebral gliomas measured by [18F] fluorodeoxyglucose and positron emission tomography. Neurology 32(12):1323–1329

    Article  PubMed  Google Scholar 

  2. Delbeke D et al (1995) Optimal cutoff levels of F-18 fluorodeoxyglucose uptake in the differentiation of low-grade from high-grade brain tumors with PET. Radiology 195(1):47–52

    Article  CAS  PubMed  Google Scholar 

  3. Glantz MJ et al (1991) Identification of early recurrence of primary central nervous system tumors by [18F] fluorodeoxyglucose positron emission tomography. Ann Neurol 29(4):347–355

    Article  CAS  PubMed  Google Scholar 

  4. Holzer T et al (1993) FDG-PET as a prognostic indicator in radiochemotherapy of glioblastoma. J Comput Assist Tomogr 17(5):681–687

    Article  CAS  PubMed  Google Scholar 

  5. Herholz K et al (1998) 11C-methionine PET for differential diagnosis of low-grade gliomas. Neurology 50(5):1316–1322

    Article  CAS  PubMed  Google Scholar 

  6. Habermeier A et al (2015) System L amino acid transporter LAT1 accumulates O-(2-fluosroethyl)-l-tyrosine (FET). Amino Acids 47(2):335–344

    Article  CAS  PubMed  Google Scholar 

  7. Pauleit D et al (2005) O-(2-[18F]fluoroethyl)-l-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain 128(Pt 3):678–687

    Article  PubMed  Google Scholar 

  8. Arbizu J et al (2012) Quantitative volumetric analysis of gliomas with sequential MRI and (1)(1)C-methionine PET assessment: patterns of integration in therapy planning. Eur J Nucl Med Mol Imaging 39(5):771–781

    Article  PubMed  Google Scholar 

  9. Pirotte B et al (2004) Comparison of 18F-FDG and 11C-methionine for PET-guided stereotactic brain biopsy of gliomas. J Nucl Med 45(8):1293–1298

    CAS  PubMed  Google Scholar 

  10. Galldiks N et al (2015) The use of dynamic O-(2-18F-fluoroethyl)-l-tyrosine PET in the diagnosis of patients with progressive and recurrent glioma. Neuro Oncol 17(9):1293–1300

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Piroth MD et al (2013) Monitoring of radiochemotherapy in patients with glioblastoma using O-(2-(1)(8)Fluoroethyl)-l-tyrosine positron emission tomography: is dynamic imaging helpful? Mol Imaging 12(6):388–395

    CAS  PubMed  Google Scholar 

  12. Galldiks N et al (2015) The use of dynamic O-(2-18F-fluoroethyl)-l-tyrosine PET in the diagnosis of patients with progressive and recurrent glioma. Neuro Oncol 17(9):1293-1300

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Gempt J et al (2015) 18F-fluoro-ethyl-tyrosine positron emission tomography for grading and estimation of prognosis in patients with intracranial gliomas. Eur J Radiol 84(5):955–962

    Article  PubMed  Google Scholar 

  14. Popperl G et al (2007) FET PET for the evaluation of untreated gliomas: correlation of FET uptake and uptake kinetics with tumour grading. Eur J Nucl Med Mol Imaging 34(12):1933–1942

    Article  PubMed  Google Scholar 

  15. Bette S et al (2016) Static FET–PET and MR imaging in anaplastic gliomas (WHO III). World Neurosurg 91:524–531

    Article  PubMed  Google Scholar 

  16. Suchorska B et al (2015) Biological tumor volume in 18FET-PET before radiochemotherapy correlates with survival in GBM. Neurology 84(7):710–719

    Article  CAS  PubMed  Google Scholar 

  17. Pyka T et al (2016) Textural analysis of pre-therapeutic [18F]-FET-PET and its correlation with tumor grade and patient survival in high-grade gliomas. Eur J Nucl Med Mol Imaging 43(1):133–141

    Article  PubMed  Google Scholar 

  18. Bette S et al (2016) Prognostic value of O-(2-[18F]-fluoroethyl)-l-tyrosine-positron emission tomography imaging for histopathologic characteristics and progression-free survival in patients with low-grade glioma. World Neurosurg 89:230–239

    Article  PubMed  Google Scholar 

  19. Jansen NL et al (2012) Prediction of oligodendroglial histology and LOH 1p/19q using dynamic [(18)F]FET-PET imaging in intracranial WHO grade II and III gliomas. Neuro Oncol 14(12):1473–1480

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Albert NL et al (2016) Response Assessment in Neuro-Oncology working group and European Association for Neuro-Oncology recommendations for the clinical use of PET imaging in gliomas. Neuro Oncol 18(9):1199–1208

    Article  PubMed  Google Scholar 

  21. Langen KJ, Watts C (2016) Neuro-oncology: amino acid PET for brain tumours—ready for the clinic? Nat Rev Neurol 12(7):375–376

    Article  PubMed  Google Scholar 

  22. Heiss WD et al (1996) F-Dopa as an amino acid tracer to detect brain tumors. J Nucl Med 37(7):1180–1182

    CAS  PubMed  Google Scholar 

  23. Youland RS et al (2013) The role of LAT1 in (18)F-DOPA uptake in malignant gliomas. J Neuro oncol 111(1):11–18

    Article  CAS  Google Scholar 

  24. Kratochwil C et al (2014) Intra-individual comparison of (1)(8)F-FET and (1)(8)F-DOPA in PET imaging of recurrent brain tumors. Neuro Oncol 16(3):434–440

    Article  CAS  PubMed  Google Scholar 

  25. Lapa C et al (2014) Comparison of the amino acid tracers 18F-FET and 18F-DOPA in high-grade glioma patients. J Nucl Med 55(10):1611–1616

    Article  CAS  PubMed  Google Scholar 

  26. Rasey JS et al (2002) Validation of FLT uptake as a measure of thymidine kinase-1 activity in A549 carcinoma cells. J Nucl Med 43(9):1210–1217

    CAS  PubMed  Google Scholar 

  27. Chen W et al (2005) Imaging proliferation in brain tumors with 18F-FLT PET: comparison with 18F-FDG. J Nucl Med 46(6):945–952

    CAS  PubMed  Google Scholar 

  28. Jacobs AH et al (2005) 18F-fluoro-L-thymidine and 11C-methylmethionine as markers of increased transport and proliferation in brain tumors. J Nucl Med 46(12):1948–1958

    CAS  PubMed  Google Scholar 

  29. Chaumeil MM, Lupo JM, Ronen SM (2015) Magnetic resonance (MR) metabolic imaging in glioma. Brain Pathol 25(6):769–780

    Article  CAS  PubMed  Google Scholar 

  30. Poteet E et al (2013) Reversing the Warburg effect as a treatment for glioblastoma. J Biol Chem 288(13):9153–9164

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Vander Heiden MG, Cantley LC, Thompson CB (2009) Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324(5930):1029–1033

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Warburg O (1956) On the origin of cancer cells. Science 123(3191):309–314

    Article  CAS  PubMed  Google Scholar 

  33. Alger JR et al (1990) Metabolism of human gliomas: assessment with H-1 MR spectroscopy and F-18 fluorodeoxyglucose PET. Radiology 177(3):633–641

    Article  CAS  PubMed  Google Scholar 

  34. Law M et al (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 Neuro radiol 24(10):1989–1998

    Google Scholar 

  35. Miller BL (1991) A review of chemical issues in 1H NMR spectroscopy: N-acetyl-l-aspartate, creatine and choline. NMR Biomed 4(2):47–52

    Article  CAS  PubMed  Google Scholar 

  36. Patra S et al (2012) A short review on creatine–creatine kinase system in relation to cancer and some experimental results on creatine as adjuvant in cancer therapy. Amino Acids 42(6):2319–2330

    Article  CAS  PubMed  Google Scholar 

  37. Glunde K, Bhujwalla ZM, Ronen SM (2011) Choline metabolism in malignant transformation. Nat Rev Cancer 11(12):835–848

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Negendank W, Sauter R (1996) Intratumoral lipids in 1H MRS in vivo in brain tumors: experience of the Siemens cooperative clinical trial. Anticancer Res 16(3B):1533–1538

    CAS  PubMed  Google Scholar 

  39. Zoula S et al (2003) Correlation between the occurrence of 1H-MRS lipid signal, necrosis and lipid droplets during C6 rat glioma development. NMR Biomed 16(4):199–212

    Article  CAS  PubMed  Google Scholar 

  40. Campbell SL, Buckingham SC, Sontheimer H (2012) Human glioma cells induce hyperexcitability in cortical networks. Epilepsia 53(8):1360–1370

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Robert SM, Sontheimer H (2014) Glutamate transporters in the biology of malignant gliomas. Cell Mol Life Sci 71(10):1839–1854

    Article  CAS  PubMed  Google Scholar 

  42. Takano T et al (2001) Glutamate release promotes growth of malignant gliomas. Nat Med 7(9):1010–1015

    Article  CAS  PubMed  Google Scholar 

  43. Brandao LA, Domingues RC (2004) MR Spectroscopy of the Brain. Lippincott Williams & Wilkins, Philadelphia, Pennsylvania

    Google Scholar 

  44. Gyngell ML et al (1992) Localized proton NMR spectroscopy of experimental gliomas in rat brain in vivo. NMR Biomed 5(6):335–340

    Article  CAS  PubMed  Google Scholar 

  45. Luo Y et al (1999) In vivo observation of lactate methyl proton magnetization transfer in rat C6 glioma. Magn Reson Med 41(4):676–685

    Article  CAS  PubMed  Google Scholar 

  46. McKnight TR et al (2001) An automated technique for the quantitative assessment of 3D-MRSI data from patients with glioma. J Magn Reson Imaging 13(2):167–177

    Article  CAS  PubMed  Google Scholar 

  47. Remy C et al (1994) In vivo, ex vivo, and in vitro one- and two-dimensional nuclear magnetic resonance spectroscopy of an intracerebral glioma in rat brain: assignment of resonances. J Neurochem 62(1):166–179

    Article  CAS  PubMed  Google Scholar 

  48. Chang SM et al (2009) Integration of preoperative anatomic and metabolic physiologic imaging of newly diagnosed glioma. J Neurooncol 92(3):401–415

    Article  PubMed  PubMed Central  Google Scholar 

  49. Gempt J et al (2014) Multimodal imaging in cerebral gliomas and its neuropathological correlation. Eur J Radiol 83(5):829–834

    Article  PubMed  Google Scholar 

  50. Wang Q et al (2016) The diagnostic performance of magnetic resonance spectroscopy in differentiating high-from low-grade gliomas: a systematic review and meta-analysis. Eur Radiol 26(8):2670–2684

    Article  PubMed  Google Scholar 

  51. Zhang H et al (2014) Role of magnetic resonance spectroscopy for the differentiation of recurrent glioma from radiation necrosis: a systematic review and meta-analysis. Eur J Radiol 83(12):2181–2189

    Article  PubMed  Google Scholar 

  52. Bruhn H et al (1989) Noninvasive differentiation of tumors with use of localized H-1 MR spectroscopy in vivo: initial experience in patients with cerebral tumors. Radiology 172(2):541–548

    Article  CAS  PubMed  Google Scholar 

  53. Sahin N et al (2013) Advanced MR imaging techniques in the evaluation of nonenhancing gliomas: perfusion-weighted imaging compared with proton magnetic resonance spectroscopy and tumor grade. Neuroradiol J 26(5):531–541

    Article  PubMed  PubMed Central  Google Scholar 

  54. Liu ZL et al (2012) Noninvasive evaluation of cerebral glioma grade by using diffusion-weighted imaging-guided single-voxel proton magnetic resonance spectroscopy. J Int Med Res 40(1):76–84

    Article  PubMed  Google Scholar 

  55. Yamasaki F et al (2011) Magnetic resonance spectroscopic detection of lactate is predictive of a poor prognosis in patients with diffuse intrinsic pontine glioma. Neuro Oncol 13(7):791–801

    Article  PubMed  PubMed Central  Google Scholar 

  56. Hattingen E et al (2008) Prognostic value of choline and creatine in WHO grade II gliomas. Neuroradiology 50(9):759–767

    Article  PubMed  Google Scholar 

  57. Kazda T et al (2016) Advanced MRI increases the diagnostic accuracy of recurrent glioblastoma: single institution thresholds and validation of MR spectroscopy and diffusion weighted MR imaging. Neuroimage Clin 11:316–321

    Article  PubMed  PubMed Central  Google Scholar 

  58. Choi C et al (2012) 2-Hydroxyglutarate detection by magnetic resonance spectroscopy in IDH-mutated patients with gliomas. Nat Med 18(4):624–629

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Louis DN et al (2016) The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol 131(6):803–820

    Article  PubMed  Google Scholar 

  60. Lu C et al (2012) IDH mutation impairs histone demethylation and results in a block to cell differentiation. Nature 483(7390):474–478

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. de la Fuente MI et al (2016) Integration of 2-hydroxyglutarate-proton magnetic resonance spectroscopy into clinical practice for disease monitoring in isocitrate dehydrogenase-mutant glioma. Neuro Oncol 18(2):283–290

    Article  PubMed  Google Scholar 

  62. Prat R et al (2010) Relative value of magnetic resonance spectroscopy, magnetic resonance perfusion, and 2-(18F) fluoro-2-deoxy-d-glucose positron emission tomography for detection of recurrence or grade increase in gliomas. J Clin Neurosci 17(1):50–53

    Article  CAS  PubMed  Google Scholar 

  63. Imani F et al (2012) Comparison of proton magnetic resonance spectroscopy with fluorine-18 2-fluoro-deoxyglucose positron emission tomography for assessment of brain tumor progression. J Neuroimaging 22(2):184–190

    Article  PubMed  Google Scholar 

  64. Hipp SJ et al (2012) Molecular imaging of pediatric brain tumors: comparison of tumor metabolism using (1)(8)F-FDG-PET and MRSI. J Neurooncol 109(3):521–527

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Collet S et al (2015) [(18)F]-fluoro-l-thymidine PET and advanced MRI for preoperative grading of gliomas. Neuroimage Clin 8:448–454

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Weber MA et al (2010) Biopsy targeting gliomas: do functional imaging techniques identify similar target areas? Invest Radiol 45(12):755–768

    Article  PubMed  Google Scholar 

  67. Imani F et al (2014) Molecular and metabolic pattern classification for detection of brain glioma progression. Eur J Radiol 83(2):e100–e105

    Article  PubMed  Google Scholar 

  68. Yoon JH et al (2014) Grading of cerebral glioma with multiparametric MR imaging and 18F-FDG-PET: concordance and accuracy. Eur Radiol 24(2):380–389

    Article  PubMed  Google Scholar 

  69. Goda JS et al (2013) Can multiparametric MRI and FDG-PET predict outcome in diffuse brainstem glioma? A report from a prospective phase-II study. Pediatr Neurosurg 49(5):274–281

    Article  PubMed  Google Scholar 

  70. Floeth FW et al (2005) Multimodal metabolic imaging of cerebral gliomas: positron emission tomography with [18F]fluoroethyl-l-tyrosine and magnetic resonance spectroscopy. J Neurosurg 102(2):318–327

    Article  PubMed  Google Scholar 

  71. D’Souza MM et al (2014) 11C-MET PET/CT and advanced MRI in the evaluation of tumor recurrence in high-grade gliomas. Clin Nucl Med 39(9):791–798

    Article  PubMed  Google Scholar 

  72. Nakajima T et al (2009) Differential diagnosis between radiation necrosis and glioma progression using sequential proton magnetic resonance spectroscopy and methionine positron emission tomography. Neurol Med Chir (Tokyo) 49(9):394–401

    Article  Google Scholar 

  73. Dunet V et al (2014) Combination of MRI and dynamic FET PET for initial glioma grading. Nuklearmedizin 53(4):155–161

    Article  CAS  PubMed  Google Scholar 

  74. Bisdas S et al (2013) Metabolic mapping of gliomas using hybrid MR-PET imaging: feasibility of the method and spatial distribution of metabolic changes. Invest Radiol 48(5):295–301

    Article  CAS  PubMed  Google Scholar 

  75. Mauler J et al (2015) Congruency of tumour volume delineated by FET PET and MRSI. EJNMMI Phys 2(Suppl 1):A61

    Article  PubMed  PubMed Central  Google Scholar 

  76. Morana G et al (2015) Diagnostic and prognostic value of 18F-DOPA PET and 1H-MR spectroscopy in pediatric supratentorial infiltrative gliomas: a comparative study. Neuro Oncol 17(12):1637–1647

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Bailey DL et al (2015) Combined PET/MR: the real work has just started. Summary report of the third international workshop on PET/MR imaging; February 17–21, 2014, Tubingen, Germany. Mol Imaging Biol 17(3):297–312

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Kim ES et al (2016) A novel, integrated PET-guided MRS technique resulting in more accurate initial diagnosis of high-grade glioma. Neuroradiol J 29(3):193–197

    Article  PubMed  Google Scholar 

  79. Stadlbauer A et al (2008) Metabolic imaging of cerebral gliomas: spatial correlation of changes in O-(2-18F-fluoroethyl)-l-tyrosine PET and proton magnetic resonance spectroscopic imaging. J Nucl Med 49(5):721–729

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Neurochirurgische Klinik und Poliklinik, Klinikum Rechts Der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany

    Jens Gempt & Florian Ringel

  2. Abteilung für Neuroradiologie, Klinikum Rechts Der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany

    Stefanie Bette

  3. Nuklearmedizinische Klinik und Poliklinik, Klinikum Rechts Der Isar, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany

    Thomas Pyka & Stefan Förster

  4. Klinik und Institut für Nuklearmedizin, Klinikum Bayreuth, Preuschwitzer Str. 101, 95445, Bayreuth, Germany

    Stefan Förster

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  1. Thomas Pyka
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  2. Jens Gempt
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  3. Stefanie Bette
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  4. Florian Ringel
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Correspondence to Stefan Förster.

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Pyka, T., Gempt, J., Bette, S. et al. Positron emission tomography and magnetic resonance spectroscopy in cerebral gliomas. Clin Transl Imaging 5, 151–158 (2017). https://doi.org/10.1007/s40336-017-0222-2

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