Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Advances in neuro-oncology imaging

Key Points

  • Improvement of brain tumour diagnostics is necessary because therapies are extremely expensive and their efficient use is mandatory

  • Both amino acid PET and advanced MRI methods (perfusion-weighted imaging, diffusion-weighted imaging and magnetic resonance spectroscopic imaging) provide substantial additional information for brain tumour diagnostics

  • Advanced MRI methods are readily available but interpretation is challenging and images are frequently impaired by susceptibility artefacts

  • Amino acid PET requires additional scanning but is a robust and attractive approach for clinicians because of easy scan reading

  • Information from amino acid PET and advanced MRI methods seems to be complementary but multimodal studies are scarce and urgently needed

Abstract

Despite the fact that MRI has evolved to become the standard method for diagnosis and monitoring of patients with brain tumours, conventional MRI sequences have two key limitations: the inability to show the full extent of the tumour and the inability to differentiate neoplastic tissue from nonspecific, treatment-related changes after surgery, radiotherapy, chemotherapy or immunotherapy. In the past decade, PET involving the use of radiolabelled amino acids has developed into an important diagnostic tool to overcome some of the shortcomings of conventional MRI. The Response Assessment in Neuro-Oncology working group — an international effort to develop new standardized response criteria for clinical trials in brain tumours — has recommended the additional use of amino acid PET imaging for brain tumour management. Concurrently, a number of advanced MRI techniques such as magnetic resonance spectroscopic imaging and perfusion weighted imaging are under clinical evaluation to target the same diagnostic problems. This Review summarizes the clinical role of amino acid PET in relation to advanced MRI techniques for differential diagnosis of brain tumours; delineation of tumour extent for treatment planning and biopsy guidance; post-treatment differentiation between tumour progression or recurrence versus treatment-related changes; and monitoring response to therapy. An outlook for future developments in PET and MRI techniques is also presented.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Patient with an anaplastic astrocytoma WHO grade III.
Figure 2: Hybrid PET–MRI study of a patient with newly diagnosed glioblastoma WHO grade IV.
Figure 3: Hybrid PET–MRI study of a patient with low-grade glioma.

Similar content being viewed by others

References

  1. Ostrom, Q. T. et al. CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2007–2011. Neuro Oncol. 16 (Suppl. 4), iv1–iv63 (2014).

    PubMed  PubMed Central  Google Scholar 

  2. Nayak, L., Lee, E. Q. & Wen, P. Y. Epidemiology of brain metastases. Curr. Oncol. Rep. 14, 48–54 (2012).

    Article  PubMed  Google Scholar 

  3. Louis, D. N. et al. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathol. 131, 803–820 (2016).

    Article  PubMed  Google Scholar 

  4. Ohgaki, H. & Kleihues, P. Population-based studies on incidence, survival rates, and genetic alterations in astrocytic and oligodendroglial gliomas. J. Neuropathol. Exp. Neurol. 64, 479–489 (2005).

    Article  CAS  PubMed  Google Scholar 

  5. Albert, N. L. et al. 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, 1199–1208 (2016). This study presents the recommendations of an international group of experts for the clinical use of PET imaging in brain tumours.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Ryken, T. C. et al. The role of imaging in the management of progressive glioblastoma: a systematic review and evidence-based clinical practice guideline. J. Neurooncol. 118, 435–460 (2014).

    Article  CAS  PubMed  Google Scholar 

  7. Chung, C., Metser, U. & Menard, C. Advances in magnetic resonance imaging and positron emission tomography imaging for grading and molecular characterization of glioma. Semin. Radiat. Oncol. 25, 164–171 (2015).

    Article  PubMed  Google Scholar 

  8. Herholz, K., Coope, D. & Jackson, A. Metabolic and molecular imaging in neuro-oncology. Lancet Neurol. 6, 711–724 (2007).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Nowosielski, M. et al. An intra-individual comparison of MRI, [18F]-FET and [18F]-FLT PET in patients with high-grade gliomas. PLoS ONE 9, e95830 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Sollini, M. et al. Diagnostic performances of [18F]fluorocholine positron emission tomography in brain tumors. Q. J. Nucl. Med. Mol. Imaging 1 Sep 2015 [epub ahead of print] (2015).

  12. Gerstner, E. et al. ACRIN 6684: assessment of tumor hypoxia in newly diagnosed GBM using 18F-FMISO PET and MRI. Clin. Cancer Res. 22, 5079–5086 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Kobayashi, H. et al. Usefulness of FMISO-PET for glioma analysis. Neurol. Med. Chir. (Tokyo) 53, 773–738 (2013).

    Article  Google Scholar 

  14. Rapp, M. et al. Diagnostic performance of 18F-FET PET in newly diagnosed cerebral lesions suggestive of glioma. J. Nucl. Med. 54, 229–235 (2013).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Rapp, M. et al. Clinical value of O-(2-[18F]-fluoroethyl)-L-tyrosine positron emission tomography in patients with low-grade glioma. Neurosurg. Focus 34, E3 (2013).

    Article  PubMed  Google Scholar 

  17. Singhal, T., Narayanan, T. K., Jain, V., Mukherjee, J. & Mantil, J. 11C-L-methionine positron emission tomography in the clinical management of cerebral gliomas. Mol. Imaging Biol. 10, 1–18 (2008).

    Article  PubMed  Google Scholar 

  18. Langen, K. J., Tonn, J. C., Weller, M. & Galldiks, N. Letter to the editor: “the role of imaging in the management of progressive glioblastoma. A systematic review and evidence-based clinical practice guideline” [J Neurooncol 2014; 118:435–460]. J. Neurooncol. 120, 665–666 (2014).

    Article  PubMed  Google Scholar 

  19. Swissmedic. Swiss Agency for Therapeutic Products. Swissmedic J. 13, 651 (2014).

  20. Okubo, S. et al. Correlation of l-methyl-11C-methionine (MET) uptake with l-type amino acid transporter 1 in human gliomas. J. Neurooncol. 99, 217–225 (2010).

    Article  CAS  PubMed  Google Scholar 

  21. Youland, R. S. et al. The role of LAT1 in 18F-DOPA uptake in malignant gliomas. J. Neurooncol. 111, 11–18 (2013).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  23. Becherer, A. et al. Brain tumour imaging with PET: a comparison between [18F]fluorodopa and [11C]methionine. Eur. J. Nucl. Med. Mol. Imaging 30, 1561–1567 (2003).

    Article  CAS  PubMed  Google Scholar 

  24. Grosu, A. L. et al. An interindividual comparison of O-(2-[18F]fluoroethyl)-L-tyrosine (FET)- and L-[methyl-11C]methionine (MET)-PET in patients with brain gliomas and metastases. Int. J. Radiat. Oncol. Biol. Phys. 81, 1049–1058 (2011).

    Article  CAS  PubMed  Google Scholar 

  25. Kratochwil, C. et al. Intra-individual comparison of 18F-FET and 18F-DOPA in PET imaging of recurrent brain tumors. Neuro Oncol. 16, 434–440 (2014).

    Article  CAS  PubMed  Google Scholar 

  26. Calcagni, M. L. et al. Dynamic O-(2-[18F]fluoroethyl)-L-tyrosine (F-18 FET) PET for glioma grading: assessment of individual probability of malignancy. Clin. Nucl. Med. 36, 841–847 (2011).

    Article  PubMed  Google Scholar 

  27. Pöpperl, G. et al. 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, 1933–1942 (2007).

    Article  PubMed  Google Scholar 

  28. Weckesser, M. et al. O-(2-[18F]fluorethyl)-L-tyrosine PET in the clinical evaluation of primary brain tumours. Eur. J. Nucl. Med. Mol. Imaging 32, 422–429 (2005).

    Article  CAS  PubMed  Google Scholar 

  29. Moulin-Romsee, G. et al. Non-invasive grading of brain tumours using dynamic amino acid PET imaging: does it work for 11C-methionine? Eur. J. Nucl. Med. Mol. Imaging 34, 2082–2087 (2007).

    Article  PubMed  Google Scholar 

  30. Cicone, F. et al. Volumetric assessment of recurrent or progressive gliomas: comparison between F-DOPA PET and perfusion-weighted MRI. Eur. J. Nucl. Med. Mol. Imaging 42, 905–915 (2015).

    Article  CAS  PubMed  Google Scholar 

  31. Galldiks, N. & Langen, K. J. Applications of PET imaging of neurological tumors with radiolabeled amino acids. Q. J. Nucl. Med. Mol. Imaging 59, 70–82 (2015).

    CAS  PubMed  Google Scholar 

  32. Dunet, V., Rossier, C., Buck, A., Stupp, R. & Prior, J. O. Performance of 18F-fluoro-ethyl-tyrosine (18F-FET) PET for the differential diagnosis of primary brain tumor: a systematic review and metaanalysis. J. Nucl. Med. 53, 207–214 (2012).

    Article  CAS  PubMed  Google Scholar 

  33. Pichler, R. et al. Is there a place for FET PET in the initial evaluation of brain lesions with unknown significance? Eur. J. Nucl. Med. Mol. Imaging 37, 1521–1528 (2010).

    Article  PubMed  Google Scholar 

  34. Floeth, F. W. et al. 18F-FET PET differentiation of ring-enhancing brain lesions. J. Nucl. Med. 47, 776–782 (2006).

    CAS  PubMed  Google Scholar 

  35. Salber, D. et al. Differential uptake of O-(2-18F-fluoroethyl)-L-tyrosine, l-3H-methionine, and 3H-deoxyglucose in brain abscesses. J. Nucl. Med. 48, 2056–2062 (2007).

    Article  CAS  PubMed  Google Scholar 

  36. Hutterer, M. et al. [18F]-fluoro-ethyl-L-tyrosine PET: a valuable diagnostic tool in neuro-oncology, but not all that glitters is glioma. Neuro Oncol. 15, 341–351 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Sala, Q. et al. 18F-DOPA, a clinically available PET tracer to study brain inflammation? Clin. Nucl. Med. 39, e283–e285 (2014).

    Article  PubMed  Google Scholar 

  38. Hutterer, M. et al. Epileptic activity increases cerebral amino acid transport assessed by 18F-fluoroethyl-L-tyrosine amino acid PET — a potential brain tumor mimic. J. Nucl. Med. 58, 129–137 (2017).

    Article  CAS  PubMed  Google Scholar 

  39. Smits, A. & Baumert, B. G. The clinical value of PET with amino acid tracers for gliomas WHO grade II. Int. J. Mol. Imaging 2011, 372509 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Dunet, V., Pomoni, A., Hottinger, A., Nicod-Lalonde, M. & Prior, J. O. Performance of 18F-FET versus 18F-FDG-PET for the diagnosis and grading of brain tumors: systematic review and meta-analysis. Neuro Oncol. 18, 426–434 (2016).

    Article  CAS  PubMed  Google Scholar 

  41. Jansen, E. P., Dewit, L. G., van Herk, M. & Bartelink, H. Target volumes in radiotherapy for high-grade malignant glioma of the brain. Radiother. Oncol. 56, 151–156 (2000).

    Article  CAS  PubMed  Google Scholar 

  42. Aronen, H. J. et al. Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. Radiology 191, 41–51 (1994).

    Article  CAS  PubMed  Google Scholar 

  43. Patel, P. et al. MR perfusion-weighted imaging in the evaluation of high-grade gliomas after treatment: a systematic review and meta-analysis. Neuro Oncol. 19, 118–127 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Wang, S. et al. Differentiating tumor progression from pseudoprogression in patients with glioblastomas using diffusion tensor imaging and dynamic susceptibility contrast MRI. AJNR Am. J. Neuroradiol. 37, 28–36 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Blasel, S. et al. Perfusion MRI in the evaluation of suspected glioblastoma recurrence. J. Neuroimaging 26, 116–123 (2016).

    Article  PubMed  Google Scholar 

  46. Stadlbauer, A. et al. 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, 721–729 (2008).

    Article  CAS  PubMed  Google Scholar 

  47. Choi, C. et al. 2-hydroxyglutarate detection by magnetic resonance spectroscopy in IDH-mutated patients with gliomas. Nat. Med. 18, 624–629 (2012). This article decribes noninvasive imaging of a genetic mutation in brain tumours by magnetic resonance spectroscopy, which is of high prognostic value.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Horská, A. & Barker, P. B. Imaging of brain tumors: MR spectroscopy and metabolic imaging. Neuroimaging Clin. N. Am. 20, 293–310 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Hattingen, E. et al. 1H MR spectroscopic imaging with short and long echo time to discriminate glycine in glial tumours. MAGMA 22, 33–41 (2009).

    Article  CAS  PubMed  Google Scholar 

  50. Lehnhardt, F. G., Bock, C., Rohn, G., Ernestus, R. I. & Hoehn, M. Metabolic differences between primary and recurrent human brain tumors: a 1H NMR spectroscopic investigation. NMR Biomed. 18, 371–382 (2005).

    Article  CAS  PubMed  Google Scholar 

  51. Svolos, P. et al. The role of diffusion and perfusion weighted imaging in the differential diagnosis of cerebral tumors: a review and future perspectives. Cancer Imaging 14, 20 (2014).

    PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  53. Pauleit, D. et al. Comparison of 18F-FET and 18F-FDG PET in brain tumors. Nucl. Med. Biol. 36, 779–787 (2009).

    Article  CAS  PubMed  Google Scholar 

  54. Pirotte, B. et al. Combined use of 18F-fluorodeoxyglucose and 11C-methionine in 45 positron emission tomography-guided stereotactic brain biopsies. J. Neurosurg. 101, 476–483 (2004).

    Article  CAS  PubMed  Google Scholar 

  55. Plotkin, M. et al. Comparison of F-18 FET-PET with F-18 FDG-PET for biopsy planning of non-contrast-enhancing gliomas. Eur. Radiol. 20, 2496–2502 (2010).

    Article  PubMed  Google Scholar 

  56. Galldiks, N. et al. Role of O-(2-18F-fluoroethyl)-L-tyrosine PET as a diagnostic tool for detection of malignant progression in patients with low-grade glioma. J. Nucl. Med. 54, 2046–2054 (2013).

    Article  CAS  PubMed  Google Scholar 

  57. Jansen, N. L. et al. Dynamic 18F-FET PET in newly diagnosed astrocytic low-grade glioma identifies high-risk patients. J. Nucl. Med. 55, 198–203 (2014).

    Article  CAS  PubMed  Google Scholar 

  58. Kunz, M. et al. Hot spots in dynamic 18FET-PET delineate malignant tumor parts within suspected WHO grade II gliomas. Neuro Oncol. 13, 307–316 (2011). This article describes how the analysis of time–activity curves of the uptake of the amino acid 2-18F-fluoroethyl)- L -tyrosine with PET can detect areas with high malignancy in heterogeneous gliomas.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Jansen, N. L. et al. Prognostic significance of dynamic 18F-FET PET in newly diagnosed astrocytic high-grade glioma. J. Nucl. Med. 56, 9–15 (2015).

    Article  CAS  PubMed  Google Scholar 

  60. Thon, N. et al. Dynamic 18F-FET PET in suspected WHO grade II gliomas defines distinct biological subgroups with different clinical courses. Int. J. Cancer 136, 2132–2145 (2015).

    Article  CAS  PubMed  Google Scholar 

  61. Unterrainer, M. et al. Serial 18F-FET PET imaging of primarily 18F-FET-negative glioma — does it make sense? J. Nucl. Med. 57, 1177–1182 (2016).

    Article  CAS  PubMed  Google Scholar 

  62. Wagner, M. et al. Heterogeneity in malignant gliomas: a magnetic resonance analysis of spatial distribution of metabolite changes and regional blood volume. J. Neurooncol. 103, 663–672 (2011).

    Article  PubMed  Google Scholar 

  63. Filss, C. P. et al. Comparison of 18F-FET PET and perfusion-weighted MR imaging: a PET/MR imaging hybrid study in patients with brain tumors. J. Nucl. Med. 55, 540–545 (2014). This study demonstrates the differences in brain tumour imaging with amino acid PET and perfusion-weighted MRI.

    Article  CAS  PubMed  Google Scholar 

  64. Widhalm, G. et al. Value of H-1-magnetic resonance spectroscopy chemical shift imaging for detection of anaplastic foci in diffusely infiltrating gliomas with non-significant contrast-enhancement. J. Neurol. Neurosurg. Psychiatry 82, 512–520 (2011).

    Article  PubMed  Google Scholar 

  65. Price, S. J. et al. Correlation of MR relative cerebral blood volume measurements with cellular density and proliferation in high-grade gliomas: an image-guided biopsy study. AJNR Am. J. Neuroradiol. 32, 501–506 (2011). This study analysis the relationship between relative cerebral blood volume mapping and tumour extent of high-grade gliomas.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Blasel, S. et al. Stripe-like increase of rCBV beyond the visible border of glioblastomas: site of tumor infiltration growing after neurosurgery. J. Neurooncol. 103, 575–584 (2011).

    Article  PubMed  Google Scholar 

  67. Sadeghi, N. et al. Apparent diffusion coefficient and cerebral blood volume in brain gliomas: relation to tumor cell density and tumor microvessel density based on stereotactic biopsies. AJNR Am. J. Neuroradiol. 29, 476–482 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Stadlbauer, A., Buchfelder, M., Doelken, M. T., Hammen, T. & Ganslandt, O. Magnetic resonance spectroscopic imaging for visualization of the infiltration zone of glioma. Cent. Eur. Neurosurg. 72, 63–69 (2011).

    Article  CAS  PubMed  Google Scholar 

  69. Kracht, L. W. et al. Delineation of brain tumor extent with [11C]l-methionine positron emission tomography: local comparison with stereotactic histopathology. Clin. Cancer Res. 10, 7163–7170 (2004).

    Article  CAS  PubMed  Google Scholar 

  70. Lopez, W. O. et al. Correlation of 18F-fluoroethyl tyrosine positron-emission tomography uptake values and histomorphological findings by stereotactic serial biopsy in newly diagnosed brain tumors using a refined software tool. Onco Targets Ther. 8, 3803–3815 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Mosskin, M. et al. Positron emission tomography compared with magnetic resonance imaging and computed tomography in supratentorial gliomas using multiple stereotactic biopsies as reference. Acta Radiol. 30, 225–232 (1989).

    Article  CAS  PubMed  Google Scholar 

  72. Pauleit, D. et al. O-(2-[18F]fluoroethyl)-L-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain 128, 678–687 (2005). This study demonstrated how imaging of tumour extent of gliomas is improved by amino acid PET compared with conventional MRI.

    Article  PubMed  Google Scholar 

  73. Henriksen, O. M. et al. Simultaneous evaluation of brain tumour metabolism, structure and blood volume using [18F]-fluoroethyltyrosine (FET) PET/MRI: feasibility, agreement and initial experience. Eur. J. Nucl. Med. Mol. Imaging 43, 103–112 (2016).

    Article  CAS  PubMed  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  75. Rose, S. et al. Correlation of MRI-derived apparent diffusion coefficients in newly diagnosed gliomas with [18F]-fluoro-L-dopa PET: what are we really measuring with minimum ADC? AJNR Am. J. Neuroradiol. 34, 758–764 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Chen, W. Clinical applications of PET in brain tumors. J. Nucl. Med. 48, 1468–1481 (2007).

    Article  PubMed  Google Scholar 

  77. Kim, S. et al. 11C-methionine PET as a prognostic marker in patients with glioma: comparison with 18F-FDG PET. Eur. J. Nucl. Med. Mol. Imaging 32, 52–59 (2005).

    Article  CAS  PubMed  Google Scholar 

  78. Dunet, V. & Prior, J. O. Response to: performance of 18F-FET-PET versus 18F-FDG-PET for the diagnosis and grading of brain tumors: inherent bias in meta-analysis not revealed by quality metrics. Neuro Oncol. 18, 1029–1030 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  79. Manabe, O. et al. Oligodendroglial component complicates the prediction of tumour grading with metabolic imaging. Eur. J. Nucl. Med. Mol. Imaging 42, 896–904 (2015).

    Article  CAS  PubMed  Google Scholar 

  80. Pöpperl, G. et al. Analysis of 18F-FET PET for grading of recurrent gliomas: is evaluation of uptake kinetics superior to standard methods? J. Nucl. Med. 47, 393–403 (2006).

    PubMed  Google Scholar 

  81. Albert, N. L. et al. Early static 18F-FET-PET scans have a higher accuracy for glioma grading than the standard 20–40 min scans. Eur. J. Nucl. Med. Mol. Imaging 43, 1105–1114 (2016).

    Article  PubMed  Google Scholar 

  82. Law, M. et al. 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, 1989–1998 (2003).

    PubMed  PubMed Central  Google Scholar 

  83. Arvinda, H. R. et al. Glioma grading: sensitivity, specificity, positive and negative predictive values of diffusion and perfusion imaging. J. Neurooncol. 94, 87–96 (2009).

    Article  CAS  PubMed  Google Scholar 

  84. Hattingen, E. et al. 1H MRSI and progression-free survival in patients with WHO grades II and III gliomas. Neurol. Res. 32, 593–602 (2010).

    Article  PubMed  Google Scholar 

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

    Article  PubMed  Google Scholar 

  86. Toyooka, M. et al. Tissue characterization of glioma by proton magnetic resonance spectroscopy and perfusion-weighted magnetic resonance imaging: glioma grading and histological correlation. Clin. Imaging 32, 251–258 (2008).

    Article  PubMed  Google Scholar 

  87. Hilario, A. et al. The added value of apparent diffusion coefficient to cerebral blood volume in the preoperative grading of diffuse gliomas. AJNR Am. J. Neuroradiol. 33, 701–707 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Fayed, N., Davila, J., Medrano, J. & Olmos, S. Malignancy assessment of brain tumours with magnetic resonance spectroscopy and dynamic susceptibility contrast MRI. Eur. J. Radiol. 67, 427–433 (2008).

    Article  PubMed  Google Scholar 

  89. Leclerc, X., Huisman, T. A. & Sorensen, A. G. The potential of proton magnetic resonance spectroscopy (1H-MRS) in the diagnosis and management of patients with brain tumors. Curr. Opin. Oncol. 14, 292–298 (2002).

    Article  PubMed  Google Scholar 

  90. Kim, J. H. et al. 3T 1H-MR spectroscopy in grading of cerebral gliomas: comparison of short and intermediate echo time sequences. AJNR Am. J. Neuroradiol. 27, 1412–1418 (2006).

    PubMed  PubMed Central  Google Scholar 

  91. Castillo, M., Smith, J. K., Kwock, L. & Wilber, K. Apparent diffusion coefficients in the evaluation of high-grade cerebral gliomas. AJNR Am. J. Neuroradiol. 22, 60–64 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Lev, M. H. et al. Glial tumor grading and outcome prediction using dynamic spin-echo MR susceptibility mapping compared with conventional contrast-enhanced MR: confounding effect of elevated rCBV of oligodendrogliomas [corrected]. AJNR Am. J. Neuroradiol. 25, 214–221 (2004).

    PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  94. Senft, C. et al. Diagnostic value of proton magnetic resonance spectroscopy in the noninvasive grading of solid gliomas: comparison of maximum and mean choline values. Neurosurgery 65, 908–913 (2009).

    Article  PubMed  Google Scholar 

  95. Guzman-De-Villoria, J. A., Mateos-Perez, J. M., Fernandez-Garcia, P., Castro, E. & Desco, M. Added value of advanced over conventional magnetic resonance imaging in grading gliomas and other primary brain tumors. Cancer Imaging 14, 35 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  96. Usinskiene, J. et al. Optimal differentiation of high- and low-grade glioma and metastasis: a meta-analysis of perfusion, diffusion, and spectroscopy metrics. Neuroradiology 58, 339–350 (2016). This meta-analysis gives an overview of the role of advanced MRI methods for tumour grading.

    Article  PubMed  Google Scholar 

  97. Galldiks, N. et al. Volumetry of [11C]-methionine positron emission tomographic uptake as a prognostic marker before treatment of patients with malignant glioma. Mol. Imaging 11, 516–527 (2012).

    CAS  PubMed  Google Scholar 

  98. Piroth, M. D. et al. Prognostic value of early [18F]fluoroethyltyrosine positron emission tomography after radiochemotherapy in glioblastoma multiforme. Int. J. Radiat. Oncol. Biol. Phys. 80, 176–184 (2011).

    Article  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  100. Villani, V. et al. The role of PET [18F]FDOPA in evaluating low-grade glioma. Anticancer Res. 35, 5117–5122 (2015).

    CAS  PubMed  Google Scholar 

  101. Floeth, F. W. et al. Prognostic value of O-(2-18F-fluoroethyl)-L-tyrosine PET and MRI in low-grade glioma. J. Nucl. Med. 48, 519–527 (2007).

    Article  CAS  PubMed  Google Scholar 

  102. Jansen, N. L. et al. MRI-suspected low-grade glioma: is there a need to perform dynamic FET PET? Eur. J. Nucl. Med. Mol. Imaging 39, 1021–1029 (2012).

    Article  CAS  PubMed  Google Scholar 

  103. Hirai, T. et al. Prognostic value of perfusion MR imaging of high-grade astrocytomas: long-term follow-up study. AJNR Am. J. Neuroradiol. 29, 1505–1510 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Jain, R. et al. Genomic mapping and survival prediction in glioblastoma: molecular subclassification strengthened by hemodynamic imaging biomarkers. Radiology 267, 212–220 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  105. Shiroishi, M. S., Boxerman, J. L. & Pope, W. B. Physiologic MRI for assessment of response to therapy and prognosis in glioblastoma. Neuro Oncol. 18, 467–478 (2016).

    Article  CAS  PubMed  Google Scholar 

  106. Law, M. et al. Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology 247, 490–498 (2008).

    Article  PubMed  Google Scholar 

  107. Nakamura, H., Murakami, R., Hirai, T., Kitajima, M. & Yamashita, Y. Can MRI-derived factors predict the survival in glioblastoma patients treated with postoperative chemoradiation therapy? Acta Radiol. 54, 214–220 (2013).

    Article  PubMed  Google Scholar 

  108. Saraswathy, S. et al. Evaluation of MR markers that predict survival in patients with newly diagnosed GBM prior to adjuvant therapy. J. Neurooncol. 91, 69–81 (2009).

    Article  PubMed  Google Scholar 

  109. Ellingson, B. M. et al. Pretreatment ADC histogram analysis is a predictive imaging biomarker for bevacizumab treatment but not chemotherapy in recurrent glioblastoma. AJNR Am. J. Neuroradiol. 35, 673–679 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Brandsma, D. & van den Bent, M. J. Pseudoprogression and pseudoresponse in the treatment of gliomas. Curr. Opin. Neurol. 22, 633–638 (2009).

    Article  PubMed  Google Scholar 

  111. Wen, P. Y. et al. Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J. Clin. Oncol. 28, 1963–1972 (2010). This study describes the limitations of conventional MRI in response assessment of high-grade gliomas.

    Article  PubMed  Google Scholar 

  112. Kebir, S. et al. Late pseudoprogression in glioblastoma: diagnostic value of dynamic O-(2-[18F]fluoroethyl)-L-tyrosine PET. Clin. Cancer Res. 22, 2190–2196 (2016).

    Article  CAS  PubMed  Google Scholar 

  113. Galldiks, N. et al. Diagnosis of pseudoprogression in patients with glioblastoma using O-(2-[18F]fluoroethyl)-L-tyrosine PET. Eur. J. Nucl. Med. Mol. Imaging 42, 685–695 (2015).

    Article  CAS  PubMed  Google Scholar 

  114. Karunanithi, S. et al. 18F-FDOPA PET/CT for detection of recurrence in patients with glioma: prospective comparison with 18F-FDG PET/CT. Eur. J. Nucl. Med. Mol. Imaging 40, 1025–1035 (2013).

    Article  CAS  PubMed  Google Scholar 

  115. Rachinger, W. et al. Positron emission tomography with O-(2-[18F]fluoroethyl)-L-tyrosine versus magnetic resonance imaging in the diagnosis of recurrent gliomas. Neurosurgery 57, 505–511 (2005).

    Article  PubMed  Google Scholar 

  116. Minamimoto, R. et al. Differentiation of brain tumor recurrence from post-radiotherapy necrosis with 11C-methionine PET: visual assessment versus quantitative assessment. PLoS ONE 10, e0132515 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Nihashi, T., Dahabreh, I. J. & Terasawa, T. Diagnostic accuracy of PET for recurrent glioma diagnosis: a meta-analysis. AJNR Am. J. Neuroradiol. 34, 944–950 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Ceccon, G. et al. Dynamic O-(2-18F-fluoroethyl)-L-tyrosine positron emission tomography differentiates brain metastasis recurrence from radiation injury after radiotherapy. Neuro Oncol. 19, 281–288 (2016). This article reports on the diagnostic accuracy of O -(2-18F-fluoroethyl)- L -tyrosine PET for the differentiation of disease relapse from radiation injury in patients with brain metastasis.

    PubMed Central  Google Scholar 

  119. Galldiks, N. et al. Role of O-(2-18F-fluoroethyl)-L-tyrosine PET for differentiation of local recurrent brain metastasis from radiation necrosis. J. Nucl. Med. 53, 1367–1374 (2012).

    Article  CAS  PubMed  Google Scholar 

  120. Lizarraga, K. J. et al. 18F-FDOPA PET for differentiating recurrent or progressive brain metastatic tumors from late or delayed radiation injury after radiation treatment. J. Nucl. Med. 55, 30–36 (2014).

    Article  CAS  PubMed  Google Scholar 

  121. Terakawa, Y. et al. Diagnostic accuracy of 11C-methionine PET for differentiation of recurrent brain tumors from radiation necrosis after radiotherapy. J. Nucl. Med. 49, 694–699 (2008).

    Article  PubMed  Google Scholar 

  122. Tsuyuguchi, N. et al. Methionine positron emission tomography of recurrent metastatic brain tumor and radiation necrosis after stereotactic radiosurgery: is a differential diagnosis possible? J. Neurosurg. 98, 1056–1064 (2003).

    Article  PubMed  Google Scholar 

  123. Hodi, F. S. et al. Evaluation of immune-related response criteria and RECIST v1.1 in patients with advanced melanoma treated with pembrolizumab. J. Clin. Oncol. 34, 1510–1517 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Kebir, S. et al. Dynamic O-(2-[18F]fluoroethyl)-L-tyrosine PET imaging for the detection of checkpoint inhibitor-related pseudoprogression in melanoma brain metastases. Neuro Oncol. 18, 1462–1464 (2016). This report shows the potential of amino acid PET to detect checkpoint inhibitor-related pseudoprogression in brain metastases.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Choi, Y. J., Kim, H. S., Jahng, G. H., Kim, S. J. & Suh, D. C. Pseudoprogression in patients with glioblastoma: added value of arterial spin labeling to dynamic susceptibility contrast perfusion MR imaging. Acta Radiol. 54, 448–454 (2013).

    Article  PubMed  Google Scholar 

  126. Hu, L. S. et al. Relative cerebral blood volume values to differentiate high-grade glioma recurrence from posttreatment radiation effect: direct correlation between image-guided tissue histopathology and localized dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging measurements. AJNR Am. J. Neuroradiol. 30, 552–558 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Kreis, R. Issues of spectral quality in clinical 1H-magnetic resonance spectroscopy and a gallery of artifacts. NMR Biomed. 17, 361–381 (2004).

    Article  CAS  PubMed  Google Scholar 

  128. Hygino da Cruz, L. C. Jr, Rodriguez, I., Domingues, R. C., Gasparetto, E. L. & Sorensen, A. G. Pseudoprogression and pseudoresponse: imaging challenges in the assessment of posttreatment glioma. AJNR Am. J. Neuroradiol. 32, 1978–1985 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  130. Galldiks, N. et al. Assessment of treatment response in patients with glioblastoma using [18F]fluoroethyl-L-tyrosine PET in comparison to MRI. J. Nucl. Med. 53, 1048–1057 (2012).

    Article  CAS  PubMed  Google Scholar 

  131. Galldiks, N. et al. Use of 11C-methionine PET to monitor the effects of temozolomide chemotherapy in malignant gliomas. Eur. J. Nucl. Med. Mol. Imaging 33, 516–524 (2006).

    Article  CAS  PubMed  Google Scholar 

  132. Galldiks, N. et al. Patient-tailored, imaging-guided, long-term temozolomide chemotherapy in patients with glioblastoma. Mol. Imaging 9, 40–46 (2010).

    Article  CAS  PubMed  Google Scholar 

  133. Pöpperl, G. et al. O-(2-[18F]fluoroethyl)-L-tyrosine PET for monitoring the effects of convection-enhanced delivery of paclitaxel in patients with recurrent glioblastoma. Eur. J. Nucl. Med. Mol. Imaging 32, 1018–1025 (2005).

    Article  CAS  PubMed  Google Scholar 

  134. Popperl, G. et al. Serial O-(2-[18F]fluoroethyl)-L-tyrosine PET for monitoring the effects of intracavitary radioimmunotherapy in patients with malignant glioma. Eur. J. Nucl. Med. Mol. Imaging 33, 792–800 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Galldiks, N. et al. Earlier diagnosis of progressive disease during bevacizumab treatment using O-(2-18F-fluorethyl)-L-tyrosine positron emission tomography in comparison with magnetic resonance imaging. Mol. Imaging 12, 273–276 (2013).

    Article  PubMed  Google Scholar 

  136. Hutterer, M. et al. O-(2-18F-fluoroethyl)-L-tyrosine PET predicts failure of antiangiogenic treatment in patients with recurrent high-grade glioma. J. Nucl. Med. 52, 856–864 (2011).

    Article  CAS  PubMed  Google Scholar 

  137. Schwarzenberg, J. et al. Treatment response evaluation using 18F-FDOPA PET in patients with recurrent malignant glioma on bevacizumab therapy. Clin. Cancer Res. 20, 3550–3559 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Moffat, B. A. et al. Functional diffusion map: a noninvasive MRI biomarker for early stratification of clinical brain tumor response. Proc. Natl Acad. Sci. USA 102, 5524–5529 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Pope, W. B. et al. Apparent diffusion coefficient histogram analysis stratifies progression-free and overall survival in patients with recurrent GBM treated with bevacizumab: a multi-center study. J. Neurooncol. 108, 491–498 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  140. Rahman, R. et al. Histogram analysis of apparent diffusion coefficient within enhancing and nonenhancing tumor volumes in recurrent glioblastoma patients treated with bevacizumab. J. Neurooncol. 119, 149–158 (2014).

    Article  CAS  PubMed  Google Scholar 

  141. Schmainda, K. M. et al. Dynamic-susceptibility contrast agent MRI measures of relative cerebral blood volume predict response to bevacizumab in recurrent high-grade glioma. Neuro Oncol. 16, 880–888 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  142. Gizewski, E. R., Monninghoff, C. & Forsting, M. Perspectives of ultra-high-field MRI in neuroradiology. Clin. Neuroradiol. 25 (Suppl. 2), 267–273 (2015).

    Article  PubMed  Google Scholar 

  143. Ren, J., Sherry, A. D. & Malloy, C. R. 31P-MRS of healthy human brain: ATP synthesis, metabolite concentrations, pH, and T1 relaxation times. NMR Biomed. 28, 1455–1462 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Ward, K. M., Aletras, A. H. & Balaban, R. S. A new class of contrast agents for MRI based on proton chemical exchange dependent saturation transfer (CEST). J. Magn. Reson. 143, 79–87 (2000).

    Article  CAS  PubMed  Google Scholar 

  145. Walker-Samuel, S. et al. In vivo imaging of glucose uptake and metabolism in tumors. Nat. Med. 19, 1067–1072 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Sagiyama, K. et al. In vivo chemical exchange saturation transfer imaging allows early detection of a therapeutic response in glioblastoma. Proc. Natl Acad. Sci. USA 111, 4542–4547 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Pellegatta, S. et al. Effective immuno-targeting of the IDH1 mutation R132H in a murine model of intracranial glioma. Acta Neuropathol. Commun. 3, 4 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Andronesi, O. C. et al. Treatment response assessment in IDH-mutant glioma patients by noninvasive 3D functional spectroscopic mapping of 2-hydroxyglutarate. Clin. Cancer Res. 22, 1632–1641 (2016).

    Article  CAS  PubMed  Google Scholar 

  149. Winkeler, A. et al. The translocator protein ligand [18F]DPA-714 images glioma and activated microglia in vivo. Eur. J. Nucl. Med. Mol. Imaging 39, 811–823 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  150. Roncaroli, F., Su, Z., Herholz, K., Gerhard, A. & Turkheimer, F. E. TSPO expression in brain tumours: is TSPO a target for brain tumour imaging? Clin. Transl Imaging 4, 145–156 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  151. Su, Z. et al. The 18-kDa mitochondrial translocator protein in human gliomas: an 11C-(R)PK11195 PET imaging and neuropathology study. J. Nucl. Med. 56, 512–517 (2015).

    Article  CAS  PubMed  Google Scholar 

  152. Jensen, P. et al. TSPO imaging in glioblastoma multiforme: a direct comparison between 123I-CLINDE SPECT, 18F-FET PET, and gadolinium-enhanced MR imaging. J. Nucl. Med. 56, 1386–1390 (2015).

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

All authors researched data for the article, provided substantial contributions to discussion of content, wrote the article and reviewed and edited the manuscript before submission. K.-J.L. and N.G. contributed equally to the article.

Corresponding author

Correspondence to Karl-Josef Langen.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

PowerPoint slides

Glossary

Adjuvant chemotherapy

Administration of chemotherapy after surgery or radiation treatment for cancer to target remaining malignant cells.

T1-weighted and T2-weighted sequences

Standard morphological images weighted by the longitudinal (T1) and transverse (T2) relaxation times of the protons.

Perfusion-weighted imaging

Image acquisition techniques that highlight fluids moving through arteries, veins and capillaries.

Diffusion-weighted imaging

Imaging technique designed to weight the MRI signal by the amount of diffusion (random thermal motion) of water molecules.

Fluid-attenuated inversion recovery

MRI technique that uses inversion recovery, in which the signal from water is reduced by timing the delay of the inversion pulse.

Cerebral blood flow

Flow of capillary blood per unit mass through the brain tissue (units: ml/min/100 g).

Relative cerebral blood volume

The volume of blood in a brain lesion in relation to the normal brain tissue.

Mean transit time

The average time, in seconds, that red blood cells spend within a given volume of capillary circulation.

Single voxel spectroscopy

A magnetic resonance spectroscopy technique used to assess the concentration of metabolites in a defined region of interest.

Brownian motion

Continuous random movement of particles suspended in a fluid, which arises from collisions with the fluid molecules.

Fractional anisotropy

Fractional anisotropy (FA) is a scalar parameter (0 ≤ FA ≤1) used to quantify the degree of anisotropy of the diffusion process.

Local maxima

Area with maximum signal of different parameters in the tumour area

Hotspots

Area with locally increased signal of different parameters in the corresponding image.

Pseudoprogression

A phenomenon whereby tumours initially 'grow' on MRI due to immune infiltrate, but then decrease in size.

Convection-enhanced delivery

A therapeutic strategy to facilitate delivery of pharmaceuticals. Placement of small-diameter catheters directly into the brain tumour is followed by infusion of therapeutics.

Chemical exchange saturation transfer

An MRI technique in which exogenous or endogenous compounds containing exchangeable molecules are selectively saturated and, after transfer of this saturation, detected indirectly through the water signal with enhanced sensitivity.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Langen, KJ., Galldiks, N., Hattingen, E. et al. Advances in neuro-oncology imaging. Nat Rev Neurol 13, 279–289 (2017). https://doi.org/10.1038/nrneurol.2017.44

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrneurol.2017.44

This article is cited by

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer