Quantitative volumetric analysis of gliomas with sequential MRI and 11C-methionine PET assessment: patterns of integration in therapy planning

  • Javier ArbizuEmail author
  • S. Tejada
  • J. M. Marti-Climent
  • R. Diez-Valle
  • E. Prieto
  • G. Quincoces
  • C. Vigil
  • M. A. Idoate
  • J. L. Zubieta
  • I. Peñuelas
  • J. A. Richter
Original Article



The aim of the study was to evaluate the volumetric integration patterns of standard MRI and 11C-methionine positron emission tomography (PET) images in the surgery planning of gliomas and their relationship to the histological grade.


We studied 23 patients with suspected or previously treated glioma who underwent preoperative 11C-methionine PET because MRI was imprecise in defining the surgical target contour. Images were transferred to the treatment planning system, coregistered and fused (BrainLAB). Tumour delineation was performed by 11C-methionine PET thresholding (vPET) and manual segmentation over MRI (vMRI). A 3-D volumetric study was conducted to evaluate the contribution of each modality to tumour target volume. All cases were surgically treated and histological classification was performed according to WHO grades. Additionally, several biopsy samples were taken according to the results derived either from PET or from MRI and analysed separately.


Fifteen patients had high-grade tumours [ten glioblastoma multiforme (GBM) and five anaplastic), whereas eight patients had low-grade tumours. Biopsies from areas with high 11C-methionine uptake without correspondence in MRI showed tumour proliferation, including infiltrative zones, distinguishing them from dysplasia and radionecrosis. Two main PET/MRI integration patterns emerged after analysis of volumetric data: pattern vMRI-in-vPET (11/23) and pattern vPET-in-vMRI (9/23). Besides, a possible third pattern with differences in both directions (vMRI-diff-vPET) could also be observed (3/23). There was a statistically significant association between the tumour classification and integration patterns described above (p < 0.001, κ = 0.72). GBM was associated with pattern vMRI-in-vPET (9/10), low-grade with pattern vPET-in-vMRI (7/8) and anaplastic with pattern vMRI-diff-vPET (3/5).


The metabolically active tumour volume observed in 11C-methionine PET differs from the volume of MRI by showing areas of infiltrative tumour and distinguishing from non-tumour lesions. Differences in 11C-methionine PET/MRI integration patterns can be assigned to tumour grades according to the WHO classification. This finding may improve tumour delineation and therapy planning for gliomas.


11C-Methionine PET MRI Glioma Therapy planning Volumetry 



This work was partially supported by the Research Foundation of the University of Navarra (PIUNA 2010-04) and the Convocatoria de infraestructuras del Fondo de Investigaciones Sanitarias, ISCIII, MSC (IF 08/360)

Conflicts of interest


Supplementary material

259_2011_2049_MOESM1_ESM.doc (22 kb)
ESM 1 (DOC 34.0 kb)


  1. 1.
    Louis DN, Ohgaki H, Wiestler OD, Cavenee WK. WHO classification of tumours of the central nervous system. Lyon: IARC; 2007.Google Scholar
  2. 2.
    Salzman KL. Astrocytic tumors, infiltrating neoplasm. In: Osborn AG, Salzman KL, Barkovich AJ, editors. Diagnostic imaging: brain. 2nd ed. Salt Lake City: Amirsys; 2010. p. 14–7.Google Scholar
  3. 3.
    Lacroix M, Abi-Said D, Fourney DR, Gokaslan ZL, Shi W, DeMonte F, et al. A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival. J Neurosurg 2001;95:190–8.PubMedGoogle Scholar
  4. 4.
    Smith JS, Chang EF, Lamborn KR, Chang SM, Prados MD, Cha S, et al. Role of extent of resection in the long-term outcome of low-grade hemispheric gliomas. J Clin Oncol 2008;26:1338–45.PubMedCrossRefGoogle Scholar
  5. 5.
    Stupp R, Tonn JC, Brada M, Pentheroudakis G, ESMO Guidelines Working Group. High-grade malignant glioma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol 2010;21:v190–3.PubMedCrossRefGoogle Scholar
  6. 6.
    Soffietti R, Baumert BG, Bello L, von Deimling A, Duffau H, Frénay M, et al. Guidelines on management of low-grade gliomas: report of an EFNS-EANO Task Force. Eur J Neurol 2010;17:1124–33.PubMedCrossRefGoogle Scholar
  7. 7.
    Sanai N, Berger MS. Glioma extent of resection and its impact on patient outcome. Neurosurgery 2008;62:753–64. discussion 264-6.PubMedCrossRefGoogle Scholar
  8. 8.
    Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJ, et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med 2005;352:987–96.PubMedCrossRefGoogle Scholar
  9. 9.
    Kelly PJ, Daumas-Duport C, Kispert DB, Kall BA, Scheithauer BW, Illig JJ. Imaging-based stereotaxic serial biopsies in untreated intracranial glial neoplasms. J Neurosurg 1987;66:865–74.PubMedCrossRefGoogle Scholar
  10. 10.
    Watanabe M, Tanaka R, Takeda N. Magnetic resonance imaging and histopathology of cerebral gliomas. Neuroradiology 1992;34:463–9.PubMedCrossRefGoogle Scholar
  11. 11.
    Grosu AL, Weber WA, Riedel E, Jeremic B, Nieder C, Franz M, et al. L-(methyl-11C) methionine positron emission tomography for target delineation in resected high-grade gliomas before radiotherapy. Int J Radiat Oncol Biol Phys 2005;63:64–74.PubMedCrossRefGoogle Scholar
  12. 12.
    Plotkin M, Blechschmidt C, Auf G, Nyuyki F, Geworski L, Denecke T, et al. Comparison of F-18 FET-PET with F-18 FDG-PET for biopsy planning of non-contrast-enhancing gliomas. Eur Radiol 2010;20:2496–502.PubMedCrossRefGoogle Scholar
  13. 13.
    Jacobs AH, Li H, Winkeler A, Hilker R, Knoess C, Rüger A, et al. PET-based molecular imaging in neuroscience. Eur J Nucl Med Mol Imaging 2003;30:1051–65.PubMedCrossRefGoogle Scholar
  14. 14.
    Chung JK, Kim YK, Kim SK, Lee YJ, Paek S, Yeo JS, et al. Usefulness of 11C-methionine PET in the evaluation of brain lesions that are hypo- or isometabolic on 18F-FDG PET. Eur J Nucl Med Mol Imaging 2002;29:176–82.PubMedCrossRefGoogle Scholar
  15. 15.
    Van Laere K, Ceyssens S, Van Calenbergh F, de Groot T, Menten J, Flamen P, et al. Direct comparison of 18F-FDG and 11C-methionine PET in suspected recurrence of glioma: sensitivity, inter-observer variability and prognostic value. Eur J Nucl Med Mol Imaging 2005;32:39–51.PubMedCrossRefGoogle Scholar
  16. 16.
    Prieto E, Martí-Climent JM, Domínguez-Prado I, Garrastachu P, Díez-Valle R, Tejada S, et al. Voxel-based analysis of dual-time-point FDG PET images for brain tumor identification and delineation. J Nucl Med 2011;52:865–72.PubMedCrossRefGoogle Scholar
  17. 17.
    Kracht LW, Miletic H, Busch S, Jacobs AH, Voges J, Hoevels M, et al. Delineation of brain tumor extent with [11C]L-methionine positron emission tomography: local comparison with stereotactic histopathology. Clin Cancer Res 2004;10:7163–70.PubMedCrossRefGoogle Scholar
  18. 18.
    Miwa K, Shinoda J, Yano H, Okumura A, Iwama T, Nakashima T, et al. Discrepancy between lesion distributions on methionine PET and MR images in patients with glioblastoma multiforme: insight from a PET and MR fusion image study. J Neurol Neurosurg Psychiatry 2004;75:1457–62.PubMedCrossRefGoogle Scholar
  19. 19.
    Smits A, Baumert BG. The clinical value of PET with amino acid tracers for gliomas WHO grade II. Int J Mol Imaging 2011;2011:372509.PubMedGoogle Scholar
  20. 20.
    Mosskin M, Ericson K, Hindmarsh T, von Holst H, Collins VP, Bergström 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 1989;30:225–32.PubMedCrossRefGoogle Scholar
  21. 21.
    Pirotte B, Goldman S, Dewitte O, Massager N, Wikler D, Lefranc F, et al. Integrated positron emission tomography and magnetic resonance imaging-guided resection of brain tumors: a report of 103 consecutive procedures. J Neurosurg 2006;104:238–53.PubMedCrossRefGoogle Scholar
  22. 22.
    Roessler K, Gatterbauer B, Becherer A, Paul M, Kletter K, Prayer D, et al. Surgical target selection in cerebral glioma surgery: linking methionine (MET) PET image fusion and neuronavigation. Minim Invasive Neurosurg 2007;50:273–80.PubMedCrossRefGoogle Scholar
  23. 23.
    Tanaka Y, Nariai T, Momose T, Aoyagi M, Maehara T, Tomori T, et al. Glioma surgery using a multimodal navigation system with integrated metabolic images. J Neurosurg 2009;110:163–72.PubMedCrossRefGoogle Scholar
  24. 24.
    Levivier M, Massager N, Wikler D, Lorenzoni J, Ruiz S, Devriendt D, et al. Use of stereotactic PET images in dosimetry planning of radiosurgery for brain tumors: clinical experience and proposed classification. J Nucl Med 2004;45:1146–54.PubMedGoogle Scholar
  25. 25.
    Pirotte BJ, Levivier M, Goldman S, Massager N, Wikler D, Dewitte O, et al. Positron emission tomography-guided volumetric resection of supratentorial high-grade gliomas: a survival analysis in 66 consecutive patients. Neurosurgery 2009;64:471–81.PubMedCrossRefGoogle Scholar
  26. 26.
    Quincoces G, Peñuelas I, Valero M, Serra P, Collantes M, Martí-Climent J, et al. Simple automated system for simultaneous production of 11C-labeled tracers by solid supported methylation. Appl Radiat Isot 2006;64:808–11.PubMedCrossRefGoogle Scholar
  27. 27.
    Grosu AL, Lachner R, Wiedenmann N, Stärk S, Thamm R, Kneschaurek P, et al. Validation of a method for automatic image fusion (BrainLAB System) of CT data and 11C-methionine-PET data for stereotactic radiotherapy using a LINAC: first clinical experience. Int J Radiat Oncol Biol Phys 2003;56:1450–63.PubMedCrossRefGoogle Scholar
  28. 28.
    Abramson JH. WINPEPI (PEPI-for-Windows): computer programs for epidemiologists. Epidemiol Perspect Innov 2004;1:6.PubMedCrossRefGoogle Scholar
  29. 29.
    Grosu AL, Nestle U, Weber WA. How to use functional imaging information for radiotherapy planning. Eur J Cancer 2009;45 Suppl 1:461–3.PubMedCrossRefGoogle Scholar
  30. 30.
    Pirotte B, Goldman S, Massager N, David P, Wikler D, Vandesteene A, et al. Comparison of 18F-FDG and 11C-methionine for PET-guided stereotactic brain biopsy of gliomas. J Nucl Med 2004;45:1293–8.PubMedGoogle Scholar
  31. 31.
    Galldiks N, Ullrich R, Schroeter M, Fink GR, Jacobs AH, Kracht LW. Volumetry of [(11)C]-methionine PET uptake and MRI contrast enhancement in patients with recurrent glioblastoma multiforme. Eur J Nucl Med Mol Imaging 2010;37:84–92.PubMedCrossRefGoogle Scholar
  32. 32.
    Herholz K, Hölzer T, Bauer B, Schröder R, Voges J, Ernestus RI, et al. 11C-methionine PET for differential diagnosis of low-grade gliomas. Neurology 1998;50:1316–22.PubMedGoogle Scholar
  33. 33.
    Kinoshita M, Hashimoto N, Goto T, Yanagisawa T, Okita Y, Kagawa N, et al. Use of fractional anisotropy for determination of the cut-off value in 11C-methionine positron emission tomography for glioma. NeuroImage 2009;45:312–8.PubMedCrossRefGoogle Scholar
  34. 34.
    Singhal T, Narayanan TK, Jain V, Mukherjee J, Mantil J. 11C-L-methionine positron emission tomography in the clinical management of cerebral gliomas. Mol Imaging Biol 2008;10:1–18.PubMedCrossRefGoogle Scholar
  35. 35.
    Nuutinen J, Sonninen P, Lehikoinen P, Sutinen E, Valavaara R, Eronen E, et al. Radiotherapy treatment planning and long-term follow-up with [(11)C]methionine PET in patients with low-grade astrocytoma. Int J Radiat Oncol Biol Phys 2000;48(1):43–52.PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Javier Arbizu
    • 1
    Email author
  • S. Tejada
    • 2
  • J. M. Marti-Climent
    • 1
  • R. Diez-Valle
    • 2
  • E. Prieto
    • 1
  • G. Quincoces
    • 1
  • C. Vigil
    • 1
  • M. A. Idoate
    • 3
  • J. L. Zubieta
    • 4
  • I. Peñuelas
    • 1
  • J. A. Richter
    • 1
  1. 1.Department of Nuclear MedicineClinica Universidad de NavarraPamplonaSpain
  2. 2.Department of NeurosurgeryClinica Universidad de NavarraPamplonaSpain
  3. 3.Department of PathologyClinica Universidad de NavarraPamplonaSpain
  4. 4.Department of RadiologyClinica Universidad de NavarraPamplonaSpain

Personalised recommendations