Advertisement

Simultaneous evaluation of brain tumour metabolism, structure and blood volume using [18F]-fluoroethyltyrosine (FET) PET/MRI: feasibility, agreement and initial experience

  • Otto M. Henriksen
  • Vibeke A. Larsen
  • Aida Muhic
  • Adam E. Hansen
  • Henrik B. W. Larsson
  • Hans S. Poulsen
  • Ian Law
Original Article

Abstract

Purpose

Both [18F]-fluoroethyltyrosine (FET) PET and blood volume (BV) MRI supplement routine T1-weighted contrast-enhanced MRI in gliomas, but whether the two modalities provide identical or complementary information is unresolved. The aims of the study were to investigate the feasibility of simultaneous structural MRI, BV MRI and FET PET of gliomas using an integrated PET/MRI scanner and to assess the spatial and quantitative agreement in tumour imaging between BV MRI and FET PET.

Methods

A total of 32 glioma patients underwent a 20-min static simultaneous PET/MRI acquisition on a Siemens mMR system 20 min after injection of 200 MBq FET. The MRI protocol included standard structural MRI and dynamic susceptibility contrast (DSC) imaging for BV measurements. Maximal relative tumour FET uptake (TBRmax) and BV (rBVmax), and Dice coefficients were calculated to assess the quantitative and spatial congruence in the tumour volumes determined by FET PET, BV MRI and contrast-enhanced MRI.

Results

FET volume and TBRmax were higher in BV-positive than in BV-negative scans, and both VOLBV and rBVmax were higher in FET-positive than in FET-negative scans. TBRmax and rBVmax were positively correlated (R 2 = 0.59, p < 0.001). FET and BV positivity were in agreement in only 26 of the 32 patients and in 42 of 63 lesions, and spatial congruence in the tumour volumes as assessed by the Dice coefficients was generally poor with median Dice coefficients exceeding 0.1 in less than half the patients positive on at least one modality for any pair of modalities. In 56 % of the patients susceptibility artefacts in DSC BV maps overlapped the tumour on MRI.

Conclusion

The study demonstrated that although tumour volumes determined by BV MRI and FET PET were quantitatively correlated, their spatial congruence in a mixed population of treated glioma patients was generally poor, and the modalities did not provide the same information in this population of patients. Combined imaging of brain tumour metabolism and perfusion using hybrid PET/MR systems may provide complementary information on tumour biology, but the potential clinical value remains to be determined in future trials.

Keywords

Glioma PET/MRI [18F]-fluoro-ethyl-tyrosine Blood volume 

Notes

Acknowledgments

We thank The John and Birthe Meyer Foundation who donated the mMR PET/MR scanner to Copenhagen University Hospital Rigshospitalet. The authors would also like to thank technologists K. Stahr and M. Federspiel, and radiographer J.M. Poulsen for scanner assistance.

Compliance with ethical standards

Conflicts of interest

None.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the prospective study group. For the retrospective group included in the analysis, formal consent is not required according to the standards of the national research committee.

References

  1. 1.
    Rachinger W, Goetz C, Popperl G, Gildehaus FJ, Kreth FW, Holtmannspotter M, et al. Positron emission tomography with O-(2-[18F]fluoroethyl)-l-tyrosine versus magnetic resonance imaging in the diagnosis of recurrent gliomas. Neurosurgery. 2005;57:505–11.CrossRefPubMedGoogle Scholar
  2. 2.
    Waldman AD, Jackson A, Price SJ, Clark CA, Booth TC, Auer DP, et al. Quantitative imaging biomarkers in neuro-oncology. Nat Rev Clin Oncol. 2009;6:445–54.CrossRefPubMedGoogle Scholar
  3. 3.
    Lau EW, Drummond KJ, Ware RE, Drummond E, Hogg A, Ryan G, et al. Comparative PET study using F-18 FET and F-18 FDG for the evaluation of patients with suspected brain tumour. J Clin Neurosci. 2010;17:43–9.CrossRefPubMedGoogle Scholar
  4. 4.
    Pauleit D, Stoffels G, Bachofner A, Floeth FW, Sabel M, Herzog H, et al. Comparison of (18)F-FET and (18)F-FDG PET in brain tumors. Nucl Med Biol. 2009;36:779–87.CrossRefPubMedGoogle Scholar
  5. 5.
    Pauleit D, Floeth F, Hamacher K, Riemenschneider MJ, Reifenberger G, Muller HW, et al. O-(2-[18F]fluoroethyl)-L-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain. 2005;128:678–87.CrossRefPubMedGoogle Scholar
  6. 6.
    Floeth FW, Pauleit D, Sabel M, Stoffels G, Reifenberger G, Riemenschneider MJ, et al. Prognostic value of O-(2-18F-fluoroethyl)-L-tyrosine PET and MRI in low-grade glioma. J Nucl Med. 2007;48:519–27.CrossRefPubMedGoogle Scholar
  7. 7.
    Hutterer M, Nowosielski M, Putzer D, Jansen NL, Seiz M, Schocke 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. 2013;15:341–51.PubMedCentralCrossRefPubMedGoogle Scholar
  8. 8.
    Popperl G, Gotz C, Rachinger W, Gildehaus FJ, Tonn JC, Tatsch K. Value of O-(2-[18F]fluoroethyl)-L-tyrosine PET for the diagnosis of recurrent glioma. Eur J Nucl Med Mol Imaging. 2004;31:1464–70.CrossRefPubMedGoogle Scholar
  9. 9.
    Law M, Yang S, Wang H, Babb JS, Johnson G, Cha S, 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. 2003;24:1989–98.PubMedGoogle Scholar
  10. 10.
    Larsen VA, Simonsen HJ, Law I, Larsson HB, Hansen AE. Evaluation of dynamic contrast-enhanced T1-weighted perfusion MRI in the differentiation of tumor recurrence from radiation necrosis. Neuroradiology. 2013;55:361–9.CrossRefPubMedGoogle Scholar
  11. 11.
    Shiroishi MS, Castellazzi G, Boxerman JL, D'Amore F, Essig M, Nguyen TB, et al. Principles of T2*-weighted dynamic susceptibility contrast MRI technique in brain tumor imaging. J Magn Reson Imaging. 2015;41:296–313.CrossRefPubMedGoogle Scholar
  12. 12.
    Dandois V, Rommel D, Renard L, Jamart J, Cosnard G. Substitution of 11C-methionine PET by perfusion MRI during the follow-up of treated high-grade gliomas: preliminary results in clinical practice. J Neuroradiol. 2010;37:89–97.CrossRefPubMedGoogle Scholar
  13. 13.
    Sadeghi N, Salmon I, Decaestecker C, Levivier M, Metens T, Wikler D, et al. Stereotactic comparison among cerebral blood volume, methionine uptake, and histopathology in brain glioma. AJNR Am J Neuroradiol. 2007;28:455–61.PubMedGoogle Scholar
  14. 14.
    Sadeghi N, Salmon I, Tang BN, Denolin V, Levivier M, Wikler D, et al. Correlation between dynamic susceptibility contrast perfusion MRI and methionine metabolism in brain gliomas: preliminary results. J Magn Reson Imaging. 2006;24:989–94.CrossRefPubMedGoogle Scholar
  15. 15.
    Filss CP, Galldiks N, Stoffels G, Sabel M, Wittsack HJ, Turowski B, 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. 2014;55:540–5.CrossRefPubMedGoogle Scholar
  16. 16.
    Tietze A, Boldsen JK, Mouridsen K, Ribe L, Dyve S, Cortnum S, et al. Spatial distribution of malignant tissue in gliomas: correlations of 11C-L-methionine positron emission tomography and perfusion- and diffusion-weighted magnetic resonance imaging. Acta Radiol. 2015;56:1135–44.CrossRefPubMedGoogle Scholar
  17. 17.
    Berntsson SG, Falk A, Savitcheva I, Godau A, Zetterling M, Hesselager G, et al. Perfusion and diffusion MRI combined with (11)C-methionine PET in the preoperative evaluation of suspected adult low-grade gliomas. J Neurooncol. 2013;114:241–9.PubMedCentralCrossRefPubMedGoogle Scholar
  18. 18.
    Wehrl HF, Sauter AW, Judenhofer MS, Pichler BJ. Combined PET/MR imaging – technology and applications. Technol Cancer Res Treat. 2010;9:5–20.CrossRefPubMedGoogle Scholar
  19. 19.
    Delso G, Furst S, Jakoby B, Ladebeck R, Ganter C, Nekolla SG, et al. Performance measurements of the Siemens mMR integrated whole-body PET/MR scanner. J Nucl Med. 2011;52:1914–22.CrossRefPubMedGoogle Scholar
  20. 20.
    Andersen FL, Ladefoged CN, Beyer T, Keller SH, Hansen AE, Hojgaard L, et al. Combined PET/MR imaging in neurology: MR-based attenuation correction implies a strong spatial bias when ignoring bone. Neuroimage. 2014;84:206–16.CrossRefPubMedGoogle Scholar
  21. 21.
    Bjornerud A, Sorensen AG, Mouridsen K, Emblem KE. T1- and T2*-dominant extravasation correction in DSC-MRI: part I – theoretical considerations and implications for assessment of tumor hemodynamic properties. J Cereb Blood Flow Metab. 2011;31:2041–53.PubMedCentralCrossRefPubMedGoogle Scholar
  22. 22.
    Bisdas S, Kirkpatrick M, Giglio P, Welsh C, Spampinato MV, Rumboldt Z. Cerebral blood volume measurements by perfusion-weighted MR imaging in gliomas: ready for prime time in predicting short-term outcome and recurrent disease? AJNR Am J Neuroradiol. 2009;30:681–8.CrossRefPubMedGoogle Scholar
  23. 23.
    Boxerman JL, Schmainda KM, Weisskoff RM. Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not. AJNR Am J Neuroradiol. 2006;27:859–67.PubMedGoogle Scholar
  24. 24.
    Reardon DA, Wen PY. Glioma in 2014: unravelling tumour heterogeneity – implications for therapy. Nat Rev Clin Oncol. 2015;12:69–70.CrossRefPubMedGoogle Scholar
  25. 25.
    Vartanian A, Singh SK, Agnihotri S, Jalali S, Burrell K, Aldape KD, et al. GBM's multifaceted landscape: highlighting regional and microenvironmental heterogeneity. Neuro Oncol. 2014;16:1167–75.PubMedCentralCrossRefPubMedGoogle Scholar
  26. 26.
    Puttick S, Bell C, Dowson N, Rose S, Fay M. PET, MRI, and simultaneous PET/MRI in the development of diagnostic and therapeutic strategies for glioma. Drug Discov Today. 2015;20:306–17.CrossRefPubMedGoogle Scholar
  27. 27.
    Bisdas S, Ritz R, Bender B, Braun C, Pfannenberg C, Reimold M, et al. Metabolic mapping of gliomas using hybrid MR-PET imaging: feasibility of the method and spatial distribution of metabolic changes. Invest Radiol. 2013;48:295–301.CrossRefPubMedGoogle Scholar
  28. 28.
    Dickson JC, O'Meara C, Barnes A. A comparison of CT- and MR-based attenuation correction in neurological PET. Eur J Nucl Med Mol Imaging. 2014;41:1176–89.CrossRefPubMedGoogle Scholar
  29. 29.
    Jansen NL, Schwartz C, Graute V, Eigenbrod S, Lutz J, Egensperger R, et al. 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. 2012;14:1473–80.PubMedCentralCrossRefPubMedGoogle Scholar
  30. 30.
    Saito T, Yamasaki F, Kajiwara Y, Abe N, Akiyama Y, Kakuda T, et al. Role of perfusion-weighted imaging at 3T in the histopathological differentiation between astrocytic and oligodendroglial tumors. Eur J Radiol. 2012;81:1863–9.CrossRefPubMedGoogle Scholar
  31. 31.
    Stadlbauer A, Pichler P, Karl M, Brandner S, Lerch C, Renner B, et al. Quantification of serial changes in cerebral blood volume and metabolism in patients with recurrent glioblastoma undergoing antiangiogenic therapy. Eur J Radiol. 2015;84:1128–36.CrossRefPubMedGoogle Scholar
  32. 32.
    Galldiks N, Rapp M, Stoffels G, Fink GR, Shah NJ, Coenen HH, et al. Response assessment of bevacizumab in patients with recurrent malignant glioma using [18F]Fluoroethyl-L-tyrosine PET in comparison to MRI. Eur J Nucl Med Mol Imaging. 2013;40:22–33.CrossRefPubMedGoogle Scholar
  33. 33.
    Rau MK, Braun C, Skardelly M, Schittenhelm J, Paulsen F, Bender B, et al. Prognostic value of blood flow estimated by arterial spin labeling and dynamic susceptibility contrast-enhanced MR imaging in high-grade gliomas. J Neurooncol. 2014;120:557–66.CrossRefPubMedGoogle Scholar
  34. 34.
    Law M, Young RJ, Babb JS, Peccerelli N, Chheang S, Gruber ML, et al. Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology. 2008;247:490–8.PubMedCentralCrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Otto M. Henriksen
    • 1
  • Vibeke A. Larsen
    • 2
  • Aida Muhic
    • 3
  • Adam E. Hansen
    • 1
  • Henrik B. W. Larsson
    • 4
  • Hans S. Poulsen
    • 3
  • Ian Law
    • 1
  1. 1.Department of Clinical Physiology Nuclear Medicine and PETCopenhagen University Hospital Rigshospitalet BlegdamsvejCopenhagenDenmark
  2. 2.Department of RadiologyCopenhagen University Hospital Rigshospitalet BlegdamsvejCopenhagenDenmark
  3. 3.Department of OncologyCopenhagen University Hospital Rigshospitalet BlegdamsvejCopenhagenDenmark
  4. 4.Functional Imaging Unit, Department of Clinical Physiology Nuclear Medicine and PETCopenhagen University Hospital Rigshospitalet GlostrupGlostrupDenmark

Personalised recommendations