Skip to main content
SpringerLink
Log in

Grading and outcome prediction of pediatric diffuse astrocytic tumors with diffusion and arterial spin labeling perfusion MRI in comparison with 18F–DOPA PET

  • Original Article
  • Published:
European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Purpose

The aim of this study was to investigate MRI-derived diffusion weighted imaging (DWI) and arterial spin labeling (ASL) perfusion imaging in comparison with 18F–dihydroxyphenylalanine (DOPA) PET with respect to diagnostic performance in tumor grading and outcome prediction in pediatric patients with diffuse astrocytic tumors (DAT).

Methods

We retrospectively analyzed 26 children with histologically proven treatment naïve low and high grade DAT who underwent ASL and DWI performed within 2 weeks of 18F–DOPA PET. Relative ASL-derived cerebral blood flow max (rCBF max) and DWI-derived minimum apparent diffusion coefficient (rADC min) were compared with 18F–DOPA uptake tumor/normal tissue (T/N) and tumor/striatum (T/S) ratios, and correlated with World Health Organization (WHO) tumor grade and progression-free survival (PFS). Statistics included Pearson’s chi-square and Mann-Whitney U tests, Spearman’s rank correlation, receiver operating characteristic (ROC) analysis, discriminant function analysis (DFA), Kaplan-Meier survival curve, and Cox analysis.

Results

A significant correlation was demonstrated between rCBF max, rADC min, and 18F–DOPA PET data (p < 0.001). Significant differences in terms of rCBF max, rADC min, and 18F–DOPA uptake were found between low- and high-grade DAT (p ≤ 0.001). ROC analysis and DFA demonstrated that T/S and T/N values were the best parameters for predicting tumor progression (AUC 0.93, p < 0.001). On univariate analysis, all diagnostic tools correlated with PFS (p ≤ 0.001); however, on multivariate analysis, only 18F–DOPA uptake remained significantly associated with outcome (p ≤ 0.03), while a trend emerged for rCBF max (p = 0.09) and rADC min (p = 0.08). The combination of MRI and PET data increased the predictive power for prognosticating tumor progression (AUC 0.97, p < 0.001).

Conclusions

DWI, ASL and 18F–DOPA PET provide useful complementary information for pediatric DAT grading. 18F–DOPA uptake better correlates with PFS prediction. Combining MRI and PET data provides the highest predictive power for prognosticating tumor progression suggesting a synergistic role of these diagnostic tools.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Vossough A, Nabavizadeh SA. Functional imaging based diagnostic strategy: intra-axial brain masses. In: Scott HF, Feroze BM, editors. Functional Neuroradiology, principles and clinical application. New York: Springer; 2011. p. 197–220.

    Chapter  Google Scholar 

  2. Mabray MC, Barajas RF Jr, Cha S. Modern brain tumor imaging. Brain Tumor Res Treat. 2015;3:8–23.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Rossi A, Gandolfo C, Morana G, Severino M, Garrè ML, Cama A. New MR sequences (diffusion, perfusion, spectroscopy) in brain tumours. Pediatr Radiol. 2010;40:999–1009.

    Article  PubMed  Google Scholar 

  4. Warmuth C, Gunther M, Zimmer C. Quantification of blood flow in brain tumors: comparison of arterial spin labeling and dynamic susceptibility-weighted contrast-enhanced MR imaging. Radiology. 2003;228:523–32.

    Article  PubMed  Google Scholar 

  5. Wolf RL, Wang J, Wang S, Melhem ER, O'Rourke DM, Judy KD, et al. Grading of CNS neoplasms using continuous arterial spin labeled perfusion MR imaging at 3 Tesla. J Magn Reson Imaging. 2005;22:475–82.

    Article  PubMed  Google Scholar 

  6. Ata ES, Turgut M, Eraslan C, Dayanır YÖ. Comparison between dynamic susceptibility contrast magnetic resonance imaging and arterial spin labeling techniques in distinguishing malignant from benign brain tumors. Eur J Radiol. 2016;85:1545–53.

    Article  PubMed  Google Scholar 

  7. Yeom KW, Mitchell LA, Lober RM, Barnes PD, Vogel H, Fisher PG, et al. Arterial spin-labeled perfusion of pediatric brain tumors. AJNR Am J Neuroradiol. 2014;35:395–401.

    Article  CAS  PubMed  Google Scholar 

  8. Dangouloff-Ros V, Grevent D, Pagès M, Blauwblomme T, Calmon R, Elie C, et al. Choroid plexus Neoplasms: toward a distinction between carcinoma and Papilloma using arterial spin-Labeling. AJNR Am J Neuroradiol. 2015;36:1786–90.

    Article  CAS  PubMed  Google Scholar 

  9. Nabavizadeh SA, Assadsangabi R, Hajmomenian M, Santi M, Vossough A. High accuracy of arterial spin labeling perfusion imaging in differentiation of pilomyxoid from pilocytic astrocytoma. Neuroradiol. 2015;57:527–33.

    Article  CAS  Google Scholar 

  10. Dangouloff-Ros V, Deroulers C, Foissac F, Badoual M, Shotar E, Grévent D, et al. Arterial spin Labeling to predict brain tumor grading in children: correlations between Histopathologic vascular density and perfusion MR imaging. Radiology. 2016;281:553–66.

    Article  PubMed  Google Scholar 

  11. Albert NL, Weller M, Suchorska B, Galldiks N, Soffietti R, Kim MM, 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. 2016;18:1199–208.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Heiss WD, Raab P, Lanfermann H. Multimodality assessment of brain tumors and tumor recurrence. J Nucl Med. 2011;52:1585–600.

    Article  CAS  PubMed  Google Scholar 

  13. Morana G, Piccardo A, Milanaccio C, Puntoni M, Nozza P, Cama A, et al. Value of 18F-3,4-dihydroxyphenylalanine PET/MR image fusion in pediatric supratentorial infiltrative astrocytomas: a prospective pilot study. J Nucl Med. 2014;55:718–23.

    Article  CAS  PubMed  Google Scholar 

  14. Morana G, Piccardo A, Puntoni M, Nozza P, Cama A, Raso A, et al. Diagnostic and prognostic value of 18F-DOPA PET and 1H-MR spectroscopy in pediatric supratentorial infiltrative gliomas: a comparative study. Neuro-Oncol. 2015;17:1637–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, et al. The 2016 World Health Organization classification of Tumors of the central nervous system: a summary. Acta Neuropathol. 2016;131:803–20.

    Article  PubMed  Google Scholar 

  16. Wen PY, Macdonald DR, Reardon DA, Cloughesy TF, Sorensen AG, Galanis E, et al. Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol. 2010;28:1963–72.

    Article  PubMed  Google Scholar 

  17. van den Bent MJ, Wefel JS, Schiff D, Taphoorn MJ, Jaeckle K, Junck L, et al. Response assessment in neuro-oncology (a report of the RANO group): assessment of outcome in trials of diffuse low-grade gliomas. Lancet Oncol. 2011;12:583–93.

    Article  PubMed  Google Scholar 

  18. Sorensen AG, Patel S, Harmath C, Bridges S, Synnott J, Sievers A, et al. Comparison of diameter and perimeter methods for tumor volume calculation. J Clin Oncol. 2001;19:551–7.

    Article  CAS  PubMed  Google Scholar 

  19. Morana G, Piccardo A, Garrè ML, Cabria M, Rossi A. 18F-DOPA uptake of developmental venous anomalies in children with brain Tumors. Clin Nucl Med. 2016;41:e351–2.

    Article  PubMed  Google Scholar 

  20. Berntsson SG, Falk A, Savitcheva I, Godau A, Zetterling M, Hesselager G, et al. Perfusion and diffusion MRI combined with 11C-methionine PET in the preoperative evaluation of suspected adult low-grade gliomas. J Neuro-Oncol. 2013;11:241–9.

    Article  Google Scholar 

  21. Lapa C, Linsenmann T, Monoranu CM, Samnick S, Buck AK, Bluemel C, et al. Comparison of the amino acid tracers 18F-FET and 18F-DOPA in high-grade glioma patients. J Nucl Med. 2014;55:1611–6.

    Article  CAS  PubMed  Google Scholar 

  22. Caulo M, Panara V, Tortora D, Mattei PA, Briganti C, Pravatà E, et al. Data-driven grading of brain gliomas: a multiparametric MR imaging study. Radiology. 2014;272:494–503.

    Article  PubMed  Google Scholar 

  23. Morana G, Piccardo A, Garrè ML, Nozza P, Consales A, Rossi A. Multimodal magnetic resonance imaging and 18F-L-dihydroxyphenylalanine positron emission tomography in early characterization of pseudoresponse and nonenhancing tumor progression in a pediatric patient with malignant transformation of ganglioglioma treated with bevacizumab. J Clin Oncol. 2013;31:e1–5.

    Article  PubMed  Google Scholar 

  24. Hipp SJ, Steffen-Smith EA, Patronas N, Herscovitch P, Solomon JM, Bent RS, et al. Molecular imaging of pediatric brain tumors: comparison of tumor metabolism using 18F FDG-PET and MRSI. J Neuro-Oncol. 2012;109:521–7.

    Article  CAS  Google Scholar 

  25. Fraioli F, Shankar A, Hargrave D, Hyare H, Gaze MN, Groves AM, et al. 18F-fluoroethylcholine (18F-Cho) PET/MRI functional parameters in pediatric astrocytic brain tumors. Clin Nucl Med. 2015;40:e40–5.

    Article  PubMed  Google Scholar 

  26. Zukotynski KA, Fahey FH, Vajapeyam S, Ng SS, Kocak M, Gururangan S, et al. Exploratory evaluation of MR permeability with 18F-FDG PET mapping in Pediatric brain Tumors: a report from the Pediatric brain tumor consortium. J Nucl Med. 2013;54:1237–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Zukotynski K, Vajapeyam S, Fahey FH, Kocak M, Brown D, Ricci K, et al. Correlation of 18F-FDG PET and MR apparent diffusion coefficient (ADC) histogram metrics with survival in diffuse intrinsic Pontine Glioma: a report from the Pediatric brain tumor consortium. J Nucl Med. 2017; doi:10.2967/jnumed.116.185389.

  28. Fink JR, Muzi M, Peck M, Krohn KA. Multimodality Brain Tumor Imaging: MR Imaging, PET, and PET/MR Imaging. J Nucl Med. 2015;56:1554–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Werner P, Barthel H, Drzezga A, Sabri O. Current status and future role of brain PET/MRI in clinical and research settings. Eur J Nucl Med Mol Imaging. 2015;42:512–26.

    Article  CAS  PubMed  Google Scholar 

  30. Henriksen OM, Larsen VA, Muhic A, Hansen AE, Larsson HB, Poulsen HS, et al. Simultaneous evaluation of brain tumour metabolism, structure and blood volume using [(18)F]-fluoroethyltyrosine (FET) PET/MRI: feasibility, agreement and initial experience. Eur J Nucl Med Mol Imaging. 2016;43:103–12.

    Article  CAS  PubMed  Google Scholar 

  31. Jones DT, Mulholland SA, Pearson DM, Malley DS, Openshaw SW, Lambert SR, et al. Adult grade II diffuse astrocytomas are genetically distinct from and more aggressive than their paediatric counterparts. Acta Neuropathol. 2011;121:753–61.

    Article  PubMed  Google Scholar 

  32. Paugh BS, Qu C, Jones C, Liu Z, Adamowicz-Brice M, Zhang J, et al. Integrated molecular genetic profiling of pediatric high-grade gliomas reveals key differences with the adult disease. J Clin Oncol. 2010;28:3061–8.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Gajjar A, Bowers DC, Karajannis MA, Leary S, Witt H, Gottardo NG. Pediatric brain Tumors: innovative genomic information is transforming the diagnostic and clinical landscape. J Clin Oncol. 2015;33:2986–98.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Huisman TA. Diffusion-weighted imaging: basic concepts and application in cerebral stroke and head trauma. Eur Radiol. 2003;13:2283–97.

    Article  PubMed  Google Scholar 

  35. Kan P, Liu JK, Hedlund G, Brockmeyer DL, Walker ML, Kestle JR. The role of diffusion-weighted magnetic resonance imaging in pediatric brain tumors. Childs Nerv Syst. 2006;22:1435–9.

    Article  PubMed  Google Scholar 

  36. Lequin M, Hendrikse J. Advanced MR imaging in Pediatric brain Tumors, clinical applications. Neuroimaging Clin N Am. 2017;27:167–90.

    Article  PubMed  Google Scholar 

  37. Lober RM, Cho YJ, Tang Y, Barnes PD, Edwards MS, Vogel H, et al. Diffusion-weighted MRI derived apparent diffusion coefficient identifies prognostically distinct subgroups of pediatric diffuse intrinsic pontine glioma. J Neuro-Oncol. 2014;117:175–82.

    Article  Google Scholar 

  38. Rose S, Fay M, Thomas P, Bourgeat P, Dowson N, Salvado O, 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. 2013;34:758–64.

    Article  CAS  PubMed  Google Scholar 

  39. Karavaeva E, Harris RJ, Leu K, Shabihkhani M, Yong WH, Pope WB, et al. Relationship between [18F]FDOPA PET uptake, apparent diffusion coefficient (ADC), and proliferation rate in recurrent malignant Gliomas. Mol Imaging Biol. 2015;17:434–42.

    Article  CAS  PubMed  Google Scholar 

  40. Morana G, Puntoni M, Garrè ML, Massollo M, Lopci E, Naseri M, et al. Ability of (18)F-DOPA PET/CT and fused (18)F-DOPA PET/MRI to assess striatal involvement in paediatric glioma. Eur J Nucl Med Mol Imaging. 2016;43:1664–72.

    Article  CAS  PubMed  Google Scholar 

  41. Alsop DC, Detre JA, Golay X, Günther M, Hendrikse J, Hernandez-Garcia L, et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med. 2015;73:102–16.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported, in part, by the Associazione per la ricerca sui tumori cerebrali del bambino (ARTUCEBA) and Fondazione Guido Berlucchi.

Author information

Authors and Affiliations

  1. Neuroradiology Unit, Istituto Giannina Gaslini, via G. Gaslini 5, 16147, Genoa, Italy

    Giovanni Morana, Domenico Tortora, Mariasavina Severino & Andrea Rossi

  2. Nuclear Medicine Unit, Ente Ospedaliero Ospedali Galliera, Genoa, Italy

    Arnoldo Piccardo & Manlio Cabria

  3. Clinical Trial Unit, Scientific Directorate, Ente Ospedaliero Ospedali Galliera, Genoa, Italy

    Matteo Puntoni

  4. Pathology Unit, Istituto Giannina Gaslini, Genoa, Italy

    Paolo Nozza

  5. Neurosurgery Unit, Istituto Giannina Gaslini, Genoa, Italy

    Marcello Ravegnani, Alessandro Consales, Samantha Mascelli & Alessandro Raso

  6. Neuro-oncology Unit, Istituto Giannina Gaslini, Genoa, Italy

    Antonio Verrico & Claudia Milanaccio

Authors
  1. Giovanni Morana
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arnoldo Piccardo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Domenico Tortora
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Matteo Puntoni
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mariasavina Severino
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Paolo Nozza
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Marcello Ravegnani
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Alessandro Consales
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Samantha Mascelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Alessandro Raso
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Manlio Cabria
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Antonio Verrico
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Claudia Milanaccio
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Andrea Rossi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Giovanni Morana.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

For this type of study (retrospective study) formal consent is not required. This article does not contain any studies with animals performed by any of the authors.

Informed consent was signed from all patients or their legal guardians, and patient assent was obtained whenever appropriate.

Electronic supplementary material

ESM 1

(DOCX 105 kb).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Morana, G., Piccardo, A., Tortora, D. et al. Grading and outcome prediction of pediatric diffuse astrocytic tumors with diffusion and arterial spin labeling perfusion MRI in comparison with 18F–DOPA PET. Eur J Nucl Med Mol Imaging 44, 2084–2093 (2017). https://doi.org/10.1007/s00259-017-3777-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00259-017-3777-2

Keywords

Search

Navigation