Combination of MRI and dynamic FET PET for initial glioma grading

V. Dunet; P. Maeder; M. Nicod-Lalonde; B. Lhermitte; C. Pollo; J. Bloch; R. Stupp; R. Meuli; J. O. Prior

doi:10.3413/Nukmed-0650-14-03

Nuklearmedizin - NuclearMedicine, Inhaltsverzeichnis

Nuklearmedizin 2014; 53(04): 155-161
DOI: 10.3413/Nukmed-0650-14-03

Original article

Schattauer GmbH

Combination of MRI and dynamic FET PET for initial glioma grading

Kombination von MRI und dynamischer FET-PET zum initialen Grading von Gliomen

Autor*innen

V. Dunet

¹Department of Radiology, University Hospital Lausanne

²Department of Nuclear Medicine, University Hospital Lausanne
P. Maeder

¹Department of Radiology, University Hospital Lausanne
M. Nicod-Lalonde

²Department of Nuclear Medicine, University Hospital Lausanne
B. Lhermitte

³Department of Pathology and Laboratory Medicine, University Hospital Lausanne
C. Pollo

⁴Department of Neurosurgery, University Hospital, Bern, Switzerland
J. Bloch

⁵Department of Neurosurgery, University Hospital Lausanne
R. Stupp

⁶Department of Oncology, University Hospital Lausanne
R. Meuli

¹Department of Radiology, University Hospital Lausanne
J. O. Prior

²Department of Nuclear Medicine, University Hospital Lausanne

Abstract

Summary

Aim: MRI and PET with ¹⁸F-fluoro-ethyl-tyro- sine (FET) have been increasingly used to evaluate patients with gliomas. Our purpose was to assess the additive value of MR spectroscopy (MRS), diffusion imaging and dynamic FET-PET for glioma grading. Patients, methods: 38 patients (42 ± 15 aged, F/M: 0.46) with untreated histologically proven brain gliomas were included. All underwent conventional MRI, MRS, diffusion sequences, and FET-PET within 3±4 weeks. Performances of tumour FET time-activity-curve, early-to-middle SUVmax ratio, choline / creatine ratio and ADC histogram distribution pattern for gliomas grading were assessed, as compared to histology. Combination of these parameters and respective odds were also evaluated. Results: Tumour time-activity- curve reached the best accuracy (67%) when taken alone to distinguish between low and high-grade gliomas, followed by ADC histogram analysis (65%). Combination of time-activity-curve and ADC histogram analysis improved the sensitivity from 67% to 86% and the specificity from 63-67% to 100% (p < 0.008). On multivariate logistic regression analysis, negative slope of the tumour FET time-activity-curve however remains the best predictor of high-grade glioma (odds 7.6, SE 6.8, p = 0.022). Conclusion: Combination of dynamic FET-PET and diffusion MRI reached good performance for gliomas grading. The use of FET-PET/MR may be highly relevant in the initial assessment of primary brain tumours.

Zusammenfassung

MR und ¹⁸F-Fluorethyltyrosin (FET) PET werden vermehrt zur Diagnostik bei Patienten mit Gliomen angewandt. Ziel unserer Studie war die Bewertung des zusätzlichen Nutzens von MR-Spektroskopie (MRS), Diffusions-MR und dynamischer FET-PET für das Grading von Gliomen. Patienten, Methoden: Insgesamt, 38 Patienten (42±15 Jahre, F/M = 0,46) mit unbehandelten histologisch gesicherten zerebralen Gliomen wurden mittels konventioneller MR, MRS, Diffusionssequenzen und FET-PET untersucht, die einzelnen Untersuchungen fanden im Zeitraum von 3±4 Wochen statt. Die tumorale FET-Zeit-Aktivi- täts-Kurve, das Verhältnis der frühen zur mittleren SUVmax-Ratio, die Choline/Kreatin- Ratio und ADC-Histogramm-Verteilungsmus- ter wurden für das Gliom-Grading evaluiert und verglichen mit der Histologie. Die Kombinationen dieser Parameter und ihre Odds- Ratio wurden ausgewertet. Ergebnisse: Die tumorale FET-Zeit-Aktivitäts-Kurve allein erreichte die beste Genauigkeit (67%) bei der Differenzierung von Low- und High-grade- Gliomen, gefolgt von der ADC-Histogramm- Analyse (65%). Die Kombination beider Faktoren verbesserte die Sensibilität von 67% auf 86% und die Spezifität von 63-67% auf 100% (p < 0,008). In der multivariaten logistischen Regressionsanalyse war ein negative Steigungsfaktor der tumoralen FET-Zeit-Akti- vitäts-Kurve der beste Indikator für high-grade Gliome (Odds 7,6, SE 6,8, p = 0,022). Schlussfolgerung: Die Kombination von dynamischer FET-PET und Diffusions-MRI ist gut zum Grading von Gliomen geeignet. Daher könnte der Kombination von FET-PET/MRT hohe Relevanz in der initialen Beurteilung primärer Hirntumoren zukommen.

Keywords

MRI - ADC histogram - ¹⁸F-fluoro-ethyl-tyrosine - glioma - grading

Schlüsselwörter

MR - ADC-Histogramm - ¹⁸F-Fluorethyltyrosin - Gliom - Grading

Volltext

Referenzen

References
1 Arvinda HR, Kesavadas C, Sarma PS. et al. Glioma grading: sensitivity, specificity, positive and negative predictive values of diffusion and perfusion imaging. J Neurooncol 2009; 94: 87-96.
2 Baborie A, Kuschinsky W. Lack of relationship between cellular density and either capillary density or metabolic rate in different regions of the brain. Neurosci Lett 2006; 404: 20-22.
3 Bull JG, Saunders DE, Clark CA. Discrimination of paediatric brain tumours using apparent diffusion coefficient histograms. Eur Radiol 2012; 22: 447-457.
4 Calcagni ML, Galli G, Giordano A. et al. Dynamic O-(2-[¹⁸F]fluoroethyl)-L-tyrosine PET for glioma grading: assessment of individual probability of malignancy. Clin Nucl Med 2011; 36: 841-847.
5 Dolecek TA, Propp JM, Stroup NE, Kruchko C. CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2005-2009. Neurooncology 2012; 14 (Suppl. 05) v1-v49.
6 Dunet V, Rossier C, Buck A. et al. Performance of 18F-fluoro-ethyl-tyrosine (¹⁸F-FET) PET for the differential diagnosis of primary brain tumor. J Nucl Med. 2012; 53: 207-214.
7 Ellingson BM, Malkin MG, Rand SD. et al. Validation of functional diffusion maps as a biomarker for human glioma cellularity. J Magn Reson Imaging 2010; 31: 538-548.
8 Floeth FW, Pauleit D, Wittsack HJ. et al. Multimodal metabolic imaging of cerebral gliomas: positron emission tomography with [¹⁸F]fluoro-ethyl-L-tyrosine and magnetic resonance spectroscopy. J Neurosurg 2005; 102: 318-327.
9 Heiss P, Mayer S, Herz M. et al. Investigation of transport mechanism and uptake kinetics of O-(2-[¹⁸F]fluoroethyl)-L-tyrosine in vitro and in vivo. J Nucl Med 1999; 40: 1367-1373.
10 Heller IH, Elliott KA. The metabolism of normal brain and human gliomas in relation to cell type and density. Can J Biochem Physiol 1955; 33: 395-403.
11 Herzog H, Langen KJ, Weirich C. et al. High resolution BrainPET combined with simultaneous MRI. Nuklearmedizin 2011; 50: 74-82.
12 Holodny AI, Makeyev S, Beattie BJ. et al. Apparent diffusion coefficient of glial neoplasms. AJNR Am J Neuroradiol 2010; 31: 1042-1048.
13 Jansen NL, Graute V, Armbruster L. et al. MRI-suspected low-grade glioma: is there a need to perform dynamic FET PET?. Eur J Nucl Med Mol Imaging 2012; 39: 1021-1029.
14 Jansen NL, Schwartz C, Graute V. et al. Prediction of oligodendroglial histology and LOH 1p/19q using dynamic [¹⁸F]FET-PET imaging in intracranial WHO grade II and III gliomas. Neuro Oncol 2012; 14: 1473-1480.
15 Kang Y, Choi SH, Kim YJ. et al. Gliomas: Histogram analysis of apparent diffusion coefficient maps with standardor high-b-value diffusion-weighted MR imaging–correlation with tumor grade. Radiology 2011; 261: 882-890.
16 Kunz M, Thon N, Eigenbrod S. et al. Hot spots in dynamic ¹⁸FET-PET delineate malignant tumor parts within suspected WHO grade II gliomas. Neuro Oncol 2011; 13: 307-316.
17 La Fougere C, Suchorska B, Bartenstein P. et al. Molecular imaging of gliomas with PET. Neuro Oncol 2011; 13: 806-819.
18 Langen KJ, Bartenstein P, Boecker H. et al. German guidelines for brain tumour imaging by PET and SPECT using labelled amino acids. Nuklearmedizin 2011; 50: 167-173.
19 Law M, Yang S, Wang H. 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: 1989-1998.
20 Louis DN, Ohgaki H, Wiestler OD. et al. The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol 2007; 114: 97-109.
21 Moller-Hartmann W, Herminghaus S, Krings T. et al. Clinical application of proton magnetic resonance spectroscopy in the diagnosis of intracranial mass lesions. Neuroradiology 2002; 44: 371-381.
22 Palumbo B, Angotti F, Marano GD. Relationship between PET-FDG and MRI apparent diffusion coefficients in brain tumors. Q J Nucl Med Mol Imaging 2009; 53: 17-22.
23 Pauleit D, Floeth F, Hamacher K. et al. O-(2-[¹⁸F]fluoroethyl)-L-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain 2005; 128: 678-687.
24 Pauleit D, Floeth F, Herzog H. et al. Whole-body distribution and dosimetry of O-(2-[¹⁸F]fluoro-ethyl)-L-tyrosine. Eur J Nucl Med Mol Imaging. 2003; 30: 519-524.
25 Pope WB, Kim HJ, Huo J. et al. Recurrent glioblastoma multiforme: ADC histogram analysis predicts response to bevacizumab treatment. Radiology 2009; 252: 182-189.
26 Pöpperl G, Gotz C, Rachinger W. et al. Value of O-(2-[¹⁸F]fluoroethyl)-L-tyrosine PET for the diagnosis of recurrent glioma. Eur J Nucl Med Mol Imaging 2004; 31: 1464-1470.
27 Pöpperl G, Kreth FW, Herms J. et al. Analysis of ¹⁸F-FET PET for grading of recurrent gliomas: is evaluation of uptake kinetics superior to standard methods?. J Nucl Med 2006; 47: 393-403.
28 Pöpperl G, Kreth FW, Mehrkens JH. et al. FET PET for the evaluation of untreated gliomas. Eur J Nucl Med Mol Imaging 2007; 34: 1933-1942.
29 Rose S, Fay M, Thomas P. et al. Correlation of MRI-derived apparent diffusion coefficients in newly diagnosed gliomas with [¹⁸F]-fluoro-L-dopa PET. AJNR Am J Neuroradiol 2013; 34: 758-764.
30 Salber D, Stoffels G, Pauleit D. et al. Differential uptake of O-(2-¹⁸F-fluoroethyl)-L-tyrosine, L-³H-methionine, and ³H-deoxyglucose in brain abscesses. J Nucl Med 2007; 48: 2056-2062.
31 Spaeth N, Wyss MT, Weber B. et al. Uptake of ¹⁸F-fluorocholine, ¹⁸F-fluoroethyl-L-tyrosine, and ¹⁸F-FDG in acute cerebral radiation injury in the rat. J Nucl Med 2004; 45: 1931-1938.
32 Vander Borght T, Asenbaum S, Bartenstein P. et al. EANM procedure guidelines for brain tumour imaging using labelled amino acid analogues. Eur J Nucl Med Mol Imaging 2006; 33: 1374-1380.
33 Weber WA, Wester HJ, Grosu AL. et al. O-(2-[¹⁸F]fluoroethyl)-L-tyrosine and L-[methyl-¹¹C]methionine uptake in brain tumours. Eur J Nucl Med 2000; 27: 542-549.
34 Wester HJ, Herz M, Weber W. et al. Synthesis and radiopharmacology of O-(2-[¹⁸F]fluoroethyl)-L-tyrosine for tumor imaging. J Nucl Med 1999; 40: 205-212.