Skip to main content
Hauptrubriken
CME Facharzt-Training Webinare Zeitschriften Bücher e.Medpedia Podcast
Service
Jobbörse Info & Hilfe
Fachgebiete
Anästhesiologie Allgemeinmedizin Arbeitsmedizin Augenheilkunde Chirurgie Dermatologie Gynäkologie und Geburtshilfe HNO Innere Medizin Kardiologie Neurologie Onkologie und Hämatologie Orthopädie und Unfallchirurgie Pädiatrie Pathologie Psychiatrie Radiologie Rechtsmedizin Urologie Zahnmedizin
Themen
Klimawandel und Gesundheit Neues aus dem Markt COVID-19 Praxis und Beruf Seltene Erkrankungen GOÄ & EBM Panorama
Sammlungen
Kasuistiken Algorithmen & Infografiken Blickdiagnosen Arthropedia FlapFinder (für Dermatochirurgen) Videos Kongressberichterstattung Medizin für Apothekerinnen und Apotheker Für Ärztinnen und Ärzte in Weiterbildung Für Medizinstudierende

Live-Webinar: Aktuelle Leitlinien bei Herz-Kreislauf-Erkrankungen

Konkret geht es um den Diabetes-Patienten mit kardiovaskulären Erkrankungen oder Risiken, die Herzinsuffizienz sowie die kardiovaskuläre Primär- und Sekundärprävention. Sind Sie hier schon auf dem neuesten Stand? Unsere Experten beleuchten, wo und warum das bisherige Procedere geändert werden soll und was in der Praxis sinnvoll ist. Holen Sie sich Ihr Update und 2 CME-Punkte beim MMW-Webinar am 24. April von 17.30 bis 19 Uhr. 
Erweiterte Suche
Anmelden
nach oben
European Journal of Nuclear Medicine and Molecular Imaging
Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging 13/2017

22.08.2017 | Original Article

Comparison of 18F-FET PET and perfusion-weighted MRI for glioma grading: a hybrid PET/MR study

verfasst von: Antoine Verger, Christian P. Filss, Philipp Lohmann, Gabriele Stoffels, Michael Sabel, Hans J. Wittsack, Elena Rota Kops, Norbert Galldiks, Gereon R. Fink, Nadim J. Shah, Karl-Josef Langen

Erschienen in: European Journal of Nuclear Medicine and Molecular Imaging | Ausgabe 13/2017

Einloggen, um Zugang zu erhalten

Abstract

Purpose

Both perfusion-weighted MR imaging (PWI) and O-(2-18F-fluoroethyl)-L-tyrosine PET (18F–FET) provide grading information in cerebral gliomas. The aim of this study was to compare the diagnostic value of 18F–FET PET and PWI for tumor grading in a series of patients with newly diagnosed, untreated gliomas using an integrated PET/MR scanner.

Methods

Seventy-two patients with untreated gliomas [22 low-grade gliomas (LGG), and 50 high-grade gliomas (HGG)] were investigated with 18F–FET PET and PWI using a hybrid PET/MR scanner. After visual inspection of PET and PWI maps (rCBV, rCBF, MTT), volumes of interest (VOIs) with a diameter of 16 mm were centered upon the maximum of abnormality in the tumor area in each modality and the contralateral unaffected hemisphere. Mean and maximum tumor-to-brain ratios (TBRmean, TBRmax) were calculated. In addition, Time-to-Peak (TTP) and slopes of time–activity curves were calculated for 18F–FET PET. Diagnostic accuracies of 18F–FET PET and PWI for differentiating low-grade glioma (LGG) from high-grade glioma (HGG) were evaluated by receiver operating characteristic analyses (area under the curve; AUC).

Results

The diagnostic accuracy of 18F–FET PET and PWI to discriminate LGG from HGG was similar with highest AUC values for TBRmean and TBRmax of 18F–FET PET uptake (0.80, 0.83) and for TBRmean and TBRmax of rCBV (0.80, 0.81). In case of increased signal in the tumor area with both methods (n = 32), local hot-spots were incongruent in 25 patients (78%) with a mean distance of 10.6 ± 9.5 mm. Dynamic FET PET and combination of different parameters did not further improve diagnostic accuracy.

Conclusions

Both 18F–FET PET and PWI discriminate LGG from HGG with similar diagnostic performance. Regional abnormalities in the tumor area are usually not congruent indicating that tumor grading by 18F–FET PET and PWI is based on different pathophysiological phenomena.
Anhänge
Nur mit Berechtigung zugänglich
Literatur
1.
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.CrossRefPubMedPubMedCentral
2.
Jansen NL, Graute V, Armbruster L, Suchorska B, Lutz J, Eigenbrod S, et al. MRI-suspected low-grade glioma: is there a need to perform dynamic FET PET? Eur J Nucl Med Mol Imaging. 2012;39:1021–9.CrossRefPubMed
3.
Jansen NL, Suchorska B, Wenter V, Schmid-Tannwald C, Todica A, Eigenbrod S, et al. Prognostic significance of dynamic 18F-FET PET in newly diagnosed astrocytic high-grade glioma. J Nucl Med Off Publ Soc Nucl Med. 2015;56:9–15.
4.
Rapp M, Heinzel A, Galldiks N, Stoffels G, Felsberg J, Ewelt C, et al. Diagnostic performance of 18F-FET PET in newly diagnosed cerebral lesions suggestive of glioma. J Nucl Med Off Publ Soc Nucl Med. 2013;54:229–35.
5.
Piroth MD, Holy R, Pinkawa M, Stoffels G, Kaiser HJ, Galldiks N, et al. Prognostic impact of postoperative, pre-irradiation (18)F-fluoroethyl-l-tyrosine uptake in glioblastoma patients treated with radiochemotherapy. Radiother. Oncol J Eur Soc Ther Radiol Oncol. 2011;99:218–24.CrossRef
6.
Wyss M, Hofer S, Bruehlmeier M, Hefti M, Uhlmann C, Bärtschi E, et al. Early metabolic responses in temozolomide treated low-grade glioma patients. J Neuro-Oncol. 2009;95:87–93.CrossRef
7.
Galldiks N, Langen K-J, Holy R, Pinkawa M, Stoffels G, Nolte KW, et al. Assessment of Treatment Response in Patients with Glioblastoma Using O-(2-18F-Fluoroethyl)-L-Tyrosine PET in Comparison to MRI. J. Nucl. Med. Off. Publ. Soc. Nucl. Med. [Internet]. 2012 [cited 2012 Jun 7]; Available from: http://​www.​ncbi.​nlm.​nih.​gov/​pubmed/​22645298.
8.
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.CrossRefPubMed
9.
Galldiks N, Stoffels G, Filss C, Rapp M, Blau T, Tscherpel C, 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. 2015;17:1293–300.CrossRefPubMedPubMedCentral
10.
Galldiks N, Law I, Pope WB, Arbizu J, Langen K-J. The use of amino acid PET and conventional MRI for monitoring of brain tumor therapy. NeuroImage Clin. 2017;13:386–94.CrossRefPubMed
11.
Herholz K, Coope D, Jackson A. Metabolic and molecular imaging in neuro-oncology. Lancet Neurol. 2007;6:711–24.CrossRefPubMed
12.
Covarrubias DJ, Rosen BR, Lev MH. Dynamic magnetic resonance perfusion imaging of brain tumors. Oncologist. 2004;9:528–37.CrossRefPubMed
13.
Svolos P, Kousi E, Kapsalaki E, Theodorou K, Fezoulidis I, Kappas C, et al. The role of diffusion and perfusion weighted imaging in the differential diagnosis of cerebral tumors: a review and future perspectives. Cancer Imaging Off Publ Int Cancer Imaging Soc. 2014;14:20.
14.
Blasel S, Franz K, Ackermann H, Weidauer S, Zanella F, Hattingen E. Stripe-like increase of rCBV beyond the visible border of glioblastomas: site of tumor infiltration growing after neurosurgery. J Neuro-Oncol. 2011;103:575–84.CrossRef
15.
Usinskiene J, Ulyte A, Bjørnerud A, Venius J, Katsaros VK, Rynkeviciene R, et al. Optimal differentiation of high- and low-grade glioma and metastasis: a meta-analysis of perfusion, diffusion, and spectroscopy metrics. Neuroradiology. 2016;58:339–50.CrossRefPubMed
16.
Patel P, Baradaran H, Delgado D, Askin G, Christos P, John Tsiouris A, et al. MR perfusion-weighted imaging in the evaluation of high-grade gliomas after treatment: a systematic review and meta-analysis. Neuro-Oncol. 2017;19:118–27.CrossRefPubMed
17.
Sorensen AG, Emblem KE, Polaskova P, Jennings D, Kim H, Ancukiewicz M, et al. Increased survival of glioblastoma patients who respond to antiangiogenic therapy with elevated blood perfusion. Cancer Res. 2012;72:402–7.CrossRefPubMed
18.
Schmainda KM, Prah M, Connelly J, Rand SD, Hoffman RG, Mueller W, et al. Dynamic-susceptibility contrast agent MRI measures of relative cerebral blood volume predict response to bevacizumab in recurrent high-grade glioma. Neuro-Oncol. 2014;16:880–8.CrossRefPubMedPubMedCentral
19.
Neuner I, Kaffanke JB, Langen K-J, Kops ER, Tellmann L, Stoffels G, et al. Multimodal imaging utilising integrated MR-PET for human brain tumour assessment. Eur Radiol. 2012;22:2568–80.CrossRefPubMed
20.
Barajas RF, Phillips JJ, Parvataneni R, Molinaro A, Essock-Burns E, Bourne G, et al. Regional variation in histopathologic features of tumor specimens from treatment-naive glioblastoma correlates with anatomic and physiologic MR imaging. Neuro-Oncol. 2012;14:942–54.CrossRefPubMedPubMedCentral
21.
Habermeier A, Graf J, Sandhöfer BF, Boissel J-P, Roesch F, Closs EI. System L amino acid transporter LAT1 accumulates O-(2-fluoroethyl)-L-tyrosine (FET). Amino Acids. 2015;47:335–44.CrossRefPubMed
22.
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 Off Publ Soc Nucl Med. 2014;55:540–5.
23.
Henriksen OM, Larsen VA, Muhic A, Hansen AE, Larsson HBW, Poulsen HS, 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. 2016;43:103–12.CrossRefPubMed
24.
Göttler J, Lukas M, Kluge A, Kaczmarz S, Gempt J, Ringel F, et al. Intra-lesional spatial correlation of static and dynamic FET-PET parameters with MRI-based cerebral blood volume in patients with untreated glioma. Eur J Nucl Med Mol Imaging. 2017;44:392–7.CrossRefPubMed
25.
Langen K-J, Galldiks N, Hattingen E, Shah NJ. Advances in neuro-oncology imaging. Nat Rev Neurol. 2017;13:279–89.CrossRefPubMed
26.
Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, Burger PC, Jouvet A, et al. The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol (Berl). 2007;114:97–109.CrossRef
27.
Herzog H, Langen K-J, Weirich C, Rota Kops E, Kaffanke J, Tellmann L, et al. High resolution BrainPET combined with simultaneous MRI. Nukl Nucl Med. 2011;50:74–82.CrossRef
28.
29.
Wittsack HJ, Ritzl A, Mödder U. User friendly analysis of MR investigations of the cerebral perfusion: Windows(R)-based image processing. ROFO Fortschr Geb Rontgenstr Nuklearmed. 2002;174:742–6.CrossRefPubMed
30.
Ulmer S, Liess C, Kesari S, Otto N, Straube T, Jansen O. Use of dynamic susceptibility-contrast MRI (DSC-MRI) to assess perfusion changes in the ipsilateral brain parenchyma from glioblastoma. J Neuro-Oncol. 2009;91:213–20.CrossRef
31.
Friedman SN, Bambrough PJ, Kotsarini C, Khandanpour N, Hoggard N. Semi-automated and automated glioma grading using dynamic susceptibility-weighted contrast-enhanced perfusion MRI relative cerebral blood volume measurements. Br J Radiol. 2012;85:e1204–11.CrossRefPubMedPubMedCentral
32.
Ceccon G, Lohmann P, Stoffels G, Judov N, Filss CP, Rapp M, et al. Dynamic O-(2-18F-fluoroethyl)-L-tyrosine positron emission tomography differentiates brain metastasis recurrence from radiation injury after radiotherapy. Neuro-Oncol. 2016;
33.
Hines WG, Hines RJ. Increased power with modified forms of the Levene (med) test for heterogeneity of variance. Biometrics. 2000;56:451–4.CrossRefPubMed
34.
Pöpperl G, Kreth FW, Mehrkens JH, Herms J, Seelos K, Koch W, 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. 2007;34:1933–42.CrossRefPubMed
35.
Sato N, Suzuki M, Kuwata N, Kuroda K, Wada T, Beppu T, et al. Evaluation of the malignancy of glioma using 11C-methionine positron emission tomography and proliferating cell nuclear antigen staining. Neurosurg Rev. 1999;22:210–4.CrossRefPubMed
36.
Janvier L, Olivier P, Blonski M, Morel O, Vignaud J-M, Karcher G, et al. Correlation of SUV-derived indices with Tumoral aggressiveness of Gliomas in static 18F-FDOPA PET: use in clinical practice. Clin Nucl Med. 2015;40:e429–35.CrossRefPubMed
37.
Dunet V, Pomoni A, Hottinger A, Nicod-Lalonde M, Prior JO. Performance of 18F-FET versus 18F-FDG-PET for the diagnosis and grading of brain tumors: systematic review and meta-analysis. Neuro-Oncol. 2016;18:426–34.CrossRefPubMed
38.
Albert NL, Winkelmann I, Suchorska B, Wenter V, Schmid-Tannwald C, Mille E, et al. Early static (18)F-FET-PET scans have a higher accuracy for glioma grading than the standard 20-40 min scans. Eur J Nucl Med Mol Imaging. 2016;43:1105–14.CrossRefPubMed
39.
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.CrossRefPubMedPubMedCentral
40.
Manabe O, Hattori N, Yamaguchi S, Hirata K, Kobayashi K, Terasaka S, et al. Oligodendroglial component complicates the prediction of tumour grading with metabolic imaging. Eur J Nucl Med Mol Imaging. 2015;42:896–904.CrossRefPubMed
41.
Lev MH, Ozsunar Y, Henson JW, Rasheed AA, Barest GD, Harsh GR, 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. 2004;25:214–21.PubMed
42.
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.PubMed
43.
Arvinda HR, Kesavadas C, Sarma PS, Thomas B, Radhakrishnan VV, Gupta AK, et al. Glioma grading: sensitivity, specificity, positive and negative predictive values of diffusion and perfusion imaging. J Neuro-Oncol. 2009;94:87–96.CrossRef
44.
Fayed N, Dávila J, Medrano J, Olmos S. Malignancy assessment of brain tumours with magnetic resonance spectroscopy and dynamic susceptibility contrast MRI. Eur J Radiol. 2008;67:427–33.CrossRefPubMed
45.
Guzmán-De-Villoria JA, Mateos-Pérez JM, Fernández-García P, Castro E, Desco M. Added value of advanced over conventional magnetic resonance imaging in grading gliomas and other primary brain tumors. Cancer Imaging Off Publ Int Cancer Imaging Soc. 2014;14:35.
46.
Langen K-J, Hamacher K, Weckesser M, Floeth F, Stoffels G, Bauer D, et al. O-(2-[18F]fluoroethyl)-L-tyrosine: uptake mechanisms and clinical applications. Nucl Med Biol. 2006;33:287–94.CrossRefPubMed
47.
White ML, Zhang Y, Kirby P, Ryken TC. Can tumor contrast enhancement be used as a criterion for differentiating tumor grades of oligodendrogliomas? AJNR Am J Neuroradiol. 2005;26:784–90.PubMed
48.
Chaichana KL, McGirt MJ, Niranjan A, Olivi A, Burger PC, Quinones-Hinojosa A. Prognostic significance of contrast-enhancing low-grade gliomas in adults and a review of the literature. Neurol Res. 2009;31:931–9.CrossRefPubMed
49.
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 (Berl). 2016;131:803–20.CrossRef
Metadaten
Titel
Comparison of 18F-FET PET and perfusion-weighted MRI for glioma grading: a hybrid PET/MR study
verfasst von
Antoine Verger
Christian P. Filss
Philipp Lohmann
Gabriele Stoffels
Michael Sabel
Hans J. Wittsack
Elena Rota Kops
Norbert Galldiks
Gereon R. Fink
Nadim J. Shah
Karl-Josef Langen
Publikationsdatum
22.08.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
European Journal of Nuclear Medicine and Molecular Imaging / Ausgabe 13/2017
Print ISSN: 1619-7070
Elektronische ISSN: 1619-7089
DOI
https://doi.org/10.1007/s00259-017-3812-3

Weitere Artikel der Ausgabe 13/2017

European Journal of Nuclear Medicine and Molecular Imaging 13/2017 Zur Ausgabe

Editorial

Saving costs in cancer patient management through molecular imaging

Original Article

Diagnostic accuracy of an artificial neural network compared with statistical quantitation of myocardial perfusion images: a Japanese multicenter study

Original Article

Additive value of amyloid-PET in routine cases of clinical dementia work-up after FDG-PET

Letter to the Editor

The relevance of data driven motion correction in diagnostic PET

Original Article

TSPO PET for glioma imaging using the novel ligand 18F-GE-180: first results in patients with glioblastoma

Editorial

TSPO PET using 18F-GE-180: a new perspective in neurooncology?