nach oben

Erschienen in:

19.11.2020 | Neuro

Static ¹⁸F-FET PET and DSC-PWI based on hybrid PET/MR for the prediction of gliomas defined by IDH and 1p/19q status

verfasst von: Shuangshuang Song, Leiming Wang, Hongwei Yang, Yongzhi Shan, Ye Cheng, Lixin Xu, Chengyan Dong, Guoguang Zhao, Jie Lu

Erschienen in: European Radiology | Ausgabe 6/2021

Einloggen, um Zugang zu erhalten

Abstract

Objectives

To investigate the predictive value of static O-(2-¹⁸F-fluoroethyl)-L-tyrosine positron emission tomography (¹⁸F-FET PET) and cerebral blood volume (CBV) for glioma grading and determining isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status.

Methods

Fifty-two patients with newly diagnosed gliomas who underwent simultaneous ¹⁸F-FET PET and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) examinations on hybrid PET/MR were retrospectively enrolled. The mean and max tumor-to-brain ratio (TBR) and normalized CBV (nCBV) were calculated based on whole tumor volume segmentations with reference to PET/MR images. The predictive efficacy of FET PET and CBV in glioma according to the 2016 World Health Organization (WHO) classification was evaluated by receiver operating characteristic curve analyses with the area under the curve (AUC).

Results

TBRmean, TBRmax, nCBVmean, and nCBVmax differed between low- and high-grade gliomas, with the highest AUC of nCBVmean (0.920). TBRmax and nCBVmean showed significant differences between gliomas with and without IDH mutation (p = 0.032 and 0.010, respectively). Furthermore, TBRmean, TBRmax, and nCBVmean discriminated between IDH-wildtype glioblastomas and IDH-mutated astrocytomas (p = 0.049, 0.034 and 0.029, respectively). The combination of TBRmax and nCBVmean showed the best predictive performance (AUC, 0.903). Only nCBVmean differentiated IDH-mutated with 1p/19q codeletion oligodendrogliomas from IDH-wildtype glioblastomas (p < 0.001) (AUC, 0.829), but none of the parameters discriminated between oligodendrogliomas and astrocytomas.

Conclusions

Both FET PET and DSC-PWI might be non-invasive predictors for glioma grades and IDH mutation status. FET PET combined with CBV could improve the differentiation of IDH-mutated astrocytomas and IDH-wildtype glioblastomas. However, FET PET and CBV might be limited for identifying oligodendrogliomas.

Key Points

• Static ¹⁸F-FET PET and DSC-PWI parameters differed between low- and high-grade gliomas, with the highest AUC of the mean value of normalized CBV.

• Static ¹⁸F-FET PET and DSC-PWI parameters based on hybrid PET/MR showed predictive value in identifying glioma IDH mutation subtypes, which have gained importance for both determining the diagnosis and prognosis of gliomas according to the 2016 WHO classification.

• Static ¹⁸F-FET PET and DSC-PWI parameters have limited potential in differentiating IDH-mutated with 1p/19q codeletion oligodendrogliomas from IDH-wildtype glioblastomas or IDH-mutated astrocytomas.

Nur mit Berechtigung zugänglich

Rogers TW, Toor G, Drummond K et al (2018) The 2016 revision of the WHO Classification of Central Nervous System Tumours: retrospective application to a cohort of diffuse gliomas. J Neurooncol 137:181–189. https://doi.org/10.1007/s11060-017-2710-7CrossRefPubMed

Eckel-Passow JE, Lachance DH, Molinaro AM et al (2015) Glioma groups based on 1p/19q, IDH, and TERT promoter mutations in tumors. N Engl J Med 372:2499–2508. https://doi.org/10.1056/NEJMoa1407279CrossRefPubMedPubMedCentral

Kloosterhof NK, Bralten LB, Dubbink HJ, French PJ, van den Bent MJ (2011) Isocitrate dehydrogenase-1 mutations: a fundamentally new understanding of diffuse glioma? Lancet Oncol 12:83–91. https://doi.org/10.1016/S1470-2045(10)70053-XCrossRefPubMed

Buckner J, Giannini C, Eckel-Passow J et al (2017) Management of diffuse low-grade gliomas in adults - use of molecular diagnostics. Nat Rev Neurol 13:340–351. https://doi.org/10.1038/nrneurol.2017.54CrossRefPubMed

Ostrom QT, Cote DJ, Ascha M, Kruchko C, Barnholtz-Sloan JS (2018) Adult glioma incidence and survival by race or ethnicity in the United States from 2000 to 2014. JAMA Oncol 4:1254–1262. https://doi.org/10.1001/jamaoncol.2018.1789CrossRefPubMedPubMedCentral

Broen MPG, Smits M, Wijnenga MMJ et al (2018) The T2-FLAIR mismatch sign as an imaging marker for non-enhancing IDH-mutant, 1p/19q-intact lower-grade glioma: a validation study. Neuro Oncol 20:1393–1399. https://doi.org/10.1093/neuonc/noy048CrossRefPubMedPubMedCentral

Smits M, van den Bent MJ (2017) Imaging correlates of adult glioma genotypes. Radiology 284:316–331. https://doi.org/10.1148/radiol.2017151930CrossRefPubMed

Englander ZK, Horenstein CI, Bowden SG et al (2018) Extent of bold vascular dysregulation is greater in diffuse gliomas without isocitrate dehydrogenase 1 R132H mutation. Radiology 287:965–972. https://doi.org/10.1148/radiol.2017170790CrossRefPubMed

Latysheva A, Emblem KE, Brandal P et al (2019) Dynamic susceptibility contrast and diffusion MR imaging identify oligodendroglioma as defined by the 2016 WHO classification for brain tumors: histogram analysis approach. Neuroradiology 61:545–555. https://doi.org/10.1007/s00234-019-02173-5CrossRefPubMed

10.

Hyun SC, Sung KH, Chai JS et al (2019) Imaging prediction of isocitrate dehydrogenase (IDH) mutation in patients with glioma: a systemic review and meta-analysis. Eur Radiol 29:745–758. https://doi.org/10.1007/s00330-018-5608-7CrossRef

11.

Albert NL, Weller M, Suchorska B et al (2016) 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 18:1199–1208. https://doi.org/10.1093/neuonc/now058CrossRefPubMedPubMedCentral

12.

Law I, Albert NL, Arbizu J et al (2018) Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [18F]FDG: version 1.0. Eur J Nucl Med Mol Imaging 46:540–557. https://doi.org/10.1007/s00259-018-4207-9CrossRefPubMedPubMedCentral

13.

Galldiks N, Stoffels G, Ruge MI et al (2013) Role of O-(2-18F-fluoroethyl)-L-tyrosine PET as a diagnostic tool for detection of malignant progression in patients with low-grade glioma. J Nucl Med 54:2046–2054. https://doi.org/10.2967/jnumed.113.123836CrossRefPubMed

14.

Kunz M, Thon N, Eigenbrod S et al (2011) Hot spots in dynamic (FET)-F-18-PET delineate malignant tumor parts within suspected WHO grade II gliomas. Neuro Oncol 13:307–316. https://doi.org/10.1093/neuonc/noq196CrossRefPubMedPubMedCentral

15.

Verger A, Stoffels G, Bauer EK et al (2018) Static and dynamic 18F–FET PET for the characterization of gliomas defined by IDH and 1p/19q status. Eur J Nucl Med Mol Imaging 45:443–451. https://doi.org/10.1007/s00259-017-3846-6CrossRefPubMed

16.

Vettermann F, Suchorska B, Unterrainer M et al (2019) Non-invasive prediction of IDH-wildtype genotype in gliomas using dynamic 18F-FET PET. Eur J Nucl Med Mol Imaging 46:2581–2589. https://doi.org/10.1007/s00259-019-04477-3CrossRefPubMed

17.

Song S, Cheng Y, Ma J et al (2020) Simultaneous FET-PET and contrast-enhanced MRI based on hybrid PET/MR improves delineation of tumor spatial biodistribution in gliomas: a biopsy validation study. Eur J Nucl Med Mol Imaging 47:1458–1467. https://doi.org/10.1007/s00259-019-04656-2CrossRefPubMedPubMedCentral

18.

Welker K, Boxerman J, Kalnin A et al (2015) ASFNR recommendations for clinical performance of MR dynamic susceptibility contrast perfusion imaging of the brain. AJNR Am J Neuroradiol 36:E41–E51. https://doi.org/10.3174/ajnr.A4341CrossRefPubMedPubMedCentral

19.

Munck Af Rosenschold P, Costa J, Engelholm SA et al (2015) Impact of [18F]-fluoro-ethyl-tyrosine PET imaging on target definition for radiation therapy of high-grade glioma. Neuro Oncol 17:757–763. https://doi.org/10.1093/neuonc/nou316CrossRefPubMed

20.

Pauleit D, Floeth F, Hamacher K et al (2005) O-(2-[18F]fluoroethyl)-L-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain 128:678–687. https://doi.org/10.1093/brain/awh399CrossRefPubMed

21.

Lohmann P, Stavrinou P, Lipke K et al (2019) FET PET reveals considerable spatial differences in tumour burden compared to conventional MRI in newly diagnosed glioblastoma. Eur J Nucl Med Mol Imaging 46:591–602. https://doi.org/10.1007/s00259-018-4188-8CrossRefPubMed

22.

Filss CP, Galldiks N, Stoffels G et al (2014) Comparison of 18F-FET PET and perfusion-weighted MR imaging: a PET/MR imaging hybrid study in patients with brain tumors. J Nucl Med 55:540–545. https://doi.org/10.2967/jnumed.113.129007CrossRefPubMed

23.

Langen KJ, Watts C (2016) Neuro-oncology: amino acid PET for brain tumours - ready for the clinic? Nat Rev Neurol 12:375–376. https://doi.org/10.1038/nrneurol.2016.80CrossRefPubMed

24.

Pöpperl G, Kreth FW, Mehrkens JH et al (2007) FET PET for the evaluation of untreated gliomas: correlation of FET uptake and uptake kinetics with tumour grading. Eur J Nucl Med Mol Imaging 34:1933–1942. https://doi.org/10.1007/s00259-007-0534-yCrossRefPubMed

25.

Rapp M, Heinzel A, Galldiks N et al (2013) Diagnostic performance of F-18-FET PET in newly diagnosed cerebral lesions suggestive of glioma. J Nucl Med 54:229–235. https://doi.org/10.2967/jnumed.112.109603CrossRefPubMed

26.

Unterrainer M, Vettermann F, Brendel M et al (2017) Towards standardization of 18F-FET PET imaging: do we need a consistent method of background activity assessment? EJNMMI Res 7:48. https://doi.org/10.1186/s13550-017-0295-yCrossRefPubMedPubMedCentral

27.

Kebir S, Weber M, Lazaridis L et al (2019) Hybrid C-11-MET PET/MRI combined with “machine learning” in glioma diagnosis according to the revised glioma WHO Classification 2016. Clin Nucl Med 44:214–220. https://doi.org/10.1097/RLU.0000000000002398CrossRefPubMed

28.

Liang J, Liu D, Gao P et al (2017) Diagnostic values of DCE-MRI and DSC-MRI for differentiation between high-grade and low-grade gliomas: a comprehensive meta-analysis. Acad Radiol 25:338–348. https://doi.org/10.1016/j.acra.2017.10.001CrossRefPubMed

29.

Brendle C, Hempel J, Schittenhelm J et al (2018) Glioma grading by dynamic susceptibility contrast perfusion and (11)C-methionine positron emission tomography using different regions of interest. Neuroradiology 60:381–389. https://doi.org/10.1007/s00234-018-1993-5CrossRefPubMed

30.

Anzalone N, Castellano A, Cadioli M et al (2018) Brain gliomas: multicenter standardized assessment of dynamic contrast-enhanced and dynamic susceptibility contrast MR images. Radiology 287:933–943. https://doi.org/10.1148/radiol.2017170362CrossRefPubMed

31.

Verger A, Filss CP, Lohmann P et al (2017) Comparison of 18F-FET PET and perfusion-weighted MRI for glioma grading: a hybrid PET/MR study. Eur J Nucl Med Mol Imaging 44:2257–2265. https://doi.org/10.1007/s00259-017-3812-3CrossRefPubMed

32.

Lee JY, Ahn KJ, Lee YS, Jang JH, Jung SL, Kim BS (2018) Differentiation of grade II and III oligodendrogliomas from grade II and III astrocytomas: a histogram analysis of perfusion parameters derived from dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) MRI. Acta Radiol 59:723–731. https://doi.org/10.1177/0284185117728981CrossRefPubMed

Titel: Static 18F-FET PET and DSC-PWI based on hybrid PET/MR for the prediction of gliomas defined by IDH and 1p/19q status
verfasst von: Shuangshuang Song
Leiming Wang
Hongwei Yang
Yongzhi Shan
Ye Cheng
Lixin Xu
Chengyan Dong
Guoguang Zhao
Jie Lu
Publikationsdatum: 19.11.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: European Radiology / Ausgabe 6/2021
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-020-07470-9

Update Radiologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Die Highlights vom Kongress des American College of Cardiology 2024

Springer Medizin

Static ¹⁸F-FET PET and DSC-PWI based on hybrid PET/MR for the prediction of gliomas defined by IDH and 1p/19q status