DOI: 10.1007/s00259-018-4009-0Pages: 1573-1584

Integrated analysis of dynamic FET PET/CT parameters, histology, and methylation profiling of 44 gliomas

1. University Hospital Heidelberg, Division of Nuclear Medicine

2. University Hospital Heidelberg, Department of Neuropathology, Institute of Pathology

3. University Hospital, LMU, Department of Nuclear Medicine

4. German Cancer Research Center, Department of Biostatistics

5. University Hospital Eppendorf, University of Hamburg, Institute of Neuropathology

6. University Hospital Eppendorf, University of Hamburg, Department of Pediatric Hematology and Oncology

7. Research Institute Children’s Cancer Center Hamburg

8. German Cancer Research Center, Clinical Cooperation Unit Nuclear Medicine

Correspondence to:
Manuel Röhrich
Tel: 0049 6221 56 7732




Dynamic 18F-FET PET/CT is a powerful tool for the diagnosis of gliomas.18F-FET PET time–activity curves (TAC) allow differentiation between histological low-grade gliomas (LGG) and high-grade gliomas (HGG). Molecular methods such as epigenetic profiling are of rising importance for glioma grading and subclassification. Here, we analysed dynamic 18F-FET PET data, and the histological and epigenetic features of 44 gliomas.


Dynamic 18F-FET PET was performed in 44 patients with newly diagnosed, untreated glioma: 10 WHO grade II glioma, 13 WHO grade III glioma and 21 glioblastoma (GBM). All patients underwent stereotactic biopsy or tumour resection after 18F-FET PET imaging. As well as histological analysis of tissue samples, DNA was subjected to epigenetic analysis using the Illumina 850 K methylation array. TACs, standardized uptake values corrected for background uptake in healthy tissue (SUVmax/BG), time to peak (TTP) and kinetic modelling parameters were correlated with histological diagnoses and with epigenetic signatures. Multivariate analyses were performed to evaluate the diagnostic accuracy of 18F-FET PET in relation to the tumour groups identified by histological and methylation-based analysis.


Epigenetic profiling led to substantial tumour reclassification, with six grade II/III gliomas reclassified as GBM. Overlap of HGG-typical TACs and LGG-typical TACs was dramatically reduced when tumours were clustered on the basis of their methylation profile. SUVmax/BG values of GBM were higher than those of LGGs following both histological diagnosis and methylation-based diagnosis. The differences in TTP between GBMs and grade II/III gliomas were greater following methylation-based diagnosis than following histological diagnosis. Kinetic modeling showed that relative K1 and fractal dimension (FD) values significantly differed in histology- and methylation-based GBM and grade II/III glioma between those diagnosed histologically and those diagnosed by methylation analysis. Multivariate analysis revealed slightly greater diagnostic accuracy with methylation-based diagnosis. IDH-mutant gliomas and GBM subgroups tended to differ in their 18F-FET PET kinetics.


The status of dynamic 18F-FET PET as a biologically and clinically relevant imaging modality is confirmed in the context of molecular glioma diagnosis.

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  • Accepted: Apr 5, 2018
  • Online: May 7, 2018

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