Prediction of glioma recurrence using dynamic ¹?F-fluoroethyltyrosine PET.

Pyka, T; Gempt, J; Ringel, F; Hüttinger, S; van Marwick, S; Nekolla, S; Wester, H-J; Schwaiger, M; Förster, S

doi:10.3174/ajnr.A3980

Title:: Prediction of glioma recurrence using dynamic ¹?F-fluoroethyltyrosine PET.
Document type:: Journal Article
Author(s):: Pyka, T; Gempt, J; Ringel, F; Hüttinger, S; van Marwick, S; Nekolla, S; Wester, H-J; Schwaiger, M; Förster, S
Abstract:: Inter- and intratumor heterogeneity and the variable course of disease in patients with glioma motivate the investigation of new prognostic factors to optimize individual treatment. Here we explore the usefulness of standard static and more sophisticated dynamic (18)F-fluoroethyltyrosine-PET imaging for the assessment of patient prognosis.Thirty-four consecutive patients with untreated, first-diagnosed, histologically proved glioma were included in this retrospective study. All patients underwent dynamic PET scans before surgery (± standard treatment) and were followed up clinically and by MR imaging. Static and dynamic tumor-to-background ratio, TTP, and slope-to-peak were obtained and correlated with progression-free survival.Twenty of 34 patients experienced progression, with a median progression-free survival of 28.0 ± 11.1 months. Dynamic TTP was highly prognostic for recurrent disease, showing a strong correlation with progression-free survival (hazard ratio, 6.050; 95% CI, 2.11-17.37; P < .001). Most interesting, this correlation also proved significant in the subgroup of low-grade glioma (hazard ratio, 5.347; 95% CI, 1.05-27.20; P = .044), but not when using established static imaging parameters, such as maximum tumor-to-background ratio and mean tumor-to-background ratio. In the high-grade glioma subgroup, both dynamic and static parameters correlated with progression-free survival. The best results were achieved by defining ROIs around "hot spots" in earlier timeframes, underlining the concept of intratumor heterogeneity.(18)F-fluoroethyltyrosine-PET can predict recurrence in patients with glioma, with dynamic analysis showing advantages over static imaging, especially in the low-grade subgroup.
Journal title abbreviation:: AJNR Am J Neuroradiol
Year:: 2014
Journal volume:: 35
Journal issue:: 10
Pages contribution:: 1924-9
Language:: eng
Fulltext / DOI:: doi:10.3174/ajnr.A3980
Pubmed ID:: http://view.ncbi.nlm.nih.gov/pubmed/24924547
Print-ISSN:: 0195-6108
TUM Institution:: Fachgebiet Neuroradiologie (Prof. Zimmer); Klinik und Poliklinik für Nuklearmedizin; Neurochirurgische Klinik und Poliklinik
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