% IMPORTANT: The following is UTF-8 encoded. This means that in the presence % of non-ASCII characters, it will not work with BibTeX 0.99 or older. % Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or % “biber”. @ARTICLE{Stetter:1046717, author = {Stetter, Isabelle and Werner, Jan-Michael and Wollring, Michael and Ceccon, Garry and Ciantar, Keith George and Stoffels, Gabriele and Mottaghy, Felix M and Fink, Gereon R and Langen, Karl-Josef and Lohmann, Philipp and Galldiks, Norbert}, title = {{P}rediction of progression-free andoverall survival following temozolomide chemoradiation using {FET} {PET}-base,d parameter.s including radiomics in patients with glio blastorna}, journal = {Neuro-oncology advances}, volume = {7}, number = {1}, issn = {2632-2498}, address = {Oxford}, publisher = {Oxford University Press}, reportid = {FZJ-2025-03929}, pages = {vdaf196}, year = {2025}, note = {supported by the Deutsche Forschungsgemeinschaft project number 428090865/SPP2177 (Norbert Galldiks, Philipp Lohmann, Keith George Ciantar)}, abstract = {Background: Early after surgery and completion of first-line radiotherapy with concomitant temozolomide, the prediction of progression-free and overall survival (PFS, OS) is of considerable interest for managing patients with glioblastoma.Methods: Sixty-three newly diagnosed patients with glioblastoma (age range, 19-82 years) who received PET imaging using the radiolabeled amino acid O-(2-[18F]fluoroethyl)-L-tyrosine (FET) after surgery or biopsy and completion of radiotherapy with concomitant temozolomide were evaluated. Static FET PET parameters, that is, maximum and mean tumor-to-brain ratios (TBRmax, TBRmean), metabolic tumor volumes (MTV), and the dynamic FET PET parameters time-to-peak (TTP) and slope were obtained. Additionally, n = 1,303 FET PET radiomics features were extracted per patient, of which 15 robust features were selected for further evaluation based on test-retest analysis. The prognostic values of FET PET parameters and radiomics features were evaluated using receiver-operating-characteristic (ROC) analyses regarding a favorable PFS and OS. Subsequently, univariate and multivariate survival estimates were performed to assess the prognostic value of these parameters in predicting a significantly longer PFS and OS.Results: ROC analyses revealed that static parameters (ie, TBRmax, MTV) and one radiomics feature were the most powerful parameters to predict a significantly longer PFS (all P = .002) and OS (all P ≤ .02). In addition, the dynamic parameter TTP predicted a significantly longer OS (P ≤ .03) but not PFS (P > .05). TBRmax, MTV, and one radiomics feature remained significant in multivariate survival analysis (all P ≤ .03).Conclusion: Our results suggest that FET PET parameters, including radiomics, are highly prognostic in patients with glioblastoma at an early stage of first-line therapy.Keywords: artificial intelligence; glioma; prognosis.}, cin = {INM-3}, ddc = {610}, cid = {I:(DE-Juel1)INM-3-20090406}, pnm = {5252 - Brain Dysfunction and Plasticity (POF4-525) / DFG project G:(GEPRIS)428090865 - Radiomics basierend auf MRT und Aminosäure PET in der Neuroonkologie (428090865)}, pid = {G:(DE-HGF)POF4-5252 / G:(GEPRIS)428090865}, typ = {PUB:(DE-HGF)16}, doi = {10.1093/noajnl/vdaf196}, url = {https://juser.fz-juelich.de/record/1046717}, }