TY  - JOUR
AU  - Stetter, Isabelle
AU  - Werner, Jan-Michael
AU  - Wollring, Michael
AU  - Ceccon, Garry
AU  - Ciantar, Keith George
AU  - Stoffels, Gabriele
AU  - Mottaghy, Felix M
AU  - Fink, Gereon R
AU  - Langen, Karl-Josef
AU  - Lohmann, Philipp
AU  - Galldiks, Norbert
TI  - Prediction of progression-free andoverall survival following temozolomide chemoradiation using FET PET-base,d parameter.s including radiomics in patients with glio blastorna
JO  - Neuro-oncology advances
VL  - 7
IS  - 1
SN  - 2632-2498
CY  - Oxford
PB  - Oxford University Press
M1  - FZJ-2025-03929
SP  - vdaf196
PY  - 2025
N1  - supported by the Deutsche Forschungsgemeinschaft project number 428090865/SPP2177 (Norbert Galldiks, Philipp Lohmann, Keith George Ciantar)
AB  - 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.
LB  - PUB:(DE-HGF)16
DO  - DOI:10.1093/noajnl/vdaf196
UR  - https://juser.fz-juelich.de/record/1046717
ER  -