NIMG-42. ANALYSIS OF TUMOR RELAPSE PROBABILITY AND OVERALL SURVIVAL PREDICTION FOLLOWING TEMOZOLOMIDE CHEMORADIATION USING FET PET INCLUDING RADIOMICS IN PATIENTS WITH GLIOBLASTOMA
Abstract BACKGROUND Early after surgery and completion of first-line concomitant chemoradiation with temozolomide, the evaluation of tumor relapse probability and overall survival prediction is of considerable interest for the management of patients with glioblastoma METHODS Sixty-three newly diagnosed patients with glioblastoma (age range, 19-82) who received static and dynamic PET imaging using the radiolabeled amino acid O-(2-[18F]fluoroethyl)-L-tyrosine (FET) after surgery or biopsy and completion of concomitant chemoradiation with temozolomide were evaluated. Static FET PET parameters such as maximum and mean tumor-to-brain ratios (TBRmax, TBRmean) and metabolic tumor volumes (MTV), and the dynamic FET PET parameter time-to-peak (TTP) were obtained. Additionally, FET PET radiomics features (n=1,303) were extracted for each patient and a test-retest analysis was performed to identify robust features prior to feature selection. The prognostic value of FET PET parameters and radiomics features was evaluated using receiver-operating-characteristic (ROC) analyses with regard to a significantly prolonged progression-free and overall survival (PFS, OS). Subsequently, univariate and multivariate survival estimates were performed to assess the prognostic value of these parameters to predict a significantly longer PFS and OS RESULTS ROC analyses revealed that the parameter TBRmax was a powerful parameter to predict both a significantly longer PFS (20.3 vs. 8.9 months; P=0.002; threshold, 2.75) and OS (34.9 vs. 18.7 months; P=0.005; threshold, 2.75). MTV had a similar prognostic value for both PFS (16.7 vs. 7.2 months; P=0.002; threshold, 34.0 mL) and OS (30.6 vs. 14.8 months; P=0.002; threshold, 32.6 mL). After feature selection, 3 of 15 selected radiomics features predicted a significantly longer PFS and OS in univariate analyses. TBRmax, MTV, and one of 15 radiomics features remained significant in multivariate survival analysis (all P≤0.03) CONCLUSION Our results suggest that FET PET and radiomics parameters were highly prognostic in this group of patients at an early stage of first-line therapy.
Authors
- Gereon R. Fink (ORCID: https://orcid.org/0000-0002-8230-1856)
- Isabelle Stetter (ORCID: https://orcid.org/0009-0007-1732-5759)
- Michael Wollring (ORCID: https://orcid.org/0000-0003-2177-6708)
- Felix Manuel Mottaghy (ORCID: https://orcid.org/0000-0002-7212-6521)
- Garry Ceccon
- Norbert Galldiks (ORCID: https://orcid.org/0000-0002-2485-1796)
- Karl‐Josef Langen (ORCID: https://orcid.org/0000-0003-1101-5075)
- Gabriele Stoffels (ORCID: https://orcid.org/0000-0001-7114-1941)
- Jan‐Michael Werner (ORCID: https://orcid.org/0000-0001-7147-4594)
- Philipp Lohmann (ORCID: https://orcid.org/0000-0002-5360-046X)
- Keith George Ciantar
Institutions
- Forschungszentrum Jülich (DE)
- Universitätsklinikum Aachen (DE)
- University Hospital Cologne (DE)
- RWTH Aachen University (DE)
Publication Details
- Journal
- Neuro-Oncology
- Published
- 2024-11-01
- DOI
- https://doi.org/10.1093/neuonc/noae165.0807
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00