scholarly journals Impact of 18F-FET PET on Target Volume Definition and Tumor Progression of Recurrent High Grade Glioma Treated with Carbon-Ion Radiotherapy

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Charlotte Debus ◽  
Maria Waltenberger ◽  
Ralf Floca ◽  
Ali Afshar-Oromieh ◽  
Nina Bougatf ◽  
...  
2014 ◽  
Vol 112 (3) ◽  
pp. 425-429 ◽  
Author(s):  
Pierina Navarria ◽  
Giacomo Reggiori ◽  
Federico Pessina ◽  
Anna Maria Ascolese ◽  
Stefano Tomatis ◽  
...  

2019 ◽  
Vol 21 (Supplement_3) ◽  
pp. iii81-iii81
Author(s):  
A F Keßler ◽  
J Weiland ◽  
T Linsenmann ◽  
R Ernestus ◽  
C Hagemann ◽  
...  

Abstract BACKGROUND The addition of Tumor Treating Fields (TTFields) to the first-line therapy in glioblastoma (GBM) demonstrated significantly improved progression free survival, overall survival and longterm survival rates in the EF-14 phase 3 trial. However, responder analysis of patients with recurrent GBM (rGBM) treated with TTFields monotherapy (in the EF-11 trial) revealed delayed response monitored by MRI analysis. More recent data suggests that O-(2-18F-fluoroethyl)-L-tyrosine (FET) PET may add valuable information for monitoring therapy response of glioblastoma patients treated with TTFields. Here, we report on FET PET response in a patient with progressive anaplastic astrocytoma WHO grade III (AA) treated with TTFields in combination with temozolomide (TMZ) chemotherapy. METHODS We present a 38-year old patient with an initial diagnosis of a diffuse astrocytoma WHO grade II in 2011, and malignisation to an AA on progression. The treatment regimen included initially radio-chemotherapy (RCT) with TMZ. On further progression of the AA in 2017, TTFields were added to another 6 cycles of TMZ. Several FET PET scans for differentiation of tumor progression from treatment-related changes were performed over time. The definitive diagnosis (tumor progression and grading) was confirmed by histopathology after stereotactic biopsy (SB). RESULTS In 2012, the patient was first diagnosed with a low grade astrocytoma WHO grade II of the right frontal, temporal and parietal lobe including infiltration of thalamus and corpus was confirmed by SB, followed by irradiation. On progression in 2015, a FET PET Scan showed FET avidity in all tumor affected regions of the brain. SB confirmed an AA, while FET PET scans showed only a mild response in the temporoparietal region after 6 cycles of TMZ. In 2017, the next progression without further malignisation was confirmed by SB and treated RCT with 41.4 Gy and TMZ chemotherapy, followed by application of TTFields with an average usage rate of 85.7 % over 6 months. Thus, the TTFields adherence was well above the independent prognostic threshold of 75 %. No additional adverse events due to the combined therapy of TTFields and TMZ were observed. Due to a new contrast enhancing lesion in the right frontal lobe (10x7mm), another FET PET scan was performed 1.5 years later. In this scan, obtained after combined TTFields and RCT therapy a strong response regarding FET avidity was observed. CONCLUSION In summary, FET PET is able to add important additional information for evaluation of treatment response in high grade glioma patients, in particular for TTFields treated patients, while adding TTFields to radiochemotherapy might even enhance treatment response of high grade glioma. Further studies might elucidate the role of FET PET imaging for therapy monitoring in high grade glioma patients treated with TTFields.


2014 ◽  
Vol 16 (suppl 2) ◽  
pp. ii3-ii3
Author(s):  
P. Navarria ◽  
F. Pessina ◽  
S. Tomatis ◽  
P. Mancosu ◽  
A. Ascolese ◽  
...  

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Charlotte Debus ◽  
Ali Afshar-Oromieh ◽  
Ralf Floca ◽  
Michael Ingrisch ◽  
Maximilian Knoll ◽  
...  

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 2043-2043
Author(s):  
Patrick Salome ◽  
Francesco Sforazzini ◽  
Andreas Kudak ◽  
Laila König ◽  
Philipp Kickingereder ◽  
...  

2043 Background: Unique radiobiological and physical properties of carbon ion radiotherapy (CIRT) may be favorably utilized to improve outcome in recurrent High-Grade Glioma (rHGG). There are currently no standardized criteria for stratification of rHGG patients for re-irradiation (re-RT). This study evaluated the impact of morphological data (radiomics) and physical information (dosiomics) in stratifying rHGG patients for CIRT. Methods: Quantitative radiomics and dosiomics features were extracted from CIRT planning CTs with dose distribution (DD) and multiparametric MRIs (mpMRI, pre re-RT) of 141 patients (recurrent grade III: n=56 40%, grade IV: n=85 60%) treated with a median dose of 42 Gy (RBE) and a median fraction of 13. The MR sequences considered are T1 weighted pre-and post-contrast agent, fluid-attenuated inversion recovery (FLAIR) and apparent diffusion coefficient (ADC). Benefit of a re-RT risk score (RRRS), comprising the initial tumour grade, age and the Karnofsky Performance Score was shown to correlate with superior outcome in CIRT and conventional re-RT and was also studied here in parallel. Feature sets - a) RRRS, b) radiomics, c) dosiomics features - were evaluated both separately and combined. Multiple feature selection methods were used independently on the CT, DD and the MR sequences, followed by a stepwise Cox's Proportional Hazard model selection per modality or combination thereof. Multivariable models were ranked by 10-fold cross-validated concordance index (C-I). Results: Compared to the RRRS model (OS/PFS, C-I: 0.68/0.61), the multimodality model considering radiomics and dosiomics features (RD) allowed improved prognostic separation (OS/PFS, C-I: 0.77/0.70). The RD signature consisted of 12 and 10 textural features for the OS and PFS models. Combining the RD model with RRRS yielded the best performance (OS/PFS, C-I: 0.78/0.73). No significant correlation between the textural features and the prescribed dose, tumor grade and volume was found, with the Spearman's correlation coefficient ranging between -0.06 to 0.17. Conclusions: Integrating multimodal information outperforms unimodal prognostic separation of rHGG following CIRT, highlighting the importance to consider biological, physical and morphological data for patient stratification. Prospective validation studies of this multimodal stratifier is warranted.[Table: see text]


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