Translating the theranostic concept to neuro-oncology: disrupting barriers.

Theranostics integrate molecular imaging and targeted radionuclide therapy for personalised cancer therapy. Theranostic treatments have shown meaningful efficacy in randomised clinical trials and are approved for clinical use in prostate cancer and neuroendocrine tumours. Brain tumours represent an unmet clinical need and theranostics might offer effective treatment options, although specific issues need to be considered for clinical development. In this Policy Review, we discuss opportunities and challenges of developing targeted radionuclide therapies for the treatment of brain tumours including glioma, meningioma, and brain metastasis. The rational choice of molecular treatment targets is highlighted, including the potential relevance of different types of targeted radionuclide therapeutics, and the role of the blood-brain barrier and blood-tumour barrier. Furthermore, we discuss considerations for effective clinical trial design and conduct, as well as logistical and regulatory challenges for implementation of radionuclide therapies into neuro-oncological practice. Rational development will foster successful translation of the theranostic concept to brain tumours.

Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements.

The development, application, and benchmarking of artificial intelligence (AI) tools to improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid pace. This Policy Review provides an overview and critical assessment of the work to date in this field, focusing on diagnostic AI models of key genomic markers, predictive AI models of response before and after therapy, and differentiation of true disease progression from treatment-related changes, which is a considerable challenge based on current clinical care in neuro-oncology. Furthermore, promising future directions, including the use of AI for automated response assessment in neuro-oncology, are discussed.

Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice.

Technological advancements have enabled the extended investigation, development, and application of computational approaches in various domains, including health care. A burgeoning number of diagnostic, predictive, prognostic, and monitoring biomarkers are continuously being explored to improve clinical decision making in neuro-oncology. These advancements describe the increasing incorporation of artificial intelligence (AI) algorithms, including the use of radiomics. However, the broad applicability and clinical translation of AI are restricted by concerns about generalisability, reproducibility, scalability, and validation. This Policy Review intends to serve as the leading resource of recommendations for the standardisation and good clinical practice of AI approaches in health care, particularly in neuro-oncology. To this end, we investigate the repeatability, reproducibility, and stability of AI in response assessment in neuro-oncology in studies on factors affecting such computational approaches, and in publicly available open-source data and computational software tools facilitating these goals. The pathway for standardisation and validation of these approaches is discussed with the view of trustworthy AI enabling the next generation of clinical trials. We conclude with an outlook on the future of AI-enabled neuro-oncology.

PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): a report of the RANO group.

Response Assessment in Neuro-Oncology (RANO) response criteria have been established and were updated in 2023 for MRI-based response evaluation of diffuse gliomas in clinical trials. In addition, PET-based imaging with amino acid tracers is increasingly considered for disease monitoring in both clinical practice and clinical trials. So far, a standardised framework defining timepoints for baseline and follow-up investigations and response evaluation criteria for PET imaging of diffuse gliomas has not been established. Therefore, in this Policy Review, we propose a set of criteria for response assessment based on amino acid PET imaging in clinical trials enrolling participants with diffuse gliomas as defined in the 2021 WHO classification of tumours of the central nervous system. These proposed PET RANO criteria provide a conceptual framework that facilitates the structured implementation of PET imaging into clinical research and, ultimately, clinical routine. To this end, the PET RANO 1.0 criteria are intended to encourage specific investigations of amino acid PET imaging of gliomas.

Joint EANM/EANO/RANO/SNMMI practice guideline/procedure standards for diagnostics and therapy (theranostics) of meningiomas using radiolabeled somatostatin receptor ligands: version 1.0.

PURPOSE: To provide practice guideline/procedure standards for diagnostics and therapy (theranostics) of meningiomas using radiolabeled somatostatin receptor (SSTR) ligands. METHODS: This joint practice guideline/procedure standard was collaboratively developed by the European Association of Nuclear Medicine (EANM), the Society of Nuclear Medicine and Molecular Imaging (SNMMI), the European Association of Neurooncology (EANO), and the PET task force of the Response Assessment in Neurooncology Working Group (PET/RANO). RESULTS: Positron emission tomography (PET) using somatostatin receptor (SSTR) ligands can detect meningioma tissue with high sensitivity and specificity and may provide clinically relevant information beyond that obtained from structural magnetic resonance imaging (MRI) or computed tomography (CT) imaging alone. SSTR-directed PET imaging can be particularly useful for differential diagnosis, delineation of meningioma extent, detection of osseous involvement, and the differentiation between posttherapeutic scar tissue and tumour recurrence. Moreover, SSTR-peptide receptor radionuclide therapy (PRRT) is an emerging investigational treatment approach for meningioma. CONCLUSION: These practice guidelines will define procedure standards for the application of PET imaging in patients with meningiomas and related SSTR-targeted PRRTs in routine practice and clinical trials and will help to harmonize data acquisition and interpretation across centers, facilitate comparability of studies, and to collect larger databases. The current document provides additional information to the evidence-based recommendations from the PET/RANO Working Group regarding the utilization of PET imaging in meningiomas Galldiks (Neuro Oncol. 2017;19(12):1576-87). The information provided should be considered in the context of local conditions and regulations.

Advanced Imaging in the Diagnosis and Response Assessment of High-Grade Glioma: AJR Expert Panel Narrative Review.

This AJR Expert Panel Narrative explores the current status of advanced MRI and PET techniques for the post-therapeutic response assessment of high-grade adult-type gliomas, focusing on ongoing clinical controversies in current practice. Discussed techniques that complement conventional MRI and aid the differentiation of recurrent tumor from post-treatment effects include DWI and diffusion tensor imaging; perfusion MRI techniques including dynamic susceptibility contrast (DSC), dynamic contrast-enhanced MRI, and arterial spin labeling; MR spectroscopy including assessment of 2-hydroxyglutarate (2HG) concentration; glucose- and amino acid (AA)-based PET; and amide proton transfer imaging. Updated criteria for Response Assessment in Neuro-Oncology are presented. Given the abundant supporting clinical evidence, the panel supports a recommendation that routine response assessment after HGG treatment should include perfusion MRI, particularly given the development of a consensus recommended DSC-MRI protocol. Although published studies support 2HG MRS and AA PET, these techniques' widespread adoption will likely require increased availability (for 2HG MRS) or increased insurance funding in the United States (for AA PET). The article concludes with a series of consensus opinions from the author panel, centered on the clinical integration of the advanced imaging techniques into posttreatment surveillance protocols.

A framework for standardised tissue sampling and processing during resection of diffuse intracranial glioma: joint recommendations from four RANO groups.

Surgical resection represents the standard of care for people with newly diagnosed diffuse gliomas, and the neuropathological and molecular profile of the resected tissue guides clinical management and forms the basis for research. The Response Assessment in Neuro-Oncology (RANO) consortium is an international, multidisciplinary effort that aims to standardise research practice in neuro-oncology. These recommendations represent a multidisciplinary consensus from the four RANO groups: RANO resect, RANO recurrent glioblastoma, RANO radiotherapy, and RANO/PET for a standardised workflow to achieve a representative tumour evaluation in a disease characterised by intratumoural heterogeneity, including recommendations on which tumour regions should be surgically sampled, how to define those regions on the basis of preoperative imaging, and the optimal sample volume. Practical recommendations for tissue sampling are given for people with low-grade and high-grade gliomas, as well as for people with newly diagnosed and recurrent disease. Sampling of liquid biopsies is also addressed. A standardised workflow for subsequent handling of the resected tissue is proposed to avoid information loss due to decreasing tissue quality or insufficient clinical information. The recommendations offer a framework for prospective biobanking studies.

Clinical applications and prospects of PET imaging in patients with IDH-mutant gliomas.

PET imaging using radiolabeled amino acids in addition to MRI has become a valuable diagnostic tool in the clinical management of patients with brain tumors. This review provides a comprehensive overview of PET studies in glioma patients with a mutation in the isocitrate dehydrogenase gene (IDH). A considerable fraction of these tumors typically show no contrast enhancement on MRI, especially when classified as grade 2 according to the World Health Organization classification of Central Nervous System tumors. Major diagnostic challenges in this situation are differential diagnosis, target definition for diagnostic biopsies, delineation of glioma extent for treatment planning, differentiation of treatment-related changes from tumor progression, and the evaluation of response to alkylating agents. The main focus of this review is the role of amino acid PET in this setting. Furthermore, in light of clinical trials using IDH inhibitors targeting the mutated IDH enzyme for treating patients with IDH-mutant gliomas, we also aim to give an outlook on PET probes specifically targeting the IDH mutation, which appear potentially helpful for response assessment.

The impact of brain lesions on health-related quality of life in patients with WHO CNS grade 3 or 4 glioma: a lesion-function and resting-state fMRI analysis.

PURPOSE: In glioma patients, tumor development and multimodality therapy are associated with changes in health-related quality of life (HRQoL). It is largely unknown how different types and locations of tumor- and treatment-related brain lesions, as well as their relationship to white matter tracts and functional brain networks, affect HRQoL. METHODS: In 121 patients with pretreated gliomas of WHO CNS grades 3 or 4, structural MRI, O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET, resting-state functional MRI (rs-fMRI) and self-reported HRQoL questionnaires (EORTC QLQ-C30/BN20) were obtained. Resection cavities, T1-enhancing lesions, T2/FLAIR hyperintensities, and lesions with pathologically increased FET uptake were delineated. Effects of tumor lateralization, involvement of white matter tracts or resting-state network nodes by different types of lesions and within-network rs-fMRI connectivity were analyzed in terms of their interaction with HRQoL scores. RESULTS: Right hemisphere gliomas were associated with significantly less favorable outcomes in physical, role, emotional and social functioning, compared with left-sided tumors. Most functional HRQoL scores correlated significantly with right-sided white-matter tracts involvement by T2/FLAIR hyperintensities and with loss of within-network functional connectivity of right-sided nodes. Tumors of the left hemisphere caused significantly more communication deficits. CONCLUSION: In pretreated high-grade gliomas, right hemisphere lesions are associated with reduced HRQoL scores in most functional domains except communication ability, compared to tumors of the left hemisphere. These relationships are mainly observed for T2/FLAIR lesions involving structural and functional networks in the right hemisphere. The data suggest that sparing the right hemisphere from treatment-related tissue damage may improve HRQoL in glioma patients.

Radiomics for the non-invasive prediction of PD-L1 expression in patients with brain metastases secondary to non-small cell lung cancer.

BACKGROUND: The expression level of the programmed cell death ligand 1 (PD-L1) appears to be a predictor for response to immunotherapy using checkpoint inhibitors in patients with non-small cell lung cancer (NSCLC). As differences in terms of PD-L1 expression levels in the extracranial primary tumor and the brain metastases may occur, a reliable method for the non-invasive assessment of the intracranial PD-L1 expression is, therefore of clinical value. Here, we evaluated the potential of radiomics for a non-invasive prediction of PD-L1 expression in patients with brain metastases secondary to NSCLC. PATIENTS AND METHODS: Fifty-three NSCLC patients with brain metastases from two academic neuro-oncological centers (group 1, n = 36 patients; group 2, n = 17 patients) underwent tumor resection with a subsequent immunohistochemical evaluation of the PD-L1 expression. Brain metastases were manually segmented on preoperative T1-weighted contrast-enhanced MRI. Group 1 was used for model training and validation, group 2 for model testing. After image pre-processing and radiomics feature extraction, a test-retest analysis was performed to identify robust features prior to feature selection. The radiomics model was trained and validated using random stratified cross-validation. Finally, the best-performing radiomics model was applied to the test data. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analyses. RESULTS: An intracranial PD-L1 expression (i.e., staining of at least 1% or more of tumor cells) was present in 18 of 36 patients (50%) in group 1, and 7 of 17 patients (41%) in group 2. Univariate analysis identified the contrast-enhancing tumor volume as a significant predictor for PD-L1 expression (area under the ROC curve (AUC), 0.77). A random forest classifier using a four-parameter radiomics signature, including tumor volume, yielded an AUC of 0.83 ± 0.18 in the training data (group 1), and an AUC of 0.84 in the external test data (group 2). CONCLUSION: The developed radiomics classifiers allows for a non-invasive assessment of the intracranial PD-L1 expression in patients with brain metastases secondary to NSCLC with high accuracy.

Undetected pseudoprogressions in the CeTeG/NOA-09 trial: hints from postprogression survival and MRI analyses.

PURPOSE: In the randomized CeTeG/NOA-09 trial, lomustine/temozolomide (CCNU/TMZ) was superior to TMZ therapy regarding overall survival (OS) in MGMT promotor-methylated glioblastoma. Progression-free survival (PFS) and pseudoprogression rates (about 10%) were similar in both arms. Further evaluating this discrepancy, we analyzed patterns of postprogression survival (PPS) and MRI features at first progression according to modified RANO criteria (mRANO). METHODS: We classified the patients of the CeTeG/NOA-09 trial according to long vs. short PPS employing a cut-off of 18 months and compared baseline characteristics and survival times. In patients with available MRIs and confirmed progression, the increase in T1-enhancing, FLAIR hyperintense lesion volume and the change in ADC mean value of contrast-enhancing tumor upon progression were determined. RESULTS: Patients with long PPS in the CCNU/TMZ arm had a particularly short PFS (5.6 months). PFS in this subgroup was shorter than in the long PPS subgroup of the TMZ arm (11.1 months, p = 0.01). At mRANO-defined progression, patients of the CCNU/TMZ long PPS subgroup had a significantly higher increase of mean ADC values (p = 0.015) and a tendency to a stronger volumetric increase in T1-enhancement (p = 0.22) as compared to long PPS patients of the TMZ arm. CONCLUSION: The combination of survival and MRI analyses identified a subgroup of CCNU/TMZ-treated patients with features that sets them apart from other patients in the trial: short first PFS despite long PPS and significant increase in mean ADC values upon mRANO-defined progression. The observed pattern is compatible with the features commonly observed in pseudoprogression suggesting mRANO-undetected pseudoprogressions in the CCNU/TMZ arm of CeTeG/NOA-09.

Imaging Characteristics of Meningiomas.

Contemporary neuroimaging of meningiomas has largely relied on computed tomography, and more recently magnetic resonance imaging. While these modalities are frequently used in nearly all clinical settings where meningiomas are treated for the routine diagnosis and follow-up of these tumors, advances in neuroimaging have provided novel opportunities for prognostication and treatment planning (including both surgical planning and radiotherapy planning). These include perfusion MRIs, and positron emission tomography (PET) imaging modalities. Here we will summarize the contemporary uses for neuroimaging in meningiomas, and future applications of novel, cutting edge imaging techniques that may be routinely implemented in the future to enable more precise treatment of these challenging tumors.

Joint EANM/SIOPE/RAPNO practice guidelines/SNMMI procedure standards for imaging of paediatric gliomas using PET with radiolabelled amino acids and [18F]FDG: version 1.0.

Positron emission tomography (PET) has been widely used in paediatric oncology. 2-Deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) is the most commonly used radiopharmaceutical for PET imaging. For oncological brain imaging, different amino acid PET radiopharmaceuticals have been introduced in the last years. The purpose of this document is to provide imaging specialists and clinicians guidelines for indication, acquisition, and interpretation of [18F]FDG and radiolabelled amino acid PET in paediatric patients affected by brain gliomas. There is no high level of evidence for all recommendations suggested in this paper. These recommendations represent instead the consensus opinion of experienced leaders in the field. Further studies are needed to reach evidence-based recommendations for the applications of [18F]FDG and radiolabelled amino acid PET in paediatric neuro-oncology. These recommendations are not intended to be a substitute for national and international legal or regulatory provisions and should be considered in the context of good practice in nuclear medicine. The present guidelines/standards were developed collaboratively by the EANM and SNMMI with the European Society for Paediatric Oncology (SIOPE) Brain Tumour Group and the Response Assessment in Paediatric Neuro-Oncology (RAPNO) working group. They summarize also the views of the Neuroimaging and Oncology and Theranostics Committees of the EANM and reflect recommendations for which the EANM and other societies cannot be held responsible.

Efficacy and tolerability of regorafenib in pretreated patients with progressive CNS grade 3 or 4 gliomas.

BACKGROUND: The phase 2 REGOMA trial suggested an encouraging overall survival benefit in glioblastoma patients at first relapse treated with the multikinase inhibitor regorafenib. Here, we evaluated the efficacy and side effects of regorafenib in a real-life setting. METHODS: From 2018 to 2021, 30 patients with progressive WHO CNS grade 3 or 4 gliomas treated with regorafenib (160 mg/day; first 3 weeks of each 4-week cycle) with individual dose adjustment depending on toxicity were retrospectively identified. Side effects were evaluated according to the Common Terminology Criteria for Adverse Events (version 5.0). MRI was obtained at baseline and after every second cycle. Tumor progression was assessed according to RANO criteria. After regorafenib initiation, the median PFS and OS were calculated. RESULTS: The median number of treatment lines before regorafenib was 2 (range 1-4). Most patients (73%) had two or more pretreatment lines. At first relapse, 27% of patients received regorafenib. A total of 94 regorafenib cycles were administered (median 2 cycles; range 1-9 cycles). Grade 3 and 4 side effects were observed in 47% and 7% of patients, respectively, and were not significantly increased in patients with two or more pretreatments (P > 0.05). The most frequent grade 3 or 4 side effects were laboratory abnormalities (62%). PFS was 2.6 months (range 0.8-8.2 months), and the OS was 6.2 months (range 0.9-24 months). CONCLUSIONS: In patients with progressive WHO grade 3 or 4 gliomas, predominantly with two pretreatment lines or more, regorafenib seems to be effective despite considerable grade 3 or 4 side effects.

Static FET PET radiomics for the differentiation of treatment-related changes from glioma progression.

PURPOSE: To investigate the potential of radiomics applied to static clinical PET data using the tracer O-(2-[18F]fluoroethyl)-L-tyrosine (FET) to differentiate treatment-related changes (TRC) from tumor progression (TP) in patients with gliomas. PATIENTS AND METHODS: One hundred fifty-one (151) patients with histologically confirmed gliomas and post-therapeutic progressive MRI findings according to the response assessment in neuro-oncology criteria underwent a dynamic amino acid PET scan using the tracer O-(2-[18F]fluoroethyl)-L-tyrosine (FET). Thereof, 124 patients were investigated on a stand-alone PET scanner (data used for model development and validation), and 27 patients on a hybrid PET/MRI scanner (data used for model testing). Mean and maximum tumor to brain ratios (TBRmean, TBRmax) were calculated using the PET data from 20 to 40 min after tracer injection. Logistic regression models were evaluated for the FET PET parameters TBRmean, TBRmax, and for radiomics features of the tumor areas as well as combinations thereof to differentiate between TP and TRC. The best performing models in the validation dataset were finally applied to the test dataset. The diagnostic performance was assessed by receiver operating characteristic analysis. RESULTS: Thirty-seven patients (25%) were diagnosed with TRC, and 114 (75%) with TP. The logistic regression model comprising the conventional FET PET parameters TBRmean and TBRmax resulted in an AUC of 0.78 in both the validation (sensitivity, 64%; specificity, 80%) and the test dataset (sensitivity, 64%; specificity, 80%). The model combining the conventional FET PET parameters and two radiomics features yielded the best diagnostic performance in the validation dataset (AUC, 0.92; sensitivity, 91%; specificity, 80%) and demonstrated its generalizability in the independent test dataset (AUC, 0.85; sensitivity, 81%; specificity, 70%). CONCLUSION: The developed radiomics classifier allows the differentiation between TRC and TP in pretreated gliomas based on routinely acquired static FET PET scans with a high diagnostic accuracy.

Radiomics in neuro-oncology: Basics, workflow, and applications.

Over the last years, the amount, variety, and complexity of neuroimaging data acquired in patients with brain tumors for routine clinical purposes and the resulting number of imaging parameters have substantially increased. Consequently, a timely and cost-effective evaluation of imaging data is hardly feasible without the support of methods from the field of artificial intelligence (AI). AI can facilitate and shorten various time-consuming steps in the image processing workflow, e.g., tumor segmentation, thereby optimizing productivity. Besides, the automated and computer-based analysis of imaging data may help to increase data comparability as it is independent of the experience level of the evaluating clinician. Importantly, AI offers the potential to extract new features from the routinely acquired neuroimages of brain tumor patients. In combination with patient data such as survival, molecular markers, or genomics, mathematical models can be generated that allow, for example, the prediction of treatment response or prognosis, as well as the noninvasive assessment of molecular markers. The subdiscipline of AI dealing with the computation, identification, and extraction of image features, as well as the generation of prognostic or predictive mathematical models, is termed radiomics. This review article summarizes the basics, the current workflow, and methods used in radiomics with a focus on feature-based radiomics in neuro-oncology and provides selected examples of its clinical application.

Sequential implementation of DSC-MR perfusion and dynamic [18F]FET PET allows efficient differentiation of glioma progression from treatment-related changes.

PURPOSE: Perfusion-weighted MRI (PWI) and O-(2-[18F]fluoroethyl-)-l-tyrosine ([18F]FET) PET are both applied to discriminate tumor progression (TP) from treatment-related changes (TRC) in patients with suspected recurrent glioma. While the combination of both methods has been reported to improve the diagnostic accuracy, the performance of a sequential implementation has not been further investigated. Therefore, we retrospectively analyzed the diagnostic value of consecutive PWI and [18F]FET PET. METHODS: We evaluated 104 patients with WHO grade II-IV glioma and suspected TP on conventional MRI using PWI and dynamic [18F]FET PET. Leakage corrected maximum relative cerebral blood volumes (rCBVmax) were obtained from dynamic susceptibility contrast PWI. Furthermore, we calculated static (i.e., maximum tumor to brain ratios; TBRmax) and dynamic [18F]FET PET parameters (i.e., Slope). Definitive diagnoses were based on histopathology (n = 42) or clinico-radiological follow-up (n = 62). The diagnostic performance of PWI and [18F]FET PET parameters to differentiate TP from TRC was evaluated by analyzing receiver operating characteristic and area under the curve (AUC). RESULTS: Across all patients, the differentiation of TP from TRC using rCBVmax or [18F]FET PET parameters was moderate (AUC = 0.69-0.75; p < 0.01). A rCBVmax cutoff > 2.85 had a positive predictive value for TP of 100%, enabling a correct TP diagnosis in 44 patients. In the remaining 60 patients, combined static and dynamic [18F]FET PET parameters (TBRmax, Slope) correctly discriminated TP and TRC in a significant 78% of patients, increasing the overall accuracy to 87%. A subgroup analysis of isocitrate dehydrogenase (IDH) mutant tumors indicated a superior performance of PWI to [18F]FET PET (AUC = 0.8/< 0.62, p < 0.01/≥ 0.3). CONCLUSION: While marked hyperperfusion on PWI indicated TP, [18F]FET PET proved beneficial to discriminate TP from TRC when PWI remained inconclusive. Thus, our results highlight the clinical value of sequential use of PWI and [18F]FET PET, allowing an economical use of diagnostic methods. The impact of an IDH mutation needs further investigation.

18F-FET-PET-guided gross total resection improves overall survival in patients with WHO grade III/IV glioma: moving towards a multimodal imaging-guided resection.

PURPOSE: PET using radiolabeled amino acid [18F]-fluoro-ethyl-L-tyrosine (FET-PET) is a well-established imaging modality for glioma diagnostics. The biological tumor volume (BTV) as depicted by FET-PET often differs in volume and location from tumor volume of contrast enhancement (CE) in MRI. Our aim was to investigate whether a gross total resection of BTVs defined as < 1 cm3 of residual BTV (PET GTR) correlates with better oncological outcome. METHODS: We retrospectively analyzed imaging and survival data from patients with primary and recurrent WHO grade III or IV gliomas who underwent FET-PET before surgical resection. Tumor overlap between FET-PET and CE was evaluated. Completeness of FET-PET resection (PET GTR) was calculated after superimposition and semi-automated segmentation of pre-operative FET-PET and postoperative MRI imaging. Survival analysis was performed using the Kaplan-Meier method and the log-rank test. RESULTS: From 30 included patients, PET GTR was achieved in 20 patients. Patients with PET GTR showed improved median OS with 19.3 compared to 13.7 months for patients with residual FET uptake (p = 0.007; HR 0.3; 95% CI 0.12-0.76). This finding remained as independent prognostic factor after performing multivariate analysis (HR 0.19, 95% CI 0.06-0.62, p = 0.006). Other survival influencing factors such as age, IDH-mutation, MGMT promotor status, and adjuvant treatment modalities were equally distributed between both groups. CONCLUSION: Our results suggest that PET GTR improves the OS in patients with WHO grade III or IV gliomas. A multimodal imaging approach including FET-PET for surgical planning in newly diagnosed and recurrent tumors may improve the oncological outcome in glioma patients.

Diagnostic impact of additional O-(2-[18F]fluoroethyl)-L-tyrosine (18F-FET) PET following immunotherapy with dendritic cell vaccination in glioblastoma patients.

OBJECTIVE: Vaccination therapy using tumour antigen-loaded, autologous dendritic cells (DC) is a promising therapeutic approach alongside standard treatment for glioblastoma (GBM). However, reliable diagnostic criteria regarding therapy monitoring are not established. Here, we analysed the impact of additional 18F-fluoroethyl-tyrosine positron emission tomography (18F-FET PET) imaging following DC vaccination therapy. METHODS: We analysed data of GBM patients who received DC vaccination therapy. Following MRI diagnosis of tumour recurrence, additional static and dynamic 18F-FET PET imaging was performed. Vaccination was performed five times by intradermal injections, either weekly between concomitant radio/-chemotherapy and intermittent chemotherapy or after tumour recurrence, before re-radiation therapy. MRI and 18F-FET PET results were compared and correlated with clinical data. RESULTS: Between 2003 and 2016, 5 patients were identified who received DC vaccination and 18F-FET PET imaging (1 female/4 males; mean age: 44 ± 14 y). 3/5 patients showed congruent results of tumour progression. In three patients 18F-FET PET indicated treatment related changes, which was in contrast to MRI findings that indicated tumour progression. In these patients 18F-FET PET results could be confirmed by either neuropathological diagnosis or according to the RANO criteria. CONCLUSIONS: Despite the small patients number our results indicate an additional impact of 18F-FET PET for monitoring outcome following vaccination therapy.

Lomustine-temozolomide combination therapy versus standard temozolomide therapy in patients with newly diagnosed glioblastoma with methylated MGMT promoter (CeTeG/NOA-09): a randomised, open-label, phase 3 trial.

BACKGROUND: There is an urgent need for more effective therapies for glioblastoma. Data from a previous unrandomised phase 2 trial suggested that lomustine-temozolomide plus radiotherapy might be superior to temozolomide chemoradiotherapy in newly diagnosed glioblastoma with methylation of the MGMT promoter. In the CeTeG/NOA-09 trial, we aimed to further investigate the effect of lomustine-temozolomide therapy in the setting of a randomised phase 3 trial. METHODS: In this open-label, randomised, phase 3 trial, we enrolled patients from 17 German university hospitals who were aged 18-70 years, with newly diagnosed glioblastoma with methylated MGMT promoter, and a Karnofsky Performance Score of 70% and higher. Patients were randomly assigned (1:1) with a predefined SAS-generated randomisation list to standard temozolomide chemoradiotherapy (75 mg/m2 per day concomitant to radiotherapy [59-60 Gy] followed by six courses of temozolomide 150-200 mg/m2 per day on the first 5 days of the 4-week course) or to up to six courses of lomustine (100 mg/m2 on day 1) plus temozolomide (100-200 mg/m2 per day on days 2-6 of the 6-week course) in addition to radiotherapy (59-60 Gy). Because of the different schedules, patients and physicians were not masked to treatment groups. The primary endpoint was overall survival in the modified intention-to-treat population, comprising all randomly assigned patients who started their allocated chemotherapy. The prespecified test for overall survival differences was a log-rank test stratified for centre and recursive partitioning analysis class. The trial is registered with ClinicalTrials.gov, number NCT01149109. FINDINGS: Between June 17, 2011, and April 8, 2014, 141 patients were randomly assigned to the treatment groups; 129 patients (63 in the temozolomide and 66 in the lomustine-temozolomide group) constituted the modified intention-to-treat population. Median overall survival was improved from 31·4 months (95% CI 27·7-47·1) with temozolomide to 48·1 months (32·6 months-not assessable) with lomustine-temozolomide (hazard ratio [HR] 0·60, 95% CI 0·35-1·03; p=0·0492 for log-rank analysis). A significant overall survival difference between groups was also found in a secondary analysis of the intention-to-treat population (n=141, HR 0·60, 95% CI 0·35-1·03; p=0·0432 for log-rank analysis). Adverse events of grade 3 or higher were observed in 32 (51%) of 63 patients in the temozolomide group and 39 (59%) of 66 patients in the lomustine-temozolomide group. There were no treatment-related deaths. INTERPRETATION: Our results suggest that lomustine-temozolomide chemotherapy might improve survival compared with temozolomide standard therapy in patients with newly diagnosed glioblastoma with methylated MGMT promoter. The findings should be interpreted with caution, owing to the small size of the trial. FUNDING: German Federal Ministry of Education and Research.