Machine Learning-Based Prediction of Glioma IDH Gene Mutation Status Using Physio-Metabolic MRI of Oxygen Metabolism and Neovascularization (A Bicenter Study).

The mutational status of the isocitrate dehydrogenase (IDH) gene plays a key role in the treatment of glioma patients because it is known to affect energy metabolism pathways relevant to glioma. Physio-metabolic magnetic resonance imaging (MRI) enables the non-invasive analysis of oxygen metabolism and tissue hypoxia as well as associated neovascularization and microvascular architecture. However, evaluating such complex neuroimaging data requires computational support. Traditional machine learning algorithms and simple deep learning models were trained with radiomic features from clinical MRI (cMRI) or physio-metabolic MRI data. A total of 215 patients (first center: 166 participants + 16 participants for independent internal testing of the algorithms versus second site: 33 participants for independent external testing) were enrolled using two different physio-metabolic MRI protocols. The algorithms trained with physio-metabolic data demonstrated the best classification performance in independent internal testing: precision, 91.7%; accuracy, 87.5%; area under the receiver operating curve (AUROC), 0.979. In external testing, traditional machine learning models trained with cMRI data exhibited the best IDH classification results: precision, 84.9%; accuracy, 81.8%; and AUROC, 0.879. The poor performance for the physio-metabolic MRI approach appears to be explainable by site-dependent differences in data acquisition methodologies. The physio-metabolic MRI approach potentially supports reliable classification of IDH gene status in the presurgical stage of glioma patients. However, non-standardized protocols limit the level of evidence and underlie the need for a reproducible framework of data acquisition techniques.

New insights into neuropathology and pathogenesis of autoimmune glial fibrillary acidic protein meningoencephalomyelitis.

Anti-glial fibrillary acidic protein (GFAP) meningoencephalomyelitis (autoimmune GFAP astrocytopathy) is a new autoimmune central nervous system (CNS) disease diagnosable by the presence of anti-GFAP autoantibodies in the cerebrospinal fluid and presents as meningoencephalomyelitis in the majority of patients. Only few neuropathological reports are available and little is known about the pathogenic mechanisms. We performed a histopathological study of two autopsies and nine CNS biopsies of patients with anti-GFAP autoantibodies and found predominantly a lymphocytic and in one autopsy case a granulomatous inflammatory phenotype. Inflammatory infiltrates were composed of B and T cells, including tissue-resident memory T cells. Although obvious astrocytic damage was absent in the GFAP-staining, we found cytotoxic T cell-mediated reactions reflected by the presence of CD8+/perforin+/granzyme A/B+ cells, polarized towards astrocytes. MHC-class-I was upregulated in reactive astrocytes of all biopsies and two autopsies but not in healthy controls. Importantly, we observed a prominent immunoreactivity of astrocytes with the complement factor C4d. Finally, we provided insight into an early phase of GFAP autoimmunity in an autopsy of a pug dog encephalitis that was characterized by marked meningoencephalitis with selective astrocytic damage with loss of GFAP and AQP4 in the lesions.Our histopathological findings indicate that a cytotoxic T cell-mediated immune reaction is present in GFAP autoimmunity. Complement C4d deposition on astrocytes could either represent the cause or consequence of astrocytic reactivity. Selective astrocytic damage is prominent in the early phase of GFAP autoimmunity in a canine autopsy case, but mild or absent in subacute and chronic stages in human disease, probably due to the high regeneration potential of astrocytes. The lymphocytic and granulomatous phenotypes might reflect different stages of lesion development or patient-specific modifications of the immune response. Future studies will be necessary to investigate possible implications of pathological subtypes for clinical disease course and therapeutic strategies.

Anti-Ri paraneoplastic neurological syndrome presenting with bilateral cranial nerve VI palsy and jaw dystonia-a distinctive syndrome within the anti-Ri spectrum? : Case report and literature review.

OBJECTIVE: Paraneoplastic neurological syndromes (PNS) are rare disorders associated with various onconeuronal antibodies. Anti-Ri antibodies (ANNA-2) are typically found in patients with opsoclonus myoclonus syndrome (OMS) and ataxia. CASE REPORT: We present an anti-Ri antibody-positive 77-year-old woman with subacute progressive bilateral cranial nerve VI palsy, gait disturbance and jaw dystonia. MRI of the brain showed hyperintense signals on T2 bitemporal without contrast enhancement. Cerebrospinal fluid (CSF) examination exhibited mild pleocytosis of 13 cells/µl and positive oligoclonal bands. CSF was overall inconspicuous for a malignant or inflammatory etiology. Immunofluorescence analysis revealed anti-Ri antibodies in both serum and CSF. Subsequent diagnostic work up resulted in a newly diagnosed ductal carcinoma of the right breast. PNS in this case partially responded to the anti-tumor therapy. CONCLUSION: This case shows similarities with recently published anti-Ri syndromes, which might form a distinct triad within the anti-Ri spectrum.

Radiomic features define risk and are linked to DNA methylation attributes in primary CNS lymphoma.

Background: The prognostic roles of clinical and laboratory markers have been exploited to model risk in patients with primary CNS lymphoma, but these approaches do not fully explain the observed variation in outcome. To date, neuroimaging or molecular information is not used. The aim of this study was to determine the utility of radiomic features to capture clinically relevant phenotypes, and to link those to molecular profiles for enhanced risk stratification. Methods: In this retrospective study, we investigated 133 patients across 9 sites in Austria (2005-2018) and an external validation site in South Korea (44 patients, 2013-2016). We used T1-weighted contrast-enhanced MRI and an L1-norm regularized Cox proportional hazard model to derive a radiomic risk score. We integrated radiomic features with DNA methylation profiles using machine learning-based prediction, and validated the most relevant biological associations in tissues and cell lines. Results: The radiomic risk score, consisting of 20 mostly textural features, was a strong and independent predictor of survival (multivariate hazard ratio = 6.56 [3.64-11.81]) that remained valid in the external validation cohort. Radiomic features captured gene regulatory differences such as in BCL6 binding activity, which was put forth as testable treatment target for a subset of patients. Conclusions: The radiomic risk score was a robust and complementary predictor of survival and reflected characteristics in underlying DNA methylation patterns. Leveraging imaging phenotypes to assess risk and inform epigenetic treatment targets provides a concept on which to advance prognostic modeling and precision therapy for this aggressive cancer.

Differentiation of Glioblastoma and Brain Metastases by MRI-Based Oxygen Metabolomic Radiomics and Deep Learning.

Glioblastoma (GB) and brain metastasis (BM) are the most frequent types of brain tumors in adults. Their therapeutic management is quite different and a quick and reliable initial characterization has a significant impact on clinical outcomes. However, the differentiation of GB and BM remains a major challenge in today's clinical neurooncology due to their very similar appearance in conventional magnetic resonance imaging (MRI). Novel metabolic neuroimaging has proven useful for improving diagnostic performance but requires artificial intelligence for implementation in clinical routines. Here; we investigated whether the combination of radiomic features from MR-based oxygen metabolism ("oxygen metabolic radiomics") and deep convolutional neural networks (CNNs) can support reliably pre-therapeutic differentiation of GB and BM in a clinical setting. A self-developed one-dimensional CNN combined with radiomic features from the cerebral metabolic rate of oxygen (CMRO2) was clearly superior to human reading in all parameters for classification performance. The radiomic features for tissue oxygen saturation (mitoPO2; i.e., tissue hypoxia) also showed better diagnostic performance compared to the radiologists. Interestingly, both the mean and median values for quantitative CMRO2 and mitoPO2 values did not differ significantly between GB and BM. This demonstrates that the combination of radiomic features and DL algorithms is more efficient for class differentiation than the comparison of mean or median values. Oxygen metabolic radiomics and deep neural networks provide insights into brain tumor phenotype that may have important diagnostic implications and helpful in clinical routine diagnosis.

Real-time monitoring of intravenous thrombolysis in acute ischemic stroke using rotational thromboelastometry: a feasibility pilot study.

INTRODUCTION: Rotational thromboelastometry (ROTEM) records whole blood coagulation in vitro. Data on dynamic changes of clot patterns during intravenous thrombolysis (IVT) in acute ischemic stroke is scarce. We investigated the feasibility of ROTEM as a potential point-of-care assessment tool for IVT. METHODS: In this prospective pilot study, patients with acute stroke symptoms received IVT. Whole blood coagulation was tracked on the ROTEM analyzer. Blood samples were analyzed before, and then 2, 15, 30 and 60 min after beginning IVT. In vitro clots (iCLs) were described by their maximum clot firmness (MCF), the time needed to reach MCF (MCF-t), as well as the area under the curve (AR10). National Institutes of Health Stroke Scale (NIHSS) was used as early clinical outcome parameter. RESULTS: We analyzed 288 iCLs from 12 patients undergoing IVT. In all iCLs, an early fibrinolysis (91% within the first 10 min) was detected during IVT. Three different curve progression patterns were observed: a low-responder pattern with a continuous clot increase, a high-responder pattern with a sustained clot decrease or total clotting suppression and an intermediate-responder pattern with alternating clot characteristics. There was a difference among these groups in early clinical outcome (AR10 and MCF each p = 0.01, MCF-t p = 0.02, Kruskal-Wallis Test). CONCLUSION: The fibrinolysis patterns determined using ROTEM allow for the monitoring of IVT in patients with acute ischemic stroke. This pilot study found a correlation between the in vitro fibrinolysis patterns and early clinical outcomes. These findings support a potential for individualization of IVT in the future.

Perioperative levetiracetam for seizure prophylaxis in seizure-naive brain tumor patients with focus on neurocognitive functioning.

INTRODUCTION: In seizure-naive brain tumor patients, the efficacy of perioperative prophylactic antiepileptic drug treatment remains controversial. In case of administration, the common preferred drug is levetiracetam (LEV) because of its favorable pharmacological profile. Research to date has not sufficiently determined how LEV affects cognition in the short term, as is the case in the perioperative period. The objective of this prospective study was to examine the neurocognitive functioning of seizure-naive brain tumor patients after receiving LEV perioperatively. METHODS: Fortythree patients with supratentorial brain tumor scheduled for surgery received LEV three days before until six days after surgery as seizure prophylaxis. Cognitive functioning (NeuroCogFX), LEV plasma-levels, hematotoxicity, side-effects, as well as health-related quality of life (HRQoL, Qolie31), were recorded preoperatively before (Baseline) and after onset of LEV (Pre-Op), 4-6 days postoperatively (Post-Op) and 21 days postoperatively (Follow-Up). RESULTS: No significant changes in cognitive functioning and HRQoL were seen after onset of preoperative LEV. There was a significant improvement of NeuroCogFX total-score at Follow-Up (p = 0.004) compared to Baseline. The overall-score Qolie31 showed simultaneous improvement patterns as cognitive functioning (p < 0.001). The most frequent side effect related to study drug was somnolence (in 28.6% of patients). CONCLUSIONS: A significant improvement of cognitive functioning, as well as an improvement in HRQoL, were detected postoperatively. This is presumably due to the debulking effect of the surgery. Nevertheless, LEV has no detrimental effect on cognitive functioning in the perioperative phase in seizure-naive brain tumor patients. TRIAL REGISTRATION: This study was registered prospectively (Date: 25/11/2015; EudraCT: 2015-003,916-19).

Radiophysiomics: Brain Tumors Classification by Machine Learning and Physiological MRI Data.

The precise initial characterization of contrast-enhancing brain tumors has significant consequences for clinical outcomes. Various novel neuroimaging methods have been developed to increase the specificity of conventional magnetic resonance imaging (cMRI) but also the increased complexity of data analysis. Artificial intelligence offers new options to manage this challenge in clinical settings. Here, we investigated whether multiclass machine learning (ML) algorithms applied to a high-dimensional panel of radiomic features from advanced MRI (advMRI) and physiological MRI (phyMRI; thus, radiophysiomics) could reliably classify contrast-enhancing brain tumors. The recently developed phyMRI technique enables the quantitative assessment of microvascular architecture, neovascularization, oxygen metabolism, and tissue hypoxia. A training cohort of 167 patients suffering from one of the five most common brain tumor entities (glioblastoma, anaplastic glioma, meningioma, primary CNS lymphoma, or brain metastasis), combined with nine common ML algorithms, was used to develop overall 135 classifiers. Multiclass classification performance was investigated using tenfold cross-validation and an independent test cohort. Adaptive boosting and random forest in combination with advMRI and phyMRI data were superior to human reading in accuracy (0.875 vs. 0.850), precision (0.862 vs. 0.798), F-score (0.774 vs. 0.740), AUROC (0.886 vs. 0.813), and classification error (5 vs. 6). The radiologists, however, showed a higher sensitivity (0.767 vs. 0.750) and specificity (0.925 vs. 0.902). We demonstrated that ML-based radiophysiomics could be helpful in the clinical routine diagnosis of contrast-enhancing brain tumors; however, a high expenditure of time and work for data preprocessing requires the inclusion of deep neural networks.

MRI Response Assessment in Glioblastoma Patients Treated with Dendritic-Cell-Based Immunotherapy.

Introduction: In this post hoc analysis we compared various response-assessment criteria in newly diagnosed glioblastoma (GB) patients treated with tumor lysate-charged autologous dendritic cells (Audencel) and determined the differences in prediction of progression-free survival (PFS) and overall survival (OS). Methods: 76 patients enrolled in a multicenter phase II trial receiving standard of care (SOC, n = 40) or SOC + Audencel vaccine (n = 36) were included. MRI scans were evaluated using MacDonald, RANO, Vol-RANO, mRANO, Vol-mRANO and iRANO criteria. Tumor volumes (T1 contrast-enhancing as well as T2/FLAIR volumes) were calculated by semiautomatic segmentation. The Kruskal-Wallis-test was used to detect differences in PFS among the assessment criteria; for correlation analysis the Spearman test was used. Results: There was a significant difference in median PFS between mRANO (8.6 months) and Vol-mRANO (8.6 months) compared to MacDonald (4.0 months), RANO (4.2 months) and Vol-RANO (5.4 months). For the vaccination arm, median PFS by iRANO was 6.2 months. There was no difference in PFS between SOC and SOC + Audencel. The best correlation between PFS/OS was detected for mRANO (r = 0.65) and Vol-mRANO (r = 0.69, each p < 0.001). A total of 16/76 patients developed a pure T2/FLAIR progressing disease, and 4/36 patients treated with Audencel developed pseudoprogression. Conclusion: When comparing different response-assessment criteria in GB patients treated with dendritic cell-based immunotherapy, the best correlation between PFS and OS was observed for mRANO and Vol-mRANO. Interestingly, iRANO was not superior for predicting OS in patients treated with Audencel.

Physiological MRI of microvascular architecture, neovascularization activity, and oxygen metabolism facilitate early recurrence detection in patients with IDH-mutant WHO grade 3 glioma.

PURPOSE: This study aimed to determine the diagnostic performance of physiological MRI biomarkers including microvascular perfusion and architecture, neovascularization activity, tissue oxygen metabolism, and tension for recurrence detection of IDH-mutant WHO grade 3 glioma. METHODS: Sixty patients with IDH-mutant WHO grade 3 glioma who received overall 288 follow-up MRI examinations at 3 Tesla after standard treatment were retrospectively evaluated. A conventional MRI protocol was extended with a physiological MRI approach including vascular architecture mapping and quantitative blood-oxygen-level-dependent imaging which required 7 min extra data acquisition time. Custom-made MATLAB software was used for the calculation of MRI biomarker maps of microvascular perfusion and architecture, neovascularization activity, tissue oxygen metabolism, and tension. Statistical procedures included receiver operating characteristic analysis. RESULTS: Overall, 34 patients showed recurrence of the WHO grade 3 glioma; of these, in 15 patients, recurrence was detected one follow-up examination (averaged 160 days) earlier by physiological MRI data than by conventional MRI. During this time period, the tumor volume increased significantly (P = 0.001) on average 7.4-fold from 1.5 to 11.1 cm3. Quantitative analysis of MRI biomarkers demonstrated microvascular but no macrovascular hyperperfusion in early recurrence. Neovascularization activity (AUC = 0.833), microvascular perfusion (0.682), and oxygen metabolism (0.661) showed higher diagnostic performance for early recurrence detection of WHO grade 3 glioma compared to conventional MRI including cerebral blood volume (0.649). CONCLUSION: This study demonstrated that the targeted assessment of microvascular features and tissue oxygen tension as an early sign of neovascularization activity provided valuable information for recurrence diagnostic of WHO grade 3 glioma.

The meningioma surface factor: a novel approach to quantify shape irregularity on preoperative imaging and its correlation with WHO grade.

OBJECTIVE: Atypical and anaplastic meningiomas account for 20% of all meningiomas. An irregular tumor shape on preoperative MRI has been associated with WHO grade II-III histology. However, this subjective allocation does not allow quantification or comparison. An objective parameter of irregularity could substantially influence resection strategy toward a more aggressive approach. Therefore, the aim of this study was to objectively quantify the level of irregularity on preoperative MRI and predict histology based on WHO grade using this novel approach. METHODS: A retrospective study on meningiomas resected between January 2010 and December 2018 was conducted at two neurosurgical centers. This novel approach relies on the theory that a regularly shaped tumor has a smaller surface area than an irregularly shaped tumor with the same volume. A factor was generated using the surface area of a corresponding sphere as a reference, because for a given volume a sphere represents the shape with the smallest surface area possible. Consequently, the surface factor (SF) was calculated by dividing the surface area of a sphere with the same volume as the tumor with the surface area of the tumor. The resulting value of the SF ranges from > 0 to 1. Finally, the SF of each meningioma was then correlated with the corresponding histopathological grading. RESULTS: A total of 126 patients were included in this study; 60.3% had a WHO grade I, 34.9% a WHO grade II, and 4.8% a WHO grade III meningioma. Calculation of the SF demonstrated a significant difference in SFs between WHO grade I (SF 0.851) and WHO grade II-III meningiomas (SF 0.788) (p < 0.001). Multivariate analysis identified SF as an independent prognostic factor for WHO grade (OR 0.000009, 95% CI 0.000-0.159; p = 0.020). CONCLUSIONS: The SF is a proposed mathematical model for a quantitative and objective measurement of meningioma shape, instead of the present subjective assessment. This study revealed significant differences between the SFs of WHO grade I and WHO grade II-III meningiomas and demonstrated that SF is an independent prognostic factor for WHO grade.

Metabolic Tumor Microenvironment Characterization of Contrast Enhancing Brain Tumors Using Physiologic MRI.

The tumor microenvironment is a critical regulator of cancer development and progression as well as treatment response and resistance in brain neoplasms. The available techniques for investigation, however, are not well suited for noninvasive in vivo characterization in humans. A total of 120 patients (59 females; 61 males) with newly diagnosed contrast-enhancing brain tumors (64 glioblastoma, 20 brain metastases, 15 primary central nervous system (CNS) lymphomas (PCNSLs), and 21 meningiomas) were examined with a previously established physiological MRI protocol including quantitative blood-oxygen-level-dependent imaging and vascular architecture mapping. Six MRI biomarker maps for oxygen metabolism and neovascularization were fused for classification of five different tumor microenvironments: glycolysis, oxidative phosphorylation (OxPhos), hypoxia with/without neovascularization, and necrosis. Glioblastoma showed the highest metabolic heterogeneity followed by brain metastasis with a glycolysis-to-OxPhos ratio of approximately 2:1 in both tumor entities. In addition, glioblastoma revealed a significant higher percentage of hypoxia (24%) compared to all three other brain tumor entities: brain metastasis (7%; p < 0.001), PCNSL (8%; p = 0.001), and meningioma (8%; p = 0.003). A more aggressive biological brain tumor behavior was associated with a higher percentage of hypoxia and necrosis and a lower percentage of remaining vital tumor tissue and aerobic glycolysis. The proportion of oxidative phosphorylation, however, was rather similar (17-26%) for all four brain tumor entities. Tumor microenvironment (TME) mapping provides insights into neurobiological differences of contrast-enhancing brain tumors and deserves further clinical cancer research attention. Although there is a long roadmap ahead, TME mapping may become useful in order to develop new diagnostic and therapeutic approaches.

Influence of preoperative corticosteroid treatment on rate of diagnostic surgeries in primary central nervous system lymphoma: a multicenter retrospective study.

BACKGROUND: Corticosteroid therapy (CST) prior to biopsy may hinder histopathological diagnosis in primary central nervous system lymphoma (PCNSL). Therefore, preoperative CST in patients with suspected PCNSL should be avoided if clinically possible. The aim of this study was thus to analyze the difference in the rate of diagnostic surgeries in PCNSL patients with and without preoperative CST. METHODS: A multicenter retrospective study including all immunocompetent patients diagnosed with PCNSL between 1/2004 and 9/2018 at four neurosurgical centers in Austria was conducted and the results were compared to literature. RESULTS: A total of 143 patients were included in this study. All patients showed visible contrast enhancement on preoperative MRI. There was no statistically significant difference in the rate of diagnostic surgeries with and without preoperative CST with 97.1% (68/70) and 97.3% (71/73), respectively (p = 1.0). Tapering and pause of CST did not influence the diagnostic rate. Including our study, there are 788 PCNSL patients described in literature with an odds ratio for inconclusive surgeries after CST of 3.3 (CI 1.7-6.4). CONCLUSIONS: Preoperative CST should be avoided as it seems to diminish the diagnostic rate of biopsy in PCNSL patients. Yet, if CST has been administered preoperatively and there is still a contrast enhancing lesion to target for biopsy, surgeons should try to keep the diagnostic delay to a minimum as the likelihood for acquiring diagnostic tissue seems sufficiently high.

Functional Recovery in Autoimmune Encephalitis: A Prospective Observational Study.

Background: Prospective observations of functional recovery are lacking in patients with autoimmune encephalitis defined by antibodies against synaptic proteins and neuronal cell surface receptors. Methods: Adult patients with a diagnosis of autoimmune encephalitis were included into a prospective registry. At 3, 6 and 12 months of follow-up, the patients' modified Rankin Scale (mRS) was obtained. Results: Patients were stratified into three groups according to their antibody (Ab) status: anti-NMDAR-Ab (n=12; group I), anti-LGI1/CASPR2-Ab (n=35; group II), and other antibodies (n=24; group III). A comparably higher proportion of patients in group I received plasma exchange/immunoadsorption and second line immunosuppressive treatments at baseline. A higher proportion of patients in group II presented with seizures. Group III mainly included patients with anti-GABABR-, anti-GAD65- and anti-GlyR-Ab. At baseline, one third of them had cancer. Patients in groups I and III had much higher median mRS scores at 3 months compared to patients in group II. A median mRS of 1 was found at all follow-up time points in group II. Conclusions: The different dynamics in the recovery of patients with certain autoimmune encephalitides have important implications for clinical trials. The high proportion of patients with significant disability at 3 months after diagnosis in groups I and III points to the need for improving treatment options. More distinct scores rather than the mRS are necessary to differentiate potential neurological improvements in patients with anti-LGI1-/CASPR2-encephalitis.

Hypoxia and Microvascular Alterations Are Early Predictors of IDH-Mutated Anaplastic Glioma Recurrence.

Anaplastic gliomas (AG) represents aggressive brain tumors that often affect young adults. Although isocitrate-dehydrogenase (IDH) gene mutation has been identified as a more favorable prognostic factor, most IDH-mutated AG patients are confronted with tumor recurrence. Hence, increased knowledge about pathophysiological precursors of AG recurrence is urgently needed in order to develop precise diagnostic monitoring and tailored therapeutic approaches. In this study, 142 physiological magnetic resonance imaging (phyMRI) follow-up examinations in 60 AG patients after standard therapy were evaluated and magnetic resonance imaging (MRI) biomarker maps for microvascular architecture and perfusion, neovascularization activity, oxygen metabolism, and hypoxia calculated. From these 60 patients, 34 patients developed recurrence of the AG, and 26 patients showed no signs for AG recurrence during the study period. The time courses of MRI biomarker changes were analyzed regarding early pathophysiological alterations over a one-year period before radiological AG recurrence or a one-year period of stable disease for patients without recurrence, respectively. We detected intensifying local tissue hypoxia 250 days prior to radiological recurrence which initiated upregulation of neovascularization activity 50 to 70 days later. These changes were associated with a switch from an avascular infiltrative to a vascularized proliferative phenotype of the tumor cells another 30 days later. The dynamic changes of blood perfusion, microvessel density, neovascularization activity, and oxygen metabolism showed a close physiological interplay in the one-year period prior to radiological recurrence of IDH-mutated AG. These findings may path the wave for implementing both new MR-based imaging modalities for routine follow-up monitoring of AG patients after standard therapy and furthermore may support the development of novel, tailored therapy options in recurrent AG.

Multimodal assessment of disease activity in glioblastoma : A single center experience.

BACKGROUND: Assessment of disease activity in glioblastoma (GBM) can be challenging due to several clinical and radiological pitfalls. Besides MRI, FET-PET and neurocognitive assessment (NA) are used in several neuro-oncological centers in order to improve the specificity of response assessment. We performed a retrospective study to investigate whether the assessment by RANO (Response Assessment in NeuroOncology) corresponds to FET-PET imaging and NA results. Moreover, the concordance of RANO with a final recommendation of an interdisciplinary neuro-oncological tumor board recommendation (TBR) was analyzed. METHODS: We enrolled 25 consecutive patients with newly diagnosed histologically confirmed GBM in a pilot study, accounting for 81 multimodal test results. All patients were selected after undergoing consecutive follow-up comprising MRI, FET-PET, and NA with a subsequent TBR. Results were analyzed for correlations between RANO, FET-PET and NA. An additional consistency analysis was performed to elucidate the impact of RANO on decision making. RESULTS: A highly statistically significant correlation was found between RANO and FET-PET and NA results (all P < 0.01); however, 26% of follow-up tests exhibited inconsistent results in multimodal assessment, among which RANO was only 48% in accordance with the final TBR. The concordance of NA and FET-PET with the final TBR was 67% and 86%, respectively. CONCLUSION: The RANO proved its value in the context of multimodal assessment of disease activity in GBM; however, because the implementation of multimodal assessment showed a considerably high percentage of inconsistent results, further studies are required to investigate the relationship between different assessment techniques, in addition to their overall significance to response rating.

Tissue Hypoxia and Alterations in Microvascular Architecture Predict Glioblastoma Recurrence in Humans.

PURPOSE: Insufficient control of infiltrative glioblastoma (GBM) cells is a major cause of treatment failure and tumor recurrence. Hence, detailed insights into pathophysiologic changes that precede GBM recurrence are needed to develop more precise neuroimaging modalities for tailored diagnostic monitoring and therapeutic approaches. EXPERIMENTAL DESIGN: Overall, 168 physiologic MRI follow-up examinations of 56 patients with GBM who developed recurrence after standard therapy were retrospectively evaluated, that is, two post-standard-therapeutic follow-ups before and one at radiological recurrence. MRI biomarkers for microvascular architecture and perfusion, neovascularization activity, oxygen metabolism, and hypoxia were determined for brain areas that developed in the further course into recurrence and for the recurrent GBM itself. The temporal pattern of biomarker changes was fitted with locally estimated scatterplot smoothing functions and analyzed for pathophysiologic changes preceding radiological GBM recurrence. RESULTS: Our MRI approach demonstrated early pathophysiologic changes prior to radiological GBM recurrence in all patients. Analysis of the time courses revealed a model for the pathophysiology of GBM recurrence: 190 days prior to radiological recurrence, vascular cooption by GBM cells induced vessel regression, detected as decreasing vessel density/perfusion and increasing hypoxia. Seventy days later, neovascularization activity was upregulated, which reincreased vessel density and perfusion. Hypoxia, however, continued to intensify for 30 days and peaked 90 days before radiological recurrence. CONCLUSIONS: Hypoxia may represent an early sign for GBM recurrence. This might become useful in the development of new combined diagnostic-therapeutic approaches for tailored clinical management of recurrent GBM. Further preclinical and in-human studies are required for validation and evaluation.

Determining medical decision-making capacity in brain tumor patients: why and how?

BACKGROUND: Brain tumor patients are at high risk of impaired medical decision-making capacity (MDC), which can be ethically challenging because it limits their ability to give informed consent to medical treatments or participation in research. The European Association of Neuro-Oncology Palliative Care Multidisciplinary Task Force performed a systematic review to identify relevant evidence with respect to MDC that could be used to give recommendations on how to cope with reduced MDC in brain tumor patients. METHODS: A literature search in several electronic databases was conducted up to September 2019, including studies with brain tumor and other neurological patients. Information related to the following topics was extracted: tools to measure MDC, consent to treatment or research, predictive patient- and treatment-related factors, surrogate decision making, and interventions to improve MDC. RESULTS: A total of 138 articles were deemed eligible. Several structured capacity-assessment instruments are available to aid clinical decision making. These instruments revealed a high incidence of impaired MDC both in brain tumors and other neurological diseases for treatment- and research-related decisions. Incapacity appeared to be mostly determined by the level of cognitive impairment. Surrogate decision making should be considered in case a patient lacks capacity, ensuring that the patient's "best interests" and wishes are guaranteed. Several methods are available that may help to enhance patients' consent capacity. CONCLUSIONS: Clinical recommendations on how to detect and manage reduced MDC in brain tumor patients were formulated, reflecting among others the timing of MDC assessments, methods to enhance patients' consent capacity, and alternative procedures, including surrogate consent.

Clinical characteristics and prognostic factors of adult patients with pilocytic astrocytoma.

INTRODUCTION: Pilocytic astrocytoma (PA) is the most common primary brain neoplasm in children and treated in curative intent with gross total resection (GTR). However, PA is rare in adults, resulting in limited knowledge on the natural clinical course. This study aimed to describe the clinical course and identify prognostic factors of adult patients with PA. METHODS: 46 patients ≥ 18 years at diagnosis of PA and neurosurgical resection or biopsy between 2000 and 2018 were identified from the Neuro-Biobank of the Medical University of Vienna. In two cases with differing histopathological diagnosis at recurrence, DNA methylation analysis was performed using Illumina Infinium HumanMethylation850 BeadChip (850 k) arrays and the Molecular Neuropathology classifier. Clinico-pathological features were correlated with patient outcomes. RESULTS: Median age at diagnosis was 32.5 years (range: 19-75) and median Ki67 proliferation index was 2.8% (0.5-13.4%). Tumor location significantly correlated with resectability (p < 0.001). Tumor progression or recurrence was observed in 9/46 (19.6%) patients after a median follow up time of 53.0 months (range 0.5-300). 5-year overall and progression-free survival rates were 85.3% and 70.0%, respectively. 2/9 (22.2%) patients presented with histological changes in the recurrent tumor specimen. In detail, methylation classification redefined the histological diagnosis to anaplastic astrocytoma with piloid features and glioma in one patient, each. Age > 40 and higher body mass index (BMI) were associated with impaired progression-free and overall survival (p < 0.05). CONCLUSIONS: Tumor recurrence or progression in adult PA patients was higher than the one reported in pediatric patients. Higher age and BMI were associated with impaired prognosis.