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.

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.

European survey on neurosurgical management of primary central nervous system lymphomas and preoperative corticosteroid therapy.

Introduction: Preoperative corticosteroid therapy (CST) is common in primary central nervous system lymphoma (PCNSL) and may complicate histopathological diagnosis. There is an ongoing debate on the best management after preoperative CST. Research question: We aimed to survey how different European neurosurgical units treat PCNSL patients after preoperative CST. Methods: An English-language survey consisting of 21 questions addressing the management of patients with suspected PCNSL and preoperative CST was sent to European hospitals. The survey also included three clinical cases to assess the decision-making process in a clinical setting. Results: The survey was completed by 74 European hospitals. There was no clear consensus on how to treat a patient with PCNSL after CST. Accordingly, 24.3% responded that they would generally defer surgery regardless of a possible radiological response, 47.3% would defer surgery only if there is regression in preoperative MRI and the remaining 28.4% would defer surgery only if the tumor had completely vanished. Furthermore, there were distinct discrepancies in responses of neurosurgical units regarding their general management approach and their case-based decision in the three example cases. The results of our survey also showed regional differences and differences in treatment decisions between high-, intermediate- and low-volume centers. Discussion and conclusion: There was no clear consensus on how to treat patients with suspected PCNSL and preoperative CST. Furthermore, most centers also showed inconsistencies in their responses regarding their general approach as well as individual patient treatment. More high-quality evidence-based recommendations are needed to improve consensus and thus patient care.

Network topology in brain tumor patients with and without structural epilepsy: a prospective MEG study.

Background: It was proposed that network topology is altered in brain tumor patients. However, there is no consensus on the pattern of these changes and evidence on potential drivers is lacking. Objectives: We aimed to characterize neurooncological patients' network topology by analyzing glial brain tumors (GBTs) and brain metastases (BMs) with respect to the presence of structural epilepsy. Methods: Network topology derived from resting state magnetoencephalography was compared between (1) patients and controls, (2) GBTs and BMs, and (3) patients with (PSEs) and without structural epilepsy (PNSEs). Eligible patients were investigated from February 2019 to March 2021. We calculated whole brain (WB) connectivity in six frequency bands, network topological parameters (node degree, average shortest path length, local clustering coefficient) and performed a stratification, where differences in power were identified. For data analysis, we used Fieldtrip, Brain Connectivity MATLAB toolboxes, and in-house built scripts. Results: We included 41 patients (21 men), with a mean age of 60.1 years (range 23-82), of those were: GBTs (n = 23), BMs (n = 14), and other histologies (n = 4). Statistical analysis revealed a significantly decreased WB node degree in patients versus controls in every frequency range at the corrected level (p1-30Hz = 0.002, pγ = 0.002, pß = 0.002, pα = 0.002, pθ = 0.024, and pδ = 0.002). At the descriptive level, we found a significant augmentation for WB local clustering coefficient (p1-30Hz = 0.031, pδ = 0.013) in patients compared to controls, which did not persist the false discovery rate correction. No differences regarding networks of GBTs compared to BMs were identified. However, we found a significant increase in WB local clustering coefficient (pθ = 0.048) and decrease in WB node degree (pα = 0.039) in PSEs versus PNSEs at the uncorrected level. Conclusion: Our data suggest that network topology is altered in brain tumor patients. Histology per se might not, however, tumor-related epilepsy seems to influence the brain's functional network. Longitudinal studies and analysis of possible confounders are required to substantiate these findings.

The importance of additional intracranial injuries in epidural hematomas: detailed clinical analysis, long-term outcome, and literature review in surgically managed epidural hematomas.

Objective: Epidural hematomas (EDH) occur in up to 8.2% of all traumatic brain injury patients, with more than half needing surgical treatment. In most patients suffering from this perilous disease, good recovery with an excellent clinical course is possible. However, the clinical course is mainly dependent on the presence of additional intracerebral injuries. Few studies comparing isolated and combined EDH in detail exist. Methods: We performed a retrospective single-center study from April 2002 to December 2014. The mean follow-up time was more than 6 years. In addition to analyzing diverse clinicoradiological data, we performed a systematic literature review dealing with a detailed comparison of patients with (combined) and without (isolated) additional intracerebral injuries. Results: We included 72 patients in the study. With increasing age, combined EDH had a higher incidence than isolated EDH. The mortality rate of the patients in the cohort was 10%, of which 0% had isolated EDH and 10% had combined EDH. Good recovery was achieved in 69% of patients, of which 91% had isolated EDH and 50% had combined EDH. A subgroup analysis of the different additional intracerebral injuries in combined EDH demonstrated no significant difference in outcome. A systematic literature review only identified six studies. Patients with isolated EDH had a statistically significantly lower mortality risk [relative risk (RR): 0.22; 95% CI: 0.12-0.39] and a statistically significantly lower risk of unfavorable Glasgow outcome scale score (RR: 0.21; 95% CI: 0.14-0.31) than patients with combined EDH. Conclusions: An excellent outcome in patients with surgically treated isolated EDH is possible. Furthermore, patients with combined EDH or isolated EDH with a low Glasgow coma scale (GCS) score may have favorable outcomes in 50% of the cases. Therefore, every possible effort for treatment should be made for this potentially lethal injury.

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.

Current trends and outcomes of non-elective neurosurgical care in Central Europe during the second year of the COVID-19 pandemic.

Reflecting the first wave COVID-19 pandemic in Central Europe (i.e. March 16th-April 15th, 2020) the neurosurgical community witnessed a general diminution in the incidence of emergency neurosurgical cases, which was impelled by a reduced number of traumatic brain injuries (TBI), spine conditions, and chronic subdural hematomas (CSDH). This appeared to be associated with restrictions imposed on mobility within countries but also to possible delayed patient introduction and interdisciplinary medical counseling. In response to one year of COVID-19 experience, also mapping the third wave of COVID-19 in 2021 (i.e. March 16 to April 15, 2021), we aimed to reevaluate the current prevalence and outcomes for emergency non-elective neurosurgical cases in COVID-19-negative patients across Austria and the Czech Republic. The primary analysis was focused on incidence and 30-day mortality in emergency neurosurgical cases compared to four preceding years (2017-2020). A total of 5077 neurosurgical emergency cases were reviewed. The year 2021 compared to the years 2017-2019 was not significantly related to any increased odds of 30 day mortality in Austria or in the Czech Republic. Recently, there was a significant propensity toward increased incidence rates of emergency non-elective neurosurgical cases during the third COVID-19 pandemic wave in Austria, driven by their lower incidence during the first COVID-19 wave in 2020. Selected neurosurgical conditions commonly associated with traumatic etiologies including TBI, and CSDH roughly reverted to similar incidence rates from the previous non-COVID-19 years. Further resisting the major deleterious effects of the continuing COVID-19 pandemic, it is edifying to notice that the neurosurgical community´s demeanor to the recent third pandemic culmination keeps the very high standards of non-elective neurosurgical care alongside with low periprocedural morbidity. This also reflects the current state of health care quality in the Czech Republic and Austria.

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).

Surviving the Scene in Civilian Penetrating Brain Injury: Injury Type, Cause and Outcome in a Consecutive Patient Series in Austria.

Background: Penetrating brain injury (PBI) is a heterogeneous condition with many variables. Few data exist on civilian PBI. In some publications, PBI differentiation between low-velocity injury (LVI) and high-velocity injury (HVI) is made, but exact definitions are not given yet. The incidence of PBI depends heavily on the country of origin. Furthermore, captive bolt pistol (CBP) injuries represent a rare type of LVI and almost no reports exist in the human medical literature. Treatment of PBI has been controversially discussed due to high morbidity and mortality with results varying considerably between series. Prognostic factors are of utmost importance to identify patients who presumably benefit from treatment. Methods: A retrospective, single-center analysis of a consecutive patient series was performed from September 2005 to May 2018. We included all patients with PBI who reached our hospital alive and received any neurosurgical operative procedure. Results: Of 24 patients, 38% died, 17% had an unfavourable outcome, and 46% had a favourable outcome. In total, 58% of patients with PBI were self-inflicted. Leading causes of injury were firearms, while captive bolt pistols were responsible for 21% of injuries. LVI represented 54%, and HVI represented 46%. The outcome in HVI was significantly worse than that in LVI. A favourable outcome was achieved in 69% of LVI and 18% of HVI. Low GCS and pathological pupillary status at admission correlated significantly with an unfavourable outcome and death. Conclusions: PBI is a heterogeneous injury with many variables and major geographical and etiological differences. Differentiation between LVI and HVI is crucial for decision-making and predicting outcomes. In patients presenting with object trajectories crossing the midline, no favourable outcome could be achieved. Nevertheless, in total, a favourable outcome was possible in almost half of the patients who succeeded in surgery.

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.

An Update on Neurosurgical Management of Primary CNS Lymphoma in Immunocompetent Patients.

Primary central nervous system lymphomas (PCNSL) are rare CNS tumors that harbor a conspicuously longer diagnostic delay compared to other malignant brain tumors. The gold standard for diagnosis is stereotactic biopsy to acquire tissue for histopathological analysis and therefore neurosurgery plays a central role when reducing the diagnostic period is mandated. However, histopathological diagnosis could be complicated if the patient was preoperatively exposed to corticosteroids. Besides the histopathological result, diagnosis of a PCNSL also requires full diagnostic workup to exclude cerebral metastatic disease of a systemic lymphoma. Most reviews of PCNSL discuss recent advancements in systemic treatment options from an (neuro-)oncologic viewpoint, whereas our intention was to discuss the optimization of the diagnostic period and therefore describe current standards of imaging, summarizing the diagnostic workup, discussing the surgical workup and future diagnostic prospects as well as the influence of preoperative corticosteroid therapy to reduce the diagnostic delay of PCNSL patients.

Does pigmentation, hemosiderin and blood effect visible 5-ALA fluorescence in cerebral melanoma metastasis?

INTRODUCTION: The clinical impact of 5-aminolevulinic acid (5-ALA) fluorescence during resection of brain metastases is not yet clear.. Recent data demonstrated significantly lower incidence of visible fluorescence in cerebral melanoma metastases (CMM) compared to other brain metastases (BM). The aim of this study was to investigate if characteristic melanoma features such as pigmentation, intratumoural hemosiderin and bleeding have an influence on visible fluorescence in CMM. MATERIALS AND METHODS: A retrospective study of two neurosurgical centers was performed including adult patients with resection of CMM after preoperative administration of 5-ALA. Data on the fluorescence status (visible or no fluorescence), the fluorescence quality (strong, vague, none) and fluorescence homogeneity (homogeneous or heterogeneous) of each CMM were collected. The amount of melanin, hemosiderin and intratumoural bleeding was semi-quantitatively determined and automated computer-based calculation of the relative pigmented area was performed in fluorescing and non-fluorescing CMM samples. RESULTS: Altogether, 29 CMM were surgically removed after 5-ALA administration. Visible fluorescence was detected in 8 CMM (28%), whereas no fluorescence was detected in 21 CMM (72%). In detail, 3 tumors (10%) showed strong fluorescence, 5 tumors (17%) revealed vague fluorescence and in 21 tumors (72%) no fluorescence was found. In total, 8 fluorescing and 25 non-fluorescing CMM samples were investigated. According to the semi-quantitatively calculated fluorescence status, no statistically significant difference in the median amount of melanin (p = 0.242), hemosiderin (p = 0.603) and bleeding (p = 0.762) between CMM samples with and without visible fluorescence was found. Moreover, the automatically assessed relative pigmented area did not show a statistically significant difference between samples with visible and no fluorescence (p = 0.966). CONCLUSION: Our data indicate that 5-ALA fluorescence is not dependent on the amount of pigmentation, intratumoural hemosiderin and bleeding in CMM. We thus assume that other factors are responsible for the low rate of visible fluorescence in CMM.

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.

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.

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.

Extent of spinal canal obliteration as prognostic factor for functional outcome in patients with spontaneous spinal epidural hematoma: a retrospective study.

BACKGROUND: Spontaneous spinal epidural hematoma (SSEDH) is a rare condition with potentially devastating consequences. Known prognostic factors are short time to surgery, preoperative neurologic condition, and age. The aim of this study was to investigate the impact of the transversal hematoma extent with its subsequent spinal canal obliteration on outcome in patients with SSEDH. METHODS: A retrospective study including all patients that underwent surgery due to SSEDH at the University Hospital of St. Poelten between 1/7/2005 and 30/6/2020 was conducted. The percentage of spinal canal obliteration at the level where the hematoma was most prominent was calculated and correlated to functional outcome. RESULTS: A total of 17 patients could be included in this study. Preoperative ASIA impairment scale showed positive correlation with postoperative outcome (p = 0.005). Patients with a favorable outcome (ASIA D and E) showed a statistically significant lower mean obliteration of the spinal canal by the hematoma with 46.4% (± 8%) in comparison to patients with an unfavorable outcome with 62.1% (± 6%, p = 0.001). A cut-off of 51% yielded a sensitivity and specificity for favorable outcome of 100% and 70% respectively (area under the ROC 0.93, p < 0.001). CONCLUSION: Preoperative percentage of spinal canal obliteration is statistically significant lower in patients with favorable outcome in surgically treated patients with spontaneous spinal epidural hematoma.

Nerve root herniation with entrapment in the facet joint gap after lumbar decompression surgery: a case presentation.

BACKGROUND: An incidental dural tear is a well-known complication during spine surgery. A rare consequence is a postoperative nerve root herniation. The purpose of this report is to describe a case of such a herniation with entrapment in the facet gap joint and to present the first MR images of this rare surgical complication. CASE PRESENTATION: We report a case of a patient who underwent lumbar decompression surgery and afterwards suffered a sudden intractable sciatica. Postoperative MRI showed a new facet joint gap effusion. During revision surgery an entrapped nerve root was found in the facet joint gap. In retrospective, the herniated nerve root is visible on postoperative MRI. CONCLUSION: This case report highlights a rare complication during spine surgery. This finding is important as signs suggestive for nerve root herniation can easily be overlooked on MRI. Furthermore, this represents the first MRI documentation of this complication.

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.

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.