Clusters of resilience and vulnerability: executive functioning, coping and mental distress in patients with diffuse low-grade glioma.

PURPOSE: Diffuse low-grade gliomas (dLGG) often have a frontal location, which may negatively affect patients' executive functions (EF). Being diagnosed with dLGG and having to undergo intensive treatment can be emotionally stressful. The ability to cope with this stress in an adaptive, active and flexible way may be hampered by impaired EF. Consequently, patients may suffer from increased mental distress. The aim of the present study was to explore profiles of EF, coping and mental distress and identify characteristics of each profile. METHODS: 151 patients with dLGG were included. Latent profile analysis (LPA) was used to explore profiles. Additional demographical, tumor and radiological characteristics were included. RESULTS: Four clusters were found: 1) overall good functioning (25% of patients); 2) poor executive functioning, good psychosocial functioning (32%); 3) good executive functioning, poor psychosocial functioning (18%) and; 4) overall poor functioning (25%). Characteristics of the different clusters were lower educational level and more (micro)vascular brain damage (cluster 2), a younger age (cluster 3), and a larger tumor volume (cluster 4). EF was not a distinctive factor for coping, nor was it for mental distress. Maladaptive coping, however, did distinguish clusters with higher mental distress (cluster 3 and 4) from clusters with lower levels of mental distress (cluster 1 and 2). CONCLUSION: Four distinctive clusters with different levels of functioning and characteristics were identified. EF impairments did not hinder the use of active coping strategies. Moreover, maladaptive coping, but not EF impairment, was related to increased mental distress in patients with dLGG.

Between-hospital variation in rates of complications and decline of patient performance after glioblastoma surgery in the dutch Quality Registry Neuro Surgery.

INTRODUCTION: For decisions on glioblastoma surgery, the risk of complications and decline in performance is decisive. In this study, we determine the rate of complications and performance decline after resections and biopsies in a national quality registry, their risk factors and the risk-standardized variation between institutions. METHODS: Data from all 3288 adults with first-time glioblastoma surgery at 13 hospitals were obtained from a prospective population-based Quality Registry Neuro Surgery in the Netherlands between 2013 and 2017. Patients were stratified by biopsies and resections. Complications were categorized as Clavien-Dindo grades II and higher. Performance decline was considered a deterioration of more than 10 Karnofsky points at 6 weeks. Risk factors were evaluated in multivariable logistic regression analysis. Patient-specific expected and observed complications and performance declines were summarized for institutions and analyzed in funnel plots. RESULTS: For 2271 resections, the overall complication rate was 20 % and 16 % declined in performance. For 1017 biopsies, the overall complication rate was 11 % and 30 % declined in performance. Patient-related characteristics were significant risk factors for complications and performance decline, i.e. higher age, lower baseline Karnofsky, higher ASA classification, and the surgical procedure. Hospital characteristics, i.e. case volume, university affiliation and biopsy percentage, were not. In three institutes the observed complication rate was significantly less than expected. In one institute significantly more performance declines were observed than expected, and in one institute significantly less. CONCLUSIONS: Patient characteristics, but not case volume, were risk factors for complications and performance decline after glioblastoma surgery. After risk-standardization, hospitals varied in complications and performance declines.

Comparing navigated transcranial magnetic stimulation mapping and "gold standard" direct cortical stimulation mapping in neurosurgery: a systematic review.

The objective of this systematic review is to create an overview of the literature on the comparison of navigated transcranial magnetic stimulation (nTMS) as a mapping tool to the current gold standard, which is (intraoperative) direct cortical stimulation (DCS) mapping. A search in the databases of PubMed, EMBASE, and Web of Science was performed. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and recommendations were used. Thirty-five publications were included in the review, describing a total of 552 patients. All studies concerned either mapping of motor or language function. No comparative data for nTMS and DCS for other neurological functions were found. For motor mapping, the distances between the cortical representation of the different muscle groups identified by nTMS and DCS varied between 2 and 16 mm. Regarding mapping of language function, solely an object naming task was performed in the comparative studies on nTMS and DCS. Sensitivity and specificity ranged from 10 to 100% and 13.3-98%, respectively, when nTMS language mapping was compared with DCS mapping. The positive predictive value (PPV) and negative predictive value (NPV) ranged from 17 to 75% and 57-100% respectively. The available evidence for nTMS as a mapping modality for motor and language function is discussed.

Between-hospital variation in mortality and survival after glioblastoma surgery in the Dutch Quality Registry for Neuro Surgery.

PURPOSE: Standards for surgical decisions are unavailable, hence treatment decisions can be personalized, but also introduce variation in treatment and outcome. National registrations seek to monitor healthcare quality. The goal of the study is to measure between-hospital variation in risk-standardized survival outcome after glioblastoma surgery and to explore the association between survival and hospital characteristics in conjunction with patient-related risk factors. METHODS: Data of 2,409 adults with first-time glioblastoma surgery at 14 hospitals were obtained from a comprehensive, prospective population-based Quality Registry Neuro Surgery in The Netherlands between 2011 and 2014. We compared the observed survival with patient-specific risk-standardized expected early (30-day) mortality and late (2-year) survival, based on age, performance, and treatment year. We analyzed funnel plots, logistic regression and proportional hazards models. RESULTS: Overall 30-day mortality was 5.2% and overall 2-year survival was 13.5%. Median survival varied between 4.8 and 14.9 months among hospitals, and biopsy percentages ranged between 16 and 73%. One hospital had lower than expected early mortality, and four hospitals had lower than expected late survival. Higher case volume was related with lower early mortality (P = 0.031). Patient-related risk factors (lower age; better performance; more recent years of treatment) were significantly associated with longer overall survival. Of the hospital characteristics, longer overall survival was associated with lower biopsy percentage (HR 2.09, 1.34-3.26, P = 0.001), and not with academic setting, nor with case volume. CONCLUSIONS: Hospitals vary more in late survival than early mortality after glioblastoma surgery. Widely varying biopsy percentages indicate treatment variation. Patient-related factors have a stronger association with overall survival than hospital-related factors.

Serial FLT PET imaging to discriminate between true progression and pseudoprogression in patients with newly diagnosed glioblastoma: a long-term follow-up study.

PURPOSE: Response evaluation in patients with glioblastoma after chemoradiotherapy is challenging due to progressive, contrast-enhancing lesions on MRI that do not reflect true tumour progression. In this study, we prospectively evaluated the ability of the PET tracer 18F-fluorothymidine (FLT), a tracer reflecting proliferative activity, to discriminate between true progression and pseudoprogression in newly diagnosed glioblastoma patients treated with chemoradiotherapy. METHODS: FLT PET and MRI scans were performed before and 4 weeks after chemoradiotherapy. MRI scans were also performed after three cycles of adjuvant temozolomide. Pseudoprogression was defined as progressive disease on MRI after chemoradiotherapy with stabilisation or reduction of contrast-enhanced lesions after three cycles of temozolomide, and was compared with the disease course during long-term follow-up. Changes in maximum standardized uptake value (SUVmax) and tumour-to-normal uptake ratios were calculated for FLT and are presented as the mean SUVmax for multiple lesions. RESULTS: Between 2009 and 2012, 30 patients were included. Of 24 evaluable patients, 7 showed pseudoprogression and 7 had true progression as defined by MRI response. FLT PET parameters did not significantly differ between patients with true progression and pseudoprogression defined by MRI. The correlation between change in SUVmax and survival (p = 0.059) almost reached the standard level of statistical significance. Lower baseline FLT PET uptake was significantly correlated with improved survival (p = 0.022). CONCLUSION: Baseline FLT uptake appears to be predictive of overall survival. Furthermore, changes in SUVmax over time showed a tendency to be associated with improved survival. However, further studies are necessary to investigate the ability of FLT PET imaging to discriminate between true progression and pseudoprogression in patients with glioblastoma.

Novel insights into vascularization patterns and angiogenic factors in glioblastoma subclasses.

Glioblastoma (GBM) is a highly vascularized and aggressive type of primary brain tumor in adults with dismal survival. Molecular subtypes of GBM have been identified that are related to clinical outcome and response to therapy. Although the mesenchymal type has been ascribed higher angiogenic activity, extensive characterization of the vascular component in GBM subtypes has not been performed. Therefore, we aimed to investigate the differential vascular status and angiogenic signaling levels in molecular subtypes. GBM tissue samples representing proneural IDH1 mutant, classical-like and mesenchymal-like subtypes were analyzed by morphometry for the number of vessels, vessel size and vessel maturity. Also the expression levels of factors from multiple angiogenic signaling pathways were determined. We found that necrotic and hypoxic areas were relatively larger in mesenchymal-like tumors and these tumors also had larger vessels. However, the number of vessels, basement membrane deposition and pericyte coverage did not vary between the subtypes. Regarding signaling patterns the majority of factors were expressed at similar levels in the subtypes, and only ANGPT2, MMP2, TIMP1, VEGFA and MMP9/TIMP2 were higher expressed in GBMs of the classical-like subtype. In conclusion, although morphological differences were observed between the subtypes, the angiogenic signaling status of GBM subtypes seemed to be rather similar. These results challenge the concept of mesenchymal GBMs being more angiogenic than other subclasses.

Treatment outcome of patients with recurrent glioblastoma multiforme: a retrospective multicenter analysis.

Glioblastoma multiforme (GBM) universally recurs with dismal prognosis. We evaluated the efficacy of standard treatment strategies for patients with recurrent GBM (rGBM). From two centers in the Netherlands, 299 patients with rGBM after first-line treatment, diagnosed between 2005 and 2014, were retrospectively evaluated. Four different treatment strategies were defined: systemic treatment (SYST), re-irradiation (RT), re-resection followed by adjuvant treatment (SURG) and best supportive care (BSC). Median OS for all patients was 6.5 months, and median PFS (excluding patients receiving BSC) was 5.5 months. Older age, multifocal lesions and steroid use were significantly associated with a shorter survival. After correction for confounders, patients receiving SYST (34.8%) and SURG (18.7%) had a significantly longer survival than patients receiving BSC (39.5%), 7.3 and 11.0 versus 3.1 months, respectively [HR 0.46 (p < 0.001) and 0.36 (p < 0.001)]. Median survival for patients receiving RT (7.0%) was 9.2 months, but this was not significantly different from patients receiving BSC (p = 0.068). Patients receiving SURG compared to SYST had a longer PFS (9.0 vs. 4.3 months, respectively; p < 0.001), but no difference in OS was observed. After adjustments for confounders, patients with rGBM selected for treatment with SURG or SYST do survive significantly longer than patients who are selected for BSC based on clinical parameters. The value of reoperation versus systemic treatment strategies needs further investigation.

Emotion recognition in relation to tumor characteristics in patients with low-grade glioma.

BACKGROUND: Patients with low-grade gliomas (LGG) treated with surgery, generally function well and have a favorable prognosis. However, LGG can affect neurocognitive functioning. To date, little is known about social cognition (SC) in these patients, although impaired SC is related to social-behavioral problems and poor societal participation. Frontal brain areas are important for SC and LGG frequently have a frontal location. Therefore, the aim of the present study was to investigate whether emotion recognition, a key component of SC, was impaired, and related to general cognition, tumor location, laterality, tumor volume, and histopathological characteristics in patients with LGG, postsurgery, and before start of adjuvant therapy. METHODS: A total of 121 patients with LGG were matched with 169 healthy controls (HC). Tumor location [including (frontal) subregions; insula, anterior cingulate cortex, lateral prefrontal cortex (LPFC), orbitofrontal-ventromedial PFC] and tumor volume were determined on MRI scans. Emotion recognition was measured with the Ekman 60 faces test of the Facial Expressions of Emotion-Stimuli and Tests (FEEST). RESULTS: Patients with LGG performed significantly lower on the FEEST than HC, with 33.1% showing impairment compared to norm data. Emotion recognition was not significantly correlated to frontal tumor location, laterality, and histopathological characteristics, and significantly but weakly with general cognition and tumor volume. CONCLUSIONS: Emotion recognition is impaired in patients with LGG but not (strongly) related to specific tumor characteristics or general cognition. Hence, measuring SC with individual neuropsychological assessment of these patients is crucial, irrespective of tumor characteristics, to inform clinicians about possible impairments, and consequently offer appropriate care.

Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks.

Extent of resection after surgery is one of the main prognostic factors for patients diagnosed with glioblastoma. To achieve this, accurate segmentation and classification of residual tumor from post-operative MR images is essential. The current standard method for estimating it is subject to high inter- and intra-rater variability, and an automated method for segmentation of residual tumor in early post-operative MRI could lead to a more accurate estimation of extent of resection. In this study, two state-of-the-art neural network architectures for pre-operative segmentation were trained for the task. The models were extensively validated on a multicenter dataset with nearly 1000 patients, from 12 hospitals in Europe and the United States. The best performance achieved was a 61% Dice score, and the best classification performance was about 80% balanced accuracy, with a demonstrated ability to generalize across hospitals. In addition, the segmentation performance of the best models was on par with human expert raters. The predicted segmentations can be used to accurately classify the patients into those with residual tumor, and those with gross total resection.

Multi-class glioma segmentation on real-world data with missing MRI sequences: comparison of three deep learning algorithms.

This study tests the generalisability of three Brain Tumor Segmentation (BraTS) challenge models using a multi-center dataset of varying image quality and incomplete MRI datasets. In this retrospective study, DeepMedic, no-new-Unet (nn-Unet), and NVIDIA-net (nv-Net) were trained and tested using manual segmentations from preoperative MRI of glioblastoma (GBM) and low-grade gliomas (LGG) from the BraTS 2021 dataset (1251 in total), in addition to 275 GBM and 205 LGG acquired clinically across 12 hospitals worldwide. Data was split into 80% training, 5% validation, and 15% internal test data. An additional external test-set of 158 GBM and 69 LGG was used to assess generalisability to other hospitals' data. All models' median Dice similarity coefficient (DSC) for both test sets were within, or higher than, previously reported human inter-rater agreement (range of 0.74-0.85). For both test sets, nn-Unet achieved the highest DSC (internal = 0.86, external = 0.93) and the lowest Hausdorff distances (10.07, 13.87 mm, respectively) for all tumor classes (p < 0.001). By applying Sparsified training, missing MRI sequences did not statistically affect the performance. nn-Unet achieves accurate segmentations in clinical settings even in the presence of incomplete MRI datasets. This facilitates future clinical adoption of automated glioma segmentation, which could help inform treatment planning and glioma monitoring.

Distinct Slow-Wave Activity Patterns in Resting-State Electroencephalography and Their Relation to Language Functioning in Low-Grade Glioma and Meningioma Patients.

Introduction: Brain tumours frequently cause language impairments and are also likely to co-occur with localised abnormal slow-wave brain activity. However, it is unclear whether this applies specifically to low-grade brain tumours. We investigate slow-wave activity in resting-state electroencephalography (EEG) in low-grade glioma and meningioma patients, and its relation to pre- and postoperative language functioning. Method: Patients with a glioma (N = 15) infiltrating the language-dominant hemisphere and patients with a meningioma (N = 10) with mass effect on this hemisphere underwent extensive language testing before and 1 year after surgery. EEG was registered preoperatively, postoperatively (glioma patients only), and once in healthy individuals. Slow-wave activity in delta- and theta- frequency bands was evaluated visually and quantitatively by spectral power at three levels over the scalp: the whole brain, the affected hemisphere, and the affected region. Results: Glioma patients had increased delta activity (affected area) and increased theta activity (all levels) before and after surgery. In these patients, increased preoperative theta activity was related to the presence of language impairment, especially to poor word retrieval and grammatical performance. Preoperative slow-wave activity was also related to postoperative language outcomes. Meningioma patients showed no significant increase in EEG slow-wave activity compared to healthy individuals, but they presented with word retrieval, grammatical, and writing problems preoperatively, as well as with writing impairments postoperatively. Discussion: Although the brain-tumour pathology in low-grade gliomas and meningiomas has a different effect on resting-state brain activity, patients with low-grade gliomas and meningiomas both suffer from language impairments. Increased theta activity in glioma patients can be considered as a language-impairment marker, with prognostic value for language outcome after surgery.

Emotion Recognition in Patients with Low-Grade Glioma before and after Surgery.

Research on patients with low-grade gliomas (LGGs) showed neurocognitive impairments in various domains. However, social cognition has barely been investigated. Facial emotion recognition is a vital aspect of social cognition, but whether emotion recognition is affected in LGG patients is unclear. Therefore, we aimed to investigate the effect of LGG and resection by examining emotion recognition pre- and postoperatively. Additionally, the relationships among emotion recognition and general cognition and tumor location were investigated. Thirty patients with LGG who underwent resective surgery were included and matched with 63 healthy control participants (HCs). Emotion recognition was measured with the Facial Expressions of Emotion-Stimuli and Tests (FEEST) and general cognition with neuropsychological tests. Correlations and within-group and between-group comparisons were calculated. Before surgery, patients performed significantly worse than the HCs on FEEST-Total and FEEST-Anger. Paired comparisons showed no significant differences between FEEST scores before and post-surgery. No significant correlations with general cognition and tumor location were found. To conclude, the results of this study indicate that the tumor itself contributes significantly to social cognitive dysfunction and that surgery causes no additional deficit. Impairments were not related to general cognitive deficits or tumor location. Consequently, incorporating tests for emotion recognition into the neuropsychological assessment of patients with LGG is important.

Rare central nervous system tumors in adults: a population-based study of ependymomas, pilocytic astrocytomas, medulloblastomas, and intracranial germ cell tumors.

Background: Ependymomas, pilocytic astrocytomas, medulloblastomas, and intracranial germ cell tumors occur relative frequently in children, but are rare central nervous system (CNS) tumors in adults. In this population-based survey, we established incidence, treatment, and survival patterns for these tumors diagnosed in adult patients (≥18 years) over a 30-year period (1989-2018). Methods: Data on 1384 ependymomas, 454 pilocytic astrocytomas, 205 medulloblastomas, and 112 intracranial germ cell tumors were obtained from the Netherlands Cancer Registry (NCR) on the basis of a histopathological diagnosis. For each tumor type, age-standardized incidence rates and estimated annual percentage change were calculated. Trends in incidence and main treatment modalities were reported per 5-year periods. Overall survival was calculated using the Kaplan-Meier method, and relative survival rates were estimated using the Pohar-Perme estimator. Results: Incidence and survival rates remained generally stable for pilocytic astrocytomas, medulloblastomas, and germ cell tumors. Increasing incidence was observed for spinal ependymomas, mostly for myxopapillary ependymomas, and survival improved over time for grade II ependymomas (P < .01). Treatment patterns varied over time with shifting roles for surgery in ependymomas and for chemotherapy and radiation in medulloblastomas and germinomas. Conclusions: The study provides baseline information for highly needed national and international standard treatment protocols, and thus for further improving patient outcomes in these rare CNS tumors.

Between-hospital variation in time to glioblastoma surgery: a report from the Quality Registry Neuro Surgery in the Netherlands.

OBJECTIVE: Patients with glioblastoma are often scheduled for urgent elective surgery. Currently, the impact of the waiting period until glioblastoma surgery is undetermined. In this national quality registry study, the authors determined the wait times until surgery for patients with glioblastoma, the risk factors associated with wait times, and the risk-standardized variation in time to surgery between Dutch hospitals. The associations between time to surgery and patient outcomes were also explored. METHODS: Data from all 4589 patients who underwent first-time glioblastoma surgery between 2014 and 2019 in the Netherlands were collected by 13 hospitals in the Quality Registry Neuro Surgery. Time to surgery comprised 1) the time from first MR scan to surgery (MTS), and 2) the time from first neurosurgical consultation to surgery (CTS). Long MTS was defined as more than 21 days and long CTS as more than 14 days. Potential risk factors were analyzed in multivariable logistic regression models. The standardized rate of long time to surgery was analyzed using funnel plots. Patient outcomes including Karnofsky Performance Scale (KPS) score change, complications, and survival were analyzed by multivariable logistic regression and proportional hazards models. RESULTS: The median overall MTS and CTS were 18 and 9 days, respectively. Overall, 2576 patients (56%) had an MTS within 3 weeks and 3069 (67%) had a CTS within 2 weeks. Long MTS was significantly associated with older age, higher preoperative KPS score, higher American Society of Anesthesiologists comorbidity class, season, lower hospital case volume, university affiliation, and resection. Long CTS was significantly associated with higher baseline KPS score, university affiliation, resection, more recent year of treatment, and season. In funnel plots, considerable practice variation was observed between hospitals in patients with long times to surgery. Fewer patients with KPS score improvement were observed after a long time until resection. Long CTS was associated with longer survival. Complications and KPS score decline were not associated with time to surgery. CONCLUSIONS: Considerable between-hospital variation among Dutch hospitals was observed in the time to glioblastoma surgery. A long time to resection impeded KPS score improvement, and therefore, patients who may improve should be identified for more urgent resection. Longer survival was observed in patients selected for longer time until surgery after neurosurgical consultation (CTS).

On the cutting edge of glioblastoma surgery: where neurosurgeons agree and disagree on surgical decisions.

OBJECTIVE: The aim of glioblastoma surgery is to maximize the extent of resection while preserving functional integrity. Standards are lacking for surgical decision-making, and previous studies indicate treatment variations. These shortcomings reflect the need to evaluate larger populations from different care teams. In this study, the authors used probability maps to quantify and compare surgical decision-making throughout the brain by 12 neurosurgical teams for patients with glioblastoma. METHODS: The study included all adult patients who underwent first-time glioblastoma surgery in 2012-2013 and were treated by 1 of the 12 participating neurosurgical teams. Voxel-wise probability maps of tumor location, biopsy, and resection were constructed for each team to identify and compare patient treatment variations. Brain regions with different biopsy and resection results between teams were identified and analyzed for patient functional outcome and survival. RESULTS: The study cohort consisted of 1087 patients, of whom 363 underwent a biopsy and 724 a resection. Biopsy and resection decisions were generally comparable between teams, providing benchmarks for probability maps of resections and biopsies for glioblastoma. Differences in biopsy rates were identified for the right superior frontal gyrus and indicated variation in biopsy decisions. Differences in resection rates were identified for the left superior parietal lobule, indicating variations in resection decisions. CONCLUSIONS: Probability maps of glioblastoma surgery enabled capture of clinical practice decisions and indicated that teams generally agreed on which region to biopsy or to resect. However, treatment variations reflecting clinical dilemmas were observed and pinpointed by using the probability maps, which could therefore be useful for quality-of-care discussions between surgical teams for patients with glioblastoma.

Preoperative Brain Tumor Imaging: Models and Software for Segmentation and Standardized Reporting.

For patients suffering from brain tumor, prognosis estimation and treatment decisions are made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the lack of standardized and automatic methods for tumor detection and generation of clinical reports, incorporating a wide range of tumor characteristics, represents a major hurdle. In this study, we investigate the most occurring brain tumor types: glioblastomas, lower grade gliomas, meningiomas, and metastases, through four cohorts of up to 4,000 patients. Tumor segmentation models were trained using the AGU-Net architecture with different preprocessing steps and protocols. Segmentation performances were assessed in-depth using a wide-range of voxel and patient-wise metrics covering volume, distance, and probabilistic aspects. Finally, two software solutions have been developed, enabling an easy use of the trained models and standardized generation of clinical reports: Raidionics and Raidionics-Slicer. Segmentation performances were quite homogeneous across the four different brain tumor types, with an average true positive Dice ranging between 80 and 90%, patient-wise recall between 88 and 98%, and patient-wise precision around 95%. In conjunction to Dice, the identified most relevant other metrics were the relative absolute volume difference, the variation of information, and the Hausdorff, Mahalanobis, and object average symmetric surface distances. With our Raidionics software, running on a desktop computer with CPU support, tumor segmentation can be performed in 16-54 s depending on the dimensions of the MRI volume. For the generation of a standardized clinical report, including the tumor segmentation and features computation, 5-15 min are necessary. All trained models have been made open-access together with the source code for both software solutions and validation metrics computation. In the future, a method to convert results from a set of metrics into a final single score would be highly desirable for easier ranking across trained models. In addition, an automatic classification of the brain tumor type would be necessary to replace manual user input. Finally, the inclusion of post-operative segmentation in both software solutions will be key for generating complete post-operative standardized clinical reports.

Resting-State Electroencephalography Functional Connectivity Networks Relate to Pre- and Postoperative Language Functioning in Low-Grade Glioma and Meningioma Patients.

Introduction: Preservation of language functioning in patients undergoing brain tumor surgery is essential because language impairments negatively impact the quality of life. Brain tumor patients have alterations in functional connectivity (FC), the extent to which brain areas functionally interact. We studied FC networks in relation to language functioning in glioma and meningioma patients. Method: Patients with a low-grade glioma (N = 15) or meningioma (N = 10) infiltrating into/pressing on the language-dominant hemisphere underwent extensive language testing before and 1 year after surgery. Resting-state EEG was registered preoperatively, postoperatively (glioma patients only), and once in healthy individuals. After analyzing FC in theta and alpha frequency bands, weighted networks and Minimum Spanning Trees were quantified by various network measures. Results: Pre-operative FC network characteristics did not differ between glioma patients and healthy individuals. However, hub presence and higher local and global FC are associated with poorer language functioning before surgery in glioma patients and predict worse language performance at 1 year after surgery. For meningioma patients, a greater small worldness was related to worse language performance and hub presence; better average clustering and global integration were predictive of worse outcome on language function 1 year after surgery. The average eccentricity, diameter and tree hierarchy seem to be the network metrics with the more pronounced relation to language performance. Discussion: In this exploratory study, we demonstrated that preoperative FC networks are informative for pre- and postoperative language functioning in glioma patients and to a lesser extent in meningioma patients.

11C-methyl-L-methionine PET measuring parameters for the diagnosis of tumour progression against radiation-induced changes in brain metastases.

OBJECTIVES: Radiation-induced changes (RIC) secondary to focal radiotherapy can imitate tumour progression in brain metastases and make follow-up clinical decision making unreliable. 11C-methyl-L-methionine-PET (MET-PET) is widely used for the diagnosis of RIC in brain metastases, but minimal literature exists regarding the optimum PET measuring parameter to be used. We analysed the diagnostic performance of different MET-PET measuring parameters in distinguishing between RIC and tumour progression in a retrospective cohort of brain metastasis patients. METHODS: 26 patients with 31 metastatic lesions were included on the basis of having undergone a PET scan due to radiological uncertainty of disease progression. The PET images were analysed and methionine uptake quantified using standardised-uptake-values (SUV) and tumour-to-normal tissue (T/N) ratios, generated as SUVmean, SUVmax, SUVpeak, T/Nmean, T/Nmax-mean and T/Npeak-mean. Metabolic-tumour-volume and total-lesion methionine metabolism were also computed. A definitive diagnosis of either RIC or tumour progression was established by clinicoradiological follow-up of least 4 months subsequent to the investigative PET scan. RESULTS: All MET-PET parameters except metabolic-tumour-volume showed statistically significant differences between tumour progression and lesions with RIC. Receiver-operating-characteristic curve and area-under the-curve analysis demonstrated the highest value of 0.834 for SUVmax with a corresponding optimum threshold of 3.29. This associated with sensitivity, specificity, positive predictive and negative predictive values of 78.57, 70.59%, 74.32 and 75.25% respectively. CONCLUSIONS: MET-PET is a useful modality for the diagnosis of RIC in brain metastases. SUVmax was the PET parameter with the greatest diagnostic performance. ADVANCES IN KNOWLEDGE: More robust comparisons between SUVmax and SUVpeak could enhance follow-up treatment planning.

Timing of glioblastoma surgery and patient outcomes: a multicenter cohort study.

BACKGROUND: The impact of time-to-surgery on clinical outcome for patients with glioblastoma has not been determined. Any delay in treatment is perceived as detrimental, but guidelines do not specify acceptable timings. In this study, we relate the time to glioblastoma surgery with the extent of resection and residual tumor volume, performance change, and survival, and we explore the identification of patients for urgent surgery. METHODS: Adults with first-time surgery in 2012-2013 treated by 12 neuro-oncological teams were included in this study. We defined time-to-surgery as the number of days between the diagnostic MR scan and surgery. The relation between time-to-surgery and patient and tumor characteristics was explored in time-to-event analysis and proportional hazard models. Outcome according to time-to-surgery was analyzed by volumetric measurements, changes in performance status, and survival analysis with patient and tumor characteristics as modifiers. RESULTS: Included were 1033 patients of whom 729 had a resection and 304 a biopsy. The overall median time-to-surgery was 13 days. Surgery was within 3 days for 235 (23%) patients, and within a month for 889 (86%). The median volumetric doubling time was 22 days. Lower performance status (hazard ratio [HR] 0.942, 95% confidence interval [CI] 0.893-0.994) and larger tumor volume (HR 1.012, 95% CI 1.010-1.014) were independently associated with a shorter time-to-surgery. Extent of resection, residual tumor volume, postoperative performance change, and overall survival were not associated with time-to-surgery. CONCLUSIONS: With current decision-making for urgent surgery in selected patients with glioblastoma and surgery typically within 1 month, we found equal extent of resection, residual tumor volume, performance status, and survival after longer times-to-surgery.

Glioblastoma Surgery Imaging-Reporting and Data System: Validation and Performance of the Automated Segmentation Task.

For patients with presumed glioblastoma, essential tumor characteristics are determined from preoperative MR images to optimize the treatment strategy. This procedure is time-consuming and subjective, if performed by crude eyeballing or manually. The standardized GSI-RADS aims to provide neurosurgeons with automatic tumor segmentations to extract tumor features rapidly and objectively. In this study, we improved automatic tumor segmentation and compared the agreement with manual raters, describe the technical details of the different components of GSI-RADS, and determined their speed. Two recent neural network architectures were considered for the segmentation task: nnU-Net and AGU-Net. Two preprocessing schemes were introduced to investigate the tradeoff between performance and processing speed. A summarized description of the tumor feature extraction and standardized reporting process is included. The trained architectures for automatic segmentation and the code for computing the standardized report are distributed as open-source and as open-access software. Validation studies were performed on a dataset of 1594 gadolinium-enhanced T1-weighted MRI volumes from 13 hospitals and 293 T1-weighted MRI volumes from the BraTS challenge. The glioblastoma tumor core segmentation reached a Dice score slightly below 90%, a patientwise F1-score close to 99%, and a 95th percentile Hausdorff distance slightly below 4.0 mm on average with either architecture and the heavy preprocessing scheme. A patient MRI volume can be segmented in less than one minute, and a standardized report can be generated in up to five minutes. The proposed GSI-RADS software showed robust performance on a large collection of MRI volumes from various hospitals and generated results within a reasonable runtime.