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Abstract DNA methylation analysis has become a powerful tool in neuropathology. Although DNA methylation-based classification usually shows high accuracy, certain samples cannot be classified and remain clinically challenging. We aimed to gain insight into these cases from a clinical perspective. To address, central nervous system (CNS) tumors were subjected to DNA methylation profiling and classified according to their calibrated score using the DKFZ brain tumor classifier (V11.4) as “≥ 0.84” (score ≥ 0.84), “0.3–0.84” (score 0.3–0.84), or “

Abstract Machine learning (ML) has revolutionized data processing in recent years. This study presents the results of the first prediction models based on a long-term monocentric data registry of patients with microsurgically treated unruptured intracranial aneurysms (UIAs) using a temporal train-test split. Temporal train-test splits allow to simulate prospective validation, and therefore provide more accurate estimations of a model’s predictive quality when applied to future patients. ML models for the prediction of the Glasgow outcome scale, modified Rankin Scale (mRS), and new transient or permanent neurological deficits (output variables) were created from all UIA patients that underwent microsurgery at the Kepler University Hospital Linz (Austria) between 2002 and 2020 (n = 466), based on 18 patient- and 10 aneurysm-specific preoperative parameters (input variables). Train-test splitting was performed with a temporal split for outcome prediction in microsurgical therapy of UIA. Moreover, an external validation was conducted on an independent external data set (n = 256) of the Department of Neurosurgery, University Medical Centre Hamburg-Eppendorf. In total, 722 aneurysms were included in this study. A postoperative mRS > 2 was best predicted by a quadratic discriminant analysis (QDA) estimator in the internal test set, with an area under the receiver operating characteristic curve (ROC-AUC) of 0.87 ± 0.03 and a sensitivity and specificity of 0.83 ± 0.08 and 0.71 ± 0.07, respectively. A Multilayer Perceptron predicted the post- to preoperative mRS difference > 1 with a ROC-AUC of 0.70 ± 0.02 and a sensitivity and specificity of 0.74 ± 0.07 and 0.50 ± 0.04, respectively. The QDA was the best model for predicting a permanent new neurological deficit with a ROC-AUC of 0.71 ± 0.04 and a sensitivity and specificity of 0.65 ± 0.24 and 0.60 ± 0.12, respectively. Furthermore, these models performed significantly better than the classic logistic regression models (p 2, a pre- and postoperative difference in mRS > 1 point and a GOS

Introduction: Technical advances and the increasing role of interdisciplinary decision-making may warrant formal definitions of expertise in surgical neuro-oncology. Research question: The EANS Neuro-oncology Section felt that a survey detailing the European neurosurgical perspective on the concept of expertise in surgical neuro-oncology might be helpful. Material and methods: The EANS Neuro-oncology Section panel developed an online survey asking questions regarding criteria for expertise in neuro-oncological surgery and sent it to all individual EANS members. Results: Our questionnaire was completed by 251 respondents (consultants: 80.1%) from 42 countries. 67.7% would accept a lifetime caseload of >200 cases and 86.7% an annual caseload of >50 as evidence of neuro-oncological surgical expertise. A majority felt that surgeons who do not treat children (56.2%), do not have experience with spinal fusion (78.1%) or peripheral nerve tumors (71.7%) may still be considered experts. Majorities believed that expertise requires the use of skull-base approaches (85.8%), intraoperative monitoring (83.4%), awake craniotomies (77.3%), and neuro-endoscopy (75.5%) as well as continuing education of at least 1/year (100.0%), a research background (80.0%) and teaching activities (78.7%), and formal interdisciplinary collaborations (e.g., tumor board: 93.0%). Academic vs. non-academic affiliation, career position, years of neurosurgical experience, country of practice, and primary clinical interest had a minor influence on the respondents’ opinions. Discussion and conclusion: Opinions among neurosurgeons regarding the characteristics and features of expertise in neuro-oncology vary surprisingly little. Large majorities favoring certain thresholds and qualitative criteria suggest a consensus definition might be possible.

Abstract The severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) has changed the clinical day-to-day practice. The aim of this study was to evaluate the impact of the pandemic on patients with high-grade glioma (HGG) as well as to derive best practice recommendations. We compared a multi-institutional cohort with HGG (n = 251) from 03/2020 to 05/2020 (n = 119) to a historical cohort from 03/2019 to 05/2019 (n = 132). The endpoints were outcome (progression-free survival (PFS) and overall survival (OS)) as well as patterns of care and time intervals between treatment steps. The median OS for WHO grade 4 gliomas was 12 months in 2019 (95% Confidence Interval 9.7–14.3 months), and not reached in 2020 (p = .026). There were no other significant differences in the Kaplan–Meier estimates for OS and PFS between cohorts of 2019 and 2020, neither did stratification by WHO grade reveal any significant differences for OS, PFS or for patterns of care. The time interval between cranial magnetic resonance imaging (cMRI) and biopsy was significantly longer in 2020 cohort (11 versus 21 days, p = .031). Median follow-up was 10 months (range 0–30 months). Despite necessary disease containment policies, it is crucial to ensure that patients with HGG are treated in line with the recent guidelines and standard of care (SOC) algorithms. Therefore, we strongly suggest pursuing no changes to SOC treatment, a timely diagnosis and treatment with short time intervals between first symptoms, initial diagnosis, and treatment, as well as a guideline-based cMRI follow-up.

Introduction: Optimizing patient safety and quality improvement is increasingly important in surgery. Benchmarks and clinical quality registries are being developed to assess the best achievable results for several surgical procedures and reduce unwarranted variation between different centers. However, there is no clinical database from international centers for establishing standardized reference values of patients undergoing surgery for mesial temporal lobe epilepsy.Design: The Enhancing Safety in Epilepsy Surgery (EASINESS) study is a retrospectively conducted, multicenter, open registry. All patients undergoing mesial temporal lobe epilepsy surgery in participating centers between January 2015 and December 2019 are included in this study. The patient characteristics, preoperative diagnostic tools, surgical data, postoperative complications, and long-term seizure outcomes are recorded.Outcomes: The collected data will be used for establishing standardized reference values (“benchmarks”) for this type of surgical procedure. The primary endpoints include seizure outcomes according to the International League Against Epilepsy (ILAE) classification and defined postoperative complications.Discussion: The EASINESS will define robust and standardized outcome references after amygdalohippocampectomy for temporal lobe epilepsy. After the successful definition of benchmarks from an international cohort of renowned centers, these data will serve as reference values for the evaluation of novel surgical techniques and comparisons among centers for future clinical trials.Clinical trial registration: This study is indexed at clinicaltrials.gov (NT 04952298).