OBJECTIVE Enhanced Recovery After Surgery (ERAS) has led to a paradigm shift in perioperative care through multimodal interventions. Still, ERAS remains a relatively new concept in neurosurgery, and there is no summary of evidence on ERAS applications in cranial neurosurgery. METHODS The authors systematically reviewed the literature using the PubMed/MEDLINE, Embase, Scopus, and Cochrane Library databases for ERAS protocols and elements. Studies had to assess at least one pre-, peri-, or postoperative ERAS element and evaluate at least one of the following outcomes: 1) length of hospital stay, 2) length of ICU stay, 3) postoperative pain, 4) direct and indirect healthcare cost, 5) complication rate, 6) readmission rate, or 7) patient satisfaction. RESULTS A final 27 articles were included in the qualitative analysis, with mixed quality of evidence ranging from high in 3 cases to very low in 1 case. Seventeen studies reported a complete ERAS protocol. Preoperative ERAS elements include patient selection through multidisciplinary team discussion, patient counseling and education to adjust expectations of the postoperative period, and mental state assessment; antimicrobial, steroidal, and antiepileptic prophylaxes; nutritional assessment, as well as preoperative oral carbohydrate loading; and postoperative nausea and vomiting (PONV) prophylaxis. Anesthesiology interventions included local anesthesia for pin sites, regional field block or scalp block, avoidance or minimization of the duration of invasive monitoring, and limitation of intraoperative mannitol. Other intraoperative elements include absorbable skin sutures and avoidance of wound drains. Postoperatively, the authors identified early extubation, observation in a step-down unit instead of routine ICU admission, early mobilization, early fluid de-escalation, early intake of solid food and liquids, early removal of invasive monitoring, professional nutritional assessment, PONV management, nonopioid rescue analgesia, and early postoperative imaging. Other postoperative interventions included discharge criteria standardization and home visits or progress monitoring by a nurse. CONCLUSIONS A wide range of evidence-based interventions are available to improve recovery after elective craniotomy, although there are few published ERAS protocols. Patient-centered optimization of neurosurgical care spanning the pre-, intra-, and postoperative periods is feasible and has already provided positive results in terms of improved outcomes such as postoperative pain, patient satisfaction, reduced length of stay, and cost reduction with an excellent safety profile. Although fast-track recovery protocols and ERAS studies are gaining momentum for elective craniotomy, prospective trials are needed to provide stronger evidence.

Glioblastoma (GBM) is the most aggressive and prevalent form of a human brain tumor in adults. Several data have demonstrated the implication of microRNAs (miRNAs) in tumorigenicity of GBM stem-like cells (GSCs). The regulatory functions of miRNAs in GSCs have emerged as potential therapeutic candidates for glioma treatment. The current study aimed at investigating the function of miR-370-3p in glioma progression, as aberrant expression of miR-370-3p, is involved in various human cancers, including glioma. Analyzing our collection of GBM samples and patient-derived GSC lines, we found the expression of miR-370-3p significantly downregulated compared to normal brain tissues and normal neural stem cells. Restoration of miR-370-3p expression in GSCs significantly decreased proliferation, migration, and clonogenic abilities of GSCs, in vitro, and tumor growth in vivo. Gene expression analysis performed on miR-370-3p transduced GSCs, identified several transcripts involved in Epithelial to Mesenchymal Transition (EMT), and Hypoxia signaling pathways. Among the genes downregulated by the restored expression of miR-370-3p, we found the EMT-inducer high-mobility group AT-hook 2 (HMGA2), the master transcriptional regulator of the adaptive response to hypoxia, Hypoxia-inducible factor (HIF)1A, and the long non-coding RNAs (lncRNAs) Nuclear Enriched Abundant Transcript (NEAT)1. NEAT1 acts as an oncogene in a series of human cancers including gliomas, where it is regulated by the Epidermal Growth Factor Receptor (EGFR) pathways, and contributes to tumor growth and invasion. Noteworthy, the expression levels of miR-370-3p and NEAT1 were inversely related in both GBM tumor specimens and GSCs, and a dual-luciferase reporter assay proved the direct binding between miR-370-3p and the lncRNAs NEAT1. Our results identify a critical role of miR-370-3p in the regulation of GBM development, indicating that miR-370-3p acts as a tumor-suppressor factor inhibiting glioma cell growth, migration and invasion by targeting the lncRNAs NEAT1, HMGA2, and HIF1A, thus, providing a potential candidate for GBM patient treatment.

Background Metabolism reprogramming is a common feature in cancer, and it is critical to facilitate cancer cell growth. Isocitrate Dehydrogenase 1/2 (IDH1 & IDH2) mutations (IDHmut) are the most common genetic alteration in glioma grade II and III and secondary glioblastoma and these mutations increase reliance on glutamine metabolism, suggesting a potential vulnerability. In this study, we tested the hypothesis that the brain penetrant glutamine antagonist prodrug JHU-083 reduces glioma cell growth. Material and Methods We performed cell growth, cell cycle, and protein expression in glutamine deprived or Glutaminase (GLS) gene silenced glioma cells. We tested the effect of JHU-083 on cell proliferation, metabolism, and mTOR signaling in cancer cell lines. An orthotopic IDH1R132H glioma model was used to test the efficacy of JHU-083 in vivo. Results Glutamine deprivation and GLS gene silencing reduced glioma cell proliferation in vitro in glioma cells. JHU-083 reduced glioma cell growth in vitro, modulated cell metabolism, and disrupted mTOR signaling and downregulated Cyclin D1 protein expression, through a mechanism independent of TSC2 modulation and glutaminolysis. IDH1R132H isogenic cells preferentially reduced cell growth and mTOR signaling downregulation. In addition, guanine supplementation partially rescued IDHmut glioma cell growth, mTOR signaling, and Cyclin D1 protein expression in vitro. Finally, JHU-083 extended survival in an intracranial IDH1mut glioma model and reduced intracranial pS6 protein expression. Conclusion Targeting glutamine metabolism with JHU-083 showed efficacy in preclinical models of IDHmut glioma and measurably decreased mTOR signaling.

Background Recent technological advances have led to the development and implementation of machine learning (ML) in various disciplines, including neurosurgery. Our goal was to conduct a comprehensive survey of neurosurgeons to assess the acceptance of and attitudes toward ML in neurosurgical practice and to identify factors associated with its use. Methods The online survey consisted of nine or ten mandatory questions and was distributed in February and March 2019 through the European Association of Neurosurgical Societies (EANS) and the Congress of Neurosurgeons (CNS). Results Out of 7280 neurosurgeons who received the survey, we received 362 responses, with a response rate of 5%, mainly in Europe and North America. In total, 103 neurosurgeons (28.5%) reported using ML in their clinical practice, and 31.1% in research. Adoption rates of ML were relatively evenly distributed, with 25.6% for North America, 30.9% for Europe, 33.3% for Latin America and the Middle East, 44.4% for Asia and Pacific and 100% for Africa with only two responses. No predictors of clinical ML use were identified, although academic settings and subspecialties neuro-oncology, functional, trauma and epilepsy predicted use of ML in research. The most common applications were for predicting outcomes and complications, as well as interpretation of imaging. Conclusions This report provides a global overview of the neurosurgical applications of ML. A relevant proportion of the surveyed neurosurgeons reported clinical experience with ML algorithms. Future studies should aim to clarify the role and potential benefits of ML in neurosurgery and to reconcile these potential advantages with bioethical considerations.

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Background Indications and outcomes in lumbar spinal fusion for degenerative disease are notoriously heterogenous. Selected subsets of patients show remarkable benefit. However, their objective identification is often difficult. Decision-making may be improved with reliable prediction of long-term outcomes for each individual patient, improving patient selection and avoiding ineffective procedures. Methods Clinical prediction models for long-term functional impairment [Oswestry Disability Index (ODI) or Core Outcome Measures Index (COMI)], back pain, and leg pain after lumbar fusion for degenerative disease were developed. Achievement of the minimum clinically important difference at 12 months postoperatively was defined as a reduction from baseline of at least 15 points for ODI, 2.2 points for COMI, or 2 points for pain severity. Results Models were developed and integrated into a web-app (https://neurosurgery.shinyapps.io/fuseml/) based on a multinational cohort [N = 817; 42.7% male; mean (SD) age: 61.19 (12.36) years]. At external validation [N = 298; 35.6% male; mean (SD) age: 59.73 (12.64) years], areas under the curves for functional impairment [0.67, 95% confidence interval (CI): 0.59–0.74], back pain (0.72, 95%CI: 0.64–0.79), and leg pain (0.64, 95%CI: 0.54–0.73) demonstrated moderate ability to identify patients who are likely to benefit from surgery. Models demonstrated fair calibration of the predicted probabilities. Conclusions Outcomes after lumbar spinal fusion for degenerative disease remain difficult to predict. Although assistive clinical prediction models can help in quantifying potential benefits of surgery and the externally validated FUSE-ML tool may aid in individualized risk–benefit estimation, truly impacting clinical practice in the era of “personalized medicine” necessitates more robust tools in this patient population.

Recent technological advancements have led to the development and implementation of robotic surgery in several specialties, including neurosurgery. Our aim was to carry out a worldwide survey among neurosurgeons to assess the adoption of and attitude toward robotic technology in the neurosurgical operating room and to identify factors associated with use of robotic technology. The online survey was made up of nine or ten compulsory questions and was distributed via the European Association of the Neurosurgical Societies (EANS) and the Congress of Neurological Surgeons (CNS) in February and March 2018. From a total of 7280 neurosurgeons who were sent the survey, we received 406 answers, corresponding to a response rate of 5.6%, mostly from Europe and North America. Overall, 197 neurosurgeons (48.5%) reported having used robotic technology in clinical practice. The highest rates of adoption of robotics were observed for Europe (54%) and North America (51%). Apart from geographical region, only age under 30, female gender, and absence of a non-academic setting were significantly associated with clinical use of robotics. The Mazor family (32%) and ROSA (26%) robots were most commonly reported among robot users. Our study provides a worldwide overview of neurosurgical adoption of robotic technology. Almost half of the surveyed neurosurgeons reported having clinical experience with at least one robotic system. Ongoing and future trials should aim to clarify superiority or non-inferiority of neurosurgical robotic applications and balance these potential benefits with considerations on acquisition and maintenance costs.

Highlights Phylogenetic topographic anatomical patterns drive seizure risk in brain tumors. Seizure risk in brain tumors may be predicted using a generalized additive model. This may allow to better tailor antiepileptic therapy in brain tumor patients.