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Background: A recent trend of looking for health-related conditions on the Internet has been described, with up 70% of searchers stating that online sources have affected their medical decision-making. Patients with vestibular schwannomas (VS) use online sources, including videos, to seek information about treatment alternatives and outcomes and surgeons experience. Our study investigates the reliability and quality of VS-related online videos., Methods: In April 2020, a search was launched on YouTube for the key terms 'vestibular schwannoma,' 'acoustic neuroma,' 'eighth cranial nerve schwannoma,' and 'eighth cranial nerve neuroma.' Results were screened for possible inclusion. Three authors independently used the DISCERN instrument to evaluate the reliability and quality of the included videos. Factors possibly influencing popularity were investigated., Results: The initial search yielded 6416 videos. 38 videos were included in the final analysis. The average DISCERN score was 2.76, indicating overall poor quality and reliability of information. Only 5% scored 4.0 or more (unbiased videos that offer evidence-supported information); 31% scored between 3.0 and 3.99, and 63% scored 2.99 or less. Videos describing symptoms or the patient's clinical presentation were slightly more popular than videos without these characteristics. Surgical videos (videos containing clips of surgical procedures) were significantly more popular than non-surgical videos ( p  = .024) despite being of similarly poor quality (DISCERN score 2.85 vs. 2.74, respectively)., Conclusions: Available patient educational videos for VS are of mixed quality and reliability: the authors describe the strengths and pitfalls of existing YouTube videos. Considering that VS is a pathology with multiple available management modalities, and that patients' decision-making is affected by the information available on the Internet, it is of great importance that good-quality informative material be released by medical, academic, or educational institutions.

Purpose: the aim of this multicenter study is to preliminarily assess the role of the Endoscopic Endonasal Approach (EEA) in ultra-early (i.e., within 12 h) management of selected neurosurgical emergencies in terms of clinical and radiological outcomes., Methods: 26 patients affected by sellar/parasellar pathologies with rapid progression of symptoms were managed with EEA within 12 h from diagnosis in three Italian tertiary referral Centers from January 2016 to December 2019. Both clinical and radiological data have been collected preoperatively as well as post-operatively in order to perform retrospective analysis., Results: The average time from admission to the operating room was 5.5 h (±2.3). The extent of resection was gross-total in 20 (76.9%), subtotal in 6 (23.1%) patients. One patient experienced re-bleeding after a subtotal removal of a hemorrhagic lesion. Patients with a longer time from admission (>4 h) to the operatory room (OR) experienced stable impairment of the visual acuity ( p = 0.033) and visual field ( p = 0.029) in the post-operative setting., Conclusions: The Endoscopic Endonasal Approach represents a safe, effective technique that can be efficiently used with good results in the management of selected neurosurgical emergencies in centers with adequate experience.

Background: Despite advances in endoscopic transnasal transsphenoidal surgery (E-TNS) for pituitary adenomas (PAs), cerebrospinal fluid (CSF) leakage remains a life-threatening complication predisposing to major morbidity and mortality. In the current study we developed a supervised ML model able to predict the risk of intraoperative CSF leakage by comparing different machine learning (ML) methods and explaining the functioning and the rationale of the best performing algorithm., Methods: A retrospective cohort of 238 patients treated via E-TNS for PAs was selected. A customized pipeline of several ML models was programmed and trained; the best five models were tested on a hold-out test and the best classifier was then prospectively validated on a cohort of 35 recently treated patients., Results: Intraoperative CSF leak occurred in 54 (22,6%) of 238 patients. The most important risk's predictors were: non secreting status, older age, x-, y- and z-axes diameters, ostedural invasiveness, volume, ICD and R-ratio. The random forest (RF) classifier outperformed other models, with an AUC of 0.84, high sensitivity (86%) and specificity (88%). Positive predictive value and negative predictive value were 88% and 80% respectively. F1 score was 0.84. Prospective validation confirmed outstanding performance metrics: AUC (0.81), sensitivity (83%), specificity (79%), negative predictive value (95%) and F1 score (0.75)., Conclusions: The RF classifier showed the best performance across all models selected. RF models might predict surgical outcomes in heterogeneous multimorbid and fragile populations outperforming classical statistical analyses and other ML models (SVM, ANN etc.), improving patient management and reducing preventable morbidity and additional costs.

Spinal atypical meningiomas are rare, and those whose main extension is in the epidural space are anecdotal. Here, we report a case of a young woman presenting with sensory disturbances and a radiological diagnosis of a dorsal epidural sleeve-like mass. The surgical resection of the lesion allowed the decompression of the spinal cord and led to the histopathological diagnosis of atypical meningioma. At the 3-month follow-up, her neurological recovery was complete. Because of the gross total removal of the lesion, adjuvant radiotherapy was not performed: At the 2-year follow-up, no recurrence of disease was detected. A comprehensive literature review was performed, and just two more case reports on epidural atypical meningiomas were found in the English literature. Through this case report and literature review, we described a rare manifestation of spinal meningioma that entered into a differential diagnosis for extradural spinal lesions, such as secondary malignancies., (© 2023. The Author(s), under exclusive license to Springer Nature Switzerland AG.)

Meningiomas are mostly benign tumors that, at times, can behave aggressively, displaying recurrence despite gross-total resection (GTR) and progression to overt malignancy. Such cases represent a clinical challenge, particularly because they are difficult to recognize at first diagnosis. SOX2 (Sex-determining region Y-box2) is a transcription factor with a key role in stem cell maintenance and has been associated with tumorigenesis in a variety of cancers. The purpose of the present work was to dissect the role of SOX2 in predicting the aggressiveness of meningioma. We analyzed progressive/recurrent WHO grade 1−2 meningiomas and WHO grade 3 meningiomas; as controls, non-recurring WHO grade 1 and grade 2 meningioma patients were enrolled. SOX2 expression was evaluated using both immunohistochemistry (IHC) and RT-PCR. The final analysis included 87 patients. IHC was able to reliably assess SOX2 expression, as shown by the good correlation with mRNA levels (Spearman R = 0.0398, p = 0.001, AUC 0.87). SOX2 expression was an intrinsic characteristic of any single tumor and did not change following recurrence or progression. Importantly, SOX2 expression at first surgery was strongly related to meningioma clinical behavior, histological grade and risk of recurrence. Finally, survival data suggest a prognostic role of SOX2 expression in the whole series, both for overall and for recurrence-free survival (p < 0.0001 and p = 0.0001, respectively). Thus, SOX2 assessment could be of great help to clinicians in informing adjuvant treatments during follow-up.

Spontaneous intracerebral hemorrhage (ICH) has an increasing incidence and a worse outcome in elderly patients. The ability to predict the functional outcome in these patients can be helpful in supporting treatment decisions and establishing prognostic expectations. We evaluated the performance of a machine learning (ML) model to predict the 6-month functional status in elderly patients with ICH leveraging the predictive value of the clinical characteristics at hospital admission. Data were extracted by a retrospective multicentric database of patients ≥ 70 years of age consecutively admitted for the management of spontaneous ICH between January 1, 2014 and December 31, 2019. Relevant demographic, clinical, and radiological variables were selected by a feature selection algorithm (Boruta) and used to build a ML model. Outcome was determined according to the Glasgow Outcome Scale (GOS) at 6 months from ICH: dead (GOS 1), poor outcome (GOS 2-3: vegetative status/severe disability), and good outcome (GOS 4-5: moderate disability/good recovery). Ten features were selected by Boruta with the following relative importance order in the ML model: Glasgow Coma Scale, Charlson Comorbidity Index, ICH score, ICH volume, pupillary status, brainstem location, age, anticoagulant/antiplatelet agents, intraventricular hemorrhage, and cerebellar location. Random forest prediction model, evaluated on the hold-out test set, achieved an AUC of 0.96 (0.94-0.98), 0.89 (0.86-0.93), and 0.93 (0.90-0.95) for dead, poor, and good outcome classes, respectively, demonstrating high discriminative ability. A random forest classifier was successfully trained and internally validated to stratify elderly patients with spontaneous ICH into prognostic subclasses. The predictive value is enhanced by the ability of ML model to identify synergy among variables., (© 2022. The Author(s).)

Background: Several types of palliative surgery to treat drug-resistant epilepsy (DRE) have been reported, but the evidence that is available is insufficient to help physicians redirect patients with DRE to the most appropriate kind of surgery., Methods: A systematic search in the PubMed and Scopus databases was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to compare different clinical features, outcomes, and complications of adult patients submitted to callosotomy, vagal nerve stimulation, multiple subpial transections, deep brain stimulation, or responsive neurostimulation., Results: After 3447 articles were screened, 36 studies were selected, including the data of 1628 patients: 76 were treated with callosotomy, 659 were treated with vagal nerve stimulation, 416 were treated with deep brain stimulation, and 477 were treated with responsive neurostimulation. No studies including patients treated with multiple subpial transections met the inclusion criteria. The global weighted average seizure frequency reduction was 50.23%, and the global responder rate was 52.12%. There were significant differences among the palliative surgical procedures in term of clinical features of patients and epilepsy, seizure frequency reduction, and percentage of responders. Complications were differently distributed as well., Conclusions: Our analysis highlights the necessity of prospective studies, possibly randomized controlled trials, to compare different forms of palliative epilepsy surgery. Moreover, by identifying the outcome predictors associated with each technique, the best responder may be profiled for each procedure., (Copyright © 2022 Elsevier Inc. All rights reserved.)

5-aminolevulinic acid (5-ALA)-induced PpIX fluorescence is used by neurosurgeons to identify the tumor cells of high-grade gliomas during operation. However, the issue of whether 5-ALA-induced PpIX fluorescence consistently stains all the tumor cells is still debated. Here, we assessed the cytoplasmatic signal of 5-ALA by fluorescence microscopy in a series of human gliomas. As tumor markers, we used antibodies against collapsin response-mediated protein 5 (CRMP5), alpha thalassemia/mental retardation syndrome X-linked (ATRX), and anti-isocitrate dehydrogenase 1 (IDH1). In grade III-IV gliomas, the signal induced by 5-ALA was detected in 32.7-75.5 percent of CRMP5-expressing tumor cells. In low-grade gliomas (WHO grade II), the CRMP5-expressing tumor cells did not fluoresce following 5-ALA. Immunofluorescence with antibodies that stain various components of the blood-brain barrier (BBB) suggested that 5-ALA does not cross the un-breached BBB, in spite of its small dimension. To conclude, 5-ALA-induced PpIX fluorescence has an established role in high-grade glioma surgery, but it has limited usefulness in surgery for low-grade glioma, especially when the BBB is preserved.

Decompressive craniectomy (DC) is effective in controlling increasing intracranial pressure determined by a wide range of conditions, mainly traumatic brain injury (TBI) and stroke, and the subsequent cranioplasty (CP) displays potential therapeutic benefit in terms of overall neurological function. While autologous bone flap (ABF) harvested at the time of DC is the ideal material for skull defect reconstruction, it carries several risks. Aseptic bone flap resorption (BFR) is one of the most common complications, often leading to surgical failure. The aim of our study was to systematically review the literature and carry out a meta-analysis of possible factors involved in BFR in patients undergoing ABF cranioplasty after DC. A systematic review and meta-analysis was performed in accordance with the PRISMA guidelines. Different medical databases (PubMed, Embase, and Scopus) were screened for eligible scientific reports until April 30th 2021. The following data were collected for meta-analysis to assess their role in BFR: sex, age, the interval time between DC and CP, the presence of systemic factors, the etiology determining the DC, CP surgical time, CP features, VP shunt placement, CP infection. Studies including pediatric patients or with less than 50 patients were excluded. Fifteen studies were included. There was a statistically significant increased incidence of BFR in patients with CPF > 2 compared to patients with CPF ≤ 2 (54.50% and 22.76% respectively, p = 0.010). TBI was a significantly more frequent etiology in the BFR group compared to patients without BFR (61.95% and 47.58% respectively, p < 0.001). Finally, patients with BFR were significantly younger than patients without BFR (39.12 ± 15.36 years and 47.31 ± 14.78 years, respectively, p < 0.001). The funnel plots were largely symmetrical for all the studied factors. Bone flap fragmentation, TBI etiology, and young age significantly increase the risk of bone resorption. Further studies are needed to strengthen our results and to clarify if, in those cases, a synthetic implant for primary CP should be recommended., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Lumbosacral chordoma is a slow-growing but locally aggressive tumor, resistant to adjuvant treatments and endowed with dismal prognosis. Surgery is the mainstay of treatment but the choice of surgical approach (the posterior-only approach or the combined anterior-posterior approach) remains an open question due to the need of both pursuing a surgical radicality and preserving the neurologic function. The aim of the study was to compare the surgical and clinical outcomes of these approaches in the management of lumbosacral chordomas. A systematic review and meta-analysis in agreement with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines of papers comparing the outcomes of the two approaches was performed. Ten papers met the inclusion criteria. The combined anterior-posterior approach was more frequently performed for tumors with an upper level beyond S2 (p = 0.012). The 5-year progression-free survival was significantly higher in posterior-only approach compared with the combined anterior-posterior approach (44.7% vs 27.1%, p = 0.049). Adjuvant radiotherapy was added more frequently after a posterior-only approach (p = 0.036) and the rate of complications was significantly lower after a posterior-only approach (p = 0.040). No significant differences in sex, age, tumor diameter, entity of resection, and overall survival were observed. Posterior-only surgical approach may be a reasonable option for lumbosacral chordoma, being associated with comparable entity of surgical resection, reduced complication rate and increased 5-year progression-free survival rate as compared with combined anterior-posterior approach., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The prognostic role of epidermal growth factor receptor variant III (EGFRvIII), a constitutively activated oncogenic receptor, in glioblastoma is controversial. We performed a prospective study enrolling 355 patients operated on for de novo glioblastoma at a large academic center. The molecular profile, including EGFRvIII status, MGMT promoter methylation, and VEGF expression, was assessed. Standard parameters (age, clinical status and extent of surgical resection) were confirmed to hold prognostic value. MGMT promoter methylation portended a slightly improved survival. In the whole series, confirming previous results, EGFRvIII was not associated with worsened prognosis. Interestingly, female sex was associated with a better outcome. Such findings are of interest for the design of future trials.

Introduction: Artificial intelligence (AI) and machine learning (ML) augment decision-making processes and productivity by supporting surgeons over a range of clinical activities: from diagnosis and preoperative planning to intraoperative surgical assistance. We reviewed the literature to identify current AI platforms applied to neurosurgical perioperative and intraoperative settings and describe their role in multiple subspecialties., Evidence Acquisition: A systematic review of the literature was conducted following the PRISMA guidelines. PubMed, EMBASE, and Scopus databases were searched from inception to December 31 st , 2020. Original articles were included if they: presented AI platforms implemented in perioperative, intraoperative settings and reported ML models' performance metrics. Due to the heterogeneity in neurosurgical applications, a qualitative synthesis was deemed appropriate. The risk of bias and applicability of predicted outcomes were assessed using the PROBAST tool., Evidence Synthesis: Forty-one articles were included. All studies evaluated a supervised learning algorithm. A total of 10 ML models were described; the most frequent were neural networks (N.=15) and tree-based models (N.=13). Overall, the risk of bias was medium-high, but applicability was considered positive for all studies. Articles were grouped into four categories according to the subspecialty of interest: neuro-oncology, spine, functional and other. For each category, different prediction tasks were identified., Conclusions: In this review, we summarize the state-of-art applications of AI for the intraoperative augmentation of neurosurgical workflows across multiple subspecialties. ML models may boost surgical team performances by reducing human errors and providing patient-tailored surgical plans, but further and higher-quality studies need to be conducted.

Background: Neuroimaging differentiation of glioblastoma, primary central nervous system lymphoma (PCNSL) and solitary brain metastasis (BM) remains challenging in specific cases showing similar appearances or atypical features. Overall, advanced MRI protocols have high diagnostic reliability, but their limited worldwide availability, coupled with the overlapping of specific neuroimaging features among tumor subgroups, represent significant drawbacks and entail disparities in the planning and management of these oncological patients., Objective: To evaluate the classification performance metrics of a deep learning algorithm trained on T1-weighted gadolinium-enhanced (T1Gd) MRI scans of glioblastomas, atypical PCNSLs and BMs., Materials and Methods: We enrolled 121 patients (glioblastoma: n=47; PCNSL: n=37; BM: n=37) who had undergone preoperative T1Gd-MRI and histopathological confirmation. Each lesion was segmented, and all ROIs were exported in a DICOM dataset. The patient cohort was then split in a training and hold-out test sets following a 70/30 ratio. A Resnet101 model, a deep neural network (DNN), was trained on the training set and validated on the hold-out test set to differentiate glioblastomas, PCNSLs and BMs on T1Gd-MRI scans., Results: The DNN achieved optimal classification performance in distinguishing PCNSLs (AUC: 0.98; 95%CI: 0.95 - 1.00) and glioblastomas (AUC: 0.90; 95%CI: 0.81 - 0.97) and moderate ability in differentiating BMs (AUC: 0.81; 95%CI: 0.70 - 0.95). This performance may allow clinicians to correctly identify patients eligible for lesion biopsy or surgical resection., Conclusion: We trained and internally validated a deep learning model able to reliably differentiate ambiguous cases of PCNSLs, glioblastoma and BMs by means of T1Gd-MRI. The proposed predictive model may provide a low-cost, easily-accessible and high-speed decision-making support for eligibility to diagnostic brain biopsy or maximal tumor resection in atypical cases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Tariciotti, Caccavella, Fiore, Schisano, Carrabba, Borsa, Giordano, Palmisciano, Remoli, Remore, Pluderi, Caroli, Conte, Triulzi, Locatelli and Bertani.)

Purpose  Transsphenoidal surgery (TSS) for pituitary adenomas can be complicated by the occurrence of intraoperative cerebrospinal fluid (CSF) leakage (IOL). IOL significantly affects the course of surgery predisposing to the development of postoperative CSF leakage, a major source of morbidity and mortality in the postoperative period. The authors trained and internally validated the Random Forest (RF) prediction model to preoperatively identify patients at high risk for IOL. A locally interpretable model-agnostic explanations (LIME) algorithm is employed to elucidate the main drivers behind each machine learning (ML) model prediction. Methods  The data of 210 patients who underwent TSS were collected; first, risk factors for IOL were identified via conventional statistical methods (multivariable logistic regression). Then, the authors trained, optimized, and audited a RF prediction model. Results  IOL reported in 45 patients (21.5%). The recursive feature selection algorithm identified the following variables as the most significant determinants of IOL: Knosp's grade, sellar Hardy's grade, suprasellar Hardy's grade, tumor diameter (on X, Y, and Z axes), intercarotid distance, and secreting status (nonfunctioning and growth hormone [GH] secreting). Leveraging the predictive values of these variables, the RF prediction model achieved an area under the curve (AUC) of 0.83 (95% confidence interval [CI]: 0.78; 0.86), significantly outperforming the multivariable logistic regression model (AUC = 0.63). Conclusion  A RF model that reliably identifies patients at risk for IOL was successfully trained and internally validated. ML-based prediction models can predict events that were previously judged nearly unpredictable; their deployment in clinical practice may result in improved patient care and reduced postoperative morbidity and healthcare costs., Competing Interests: Conflict of Interest None declared., (Thieme. All rights reserved.)

Spontaneous intracranial hypotension (SIH) is an often misdiagnosed condition resulting from non-iatrogenic cerebrospinal fluid (CSF) hypovolemia, typically secondary to spinal CSF leakage. Patients commonly present with posture-related headache, nausea, and vomiting. Following failure of conservative measures, epidural blood patching (EBP) is the most commonly performed intervention for spinal CSF leaks. The authors performed a systematic review and meta-analysis of existing literature to evaluate the role of different factors possibly affecting the efficacy of the EBP procedure. In accordance with the PRISMA guidelines, PubMed/Medline and SCOPUS databases were searched. Six eligible articles were retrieved. Five hundred patients were treated for SIH with EBP, of which 300 reported good response defined as complete remission of symptoms within 48 h after the first EBP requiring no further invasive treatment. Among the factors available for meta-analysis, none was found to be statistically significant in affecting the efficacy of the EBP procedure. A largely symmetrical funnel plot is reported for all the variables evaluated, indicating that publication bias did not play a significant role in the observed effects. The current knowledge about SIH and the EBP is scarce. The existing literature is contradictory and insufficient to aid in clinical practice. More studies are needed to draw significant conclusions that may help in the identification of patients at higher risk of EBP failure, who may benefit from different approaches., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)

Background: Ability to thrive and time-to-recurrence following treatment are important parameters to assess in patients with glioblastoma multiforme (GBM), given its dismal prognosis. Though there is an ongoing debate whether it can be considered an appropriate surrogate endpoint for overall survival in clinical trials, progression-free survival (PFS) is routinely used for clinical decision-making., Objective: To investigate whether machine learning (ML)-based models can reliably stratify newly diagnosed GBM patients into prognostic subclasses on PFS basis, identifying those at higher risk for an early recurrence (≤6 mo)., Methods: Data were extracted from a multicentric database, according to the following eligibility criteria: histopathologically verified GBM and follow-up >12 mo: 474 patients met our inclusion criteria and were included in the analysis. Relevant demographic, clinical, molecular, and radiological variables were selected by a feature selection algorithm (Boruta) and used to build a ML-based model., Results: Random forest prediction model, evaluated on an 80:20 split ratio, achieved an AUC of 0.81 (95% CI: 0.77; 0.83) demonstrating high discriminative ability. Optimizing the predictive value derived from the linear and nonlinear combinations of the selected input features, our model outperformed across all performance metrics multivariable logistic regression., Conclusion: A robust ML-based prediction model that identifies patients at high risk for early recurrence was successfully trained and internally validated. Considerable effort remains to integrate these predictions in a patient-centered care context., (© Congress of Neurological Surgeons 2021.)

Brain biopsy is the gold standard in order to establish the diagnosis of unresectable brain tumors. Few studies have investigated the long-term outcomes of biopsy patients. The aim of this single-institution-based study was to assess the concordance between radiological and histopathological diagnoses, and the long-term patient outcome. Ninety-three patients who underwent brain biopsy in the last 5 years were analyzed. We included patients treated with stereotactically guided needle, open, and neuroendoscopic biopsies. Most patients (86%) received needle biopsy. Gliomas and primary brain lymphomas comprised 88.2% of cases. The diagnostic yield was 95.7%. Serious complication and death rates were 3.2% and 2.1%, respectively. The concordance rate between radiological and histological diagnoses was 93%. Notably, the positive predictive value of radiological diagnosis of lymphoma was 100%. Biopsy allowed specific treatment in 72% of cases. Disease-related neurological worsening was the main reason that precluded adjuvant treatment. Adjuvant treatment, in turn, was the strongest prognostic factor, since the median overall survival was 11 months with vs. 2 months without treatment ( p = 0.0002). Finally, advanced molecular evaluations can be obtained on glioma biopsy specimens to provide integrated diagnoses and individually tailored treatments. We conclude that, despite the huge advances in imaging techniques, biopsy is required when an adjuvant treatment is recommended, particularly in gliomas.

Objective: Ability to thrive after invasive and intensive treatment is an important parameter to assess in patients with glioblastoma multiforme (GBM). Karnofsky Performance Status (KPS) is used to identify those patients suitable for postoperative radiochemotherapy. The aim of the present study is to investigate whether machine learning (ML)-based models can reliably predict patients' KPS 6 months after surgery., Methods: A cohort of 416 patients undergoing surgery for a histopathologically confirmed GBM were collected from a multicentric database and split into a training and hold-out test set in an 80:20 ratio. Worsening of KPS at 6 months after surgery (compared with preoperative KPS) occurred in 138 patients (33.2%). Relevant preoperative, intraoperative, and immediately postoperative variables were selected by a recursive features selection algorithm (Boruta) and used to build 2 ML-based predictive models., Results: A random forest classifier and a random forest regressor were trained to predict 6 months postoperative KPS as a categorical (worsening vs. stable/improving) and continuous variables; they achieved, respectively, an area under the curve of 0.81 (95% confidence interval, 0.76-0.84) and a mean absolute error of 4.4 (95% confidence interval, 4.0-4.7). Leveraging the predictive value resulting from the combination of independent variables, the random forest classifier outperformed conventional statistics (area under the curve improvement of +21%)., Conclusions: Two robust ML-based prediction models were successfully trained and internally validated. Considerable effort remains to improve the interpretation of the results when these predictions are used in a patient-centered care context., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objective: Providing new tools to improve surgical planning is considered a main goal in meningioma treatment. In this context, two factors are crucial in determining operating strategy: meningioma-brain interface and meningioma consistency. The use of intraoperative ultrasound (ioUS) elastosonography, a real-time imaging technique, has been introduced in general surgery to evaluate similar features in other pathological settings such as thyroid and prostate cancer. The aim of the present study was to evaluate ioUS elastosonography in the intraoperative prediction of key intracranial meningioma features and to evaluate its application in guiding surgical strategy., Methods: An institutional series of 36 meningiomas studied with ioUS elastosonography is reported. Elastographic data, intraoperative surgical findings, and corresponding preoperative MRI features were classified, applying a score from 0 to 2 to both meningioma consistency and meningioma-brain interface. Statistical analysis was performed to determine the degree of agreement between meningioma elastosonographic features and surgical findings, and whether intraoperative elastosonography was a better predictor than preoperative MRI in assessing meningioma consistency and slip-brain interface, using intraoperative findings as the gold standard., Results: A significantly high degree of reliability and agreement between ioUS elastographic scores and surgical finding scores was reported (intraclass correlation coefficient = 0.848, F = 12.147, p < 0.001). When analyzing both consistency and brain-tumor interface, ioUS elastography proved to have a rather elevated sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and positive (LR+) and negative likelihood ratio (LR-). This consideration was true especially for meningiomas with a hard consistency (sensitivity = 0.92, specificity = 0.96, PPV = 0.92, NPV = 0.96, LR+ = 22.00, LR- = 0.09) and for those presenting with an adherent slip-brain interface (sensitivity = 0.76, specificity = 0.95, PPV = 0.93, NPV = 0.82, LR+ = 14.3, LR- = 0.25). Furthermore, predictions derived from ioUS elastography were found to be more accurate than MRI-derived predictions, as demonstrated by McNemar's test results in both consistency (p < 0.001) and interface (p < 0.001)., Conclusions: While external validation of the data is needed to transform ioUS elastography into a fully deployable clinical tool, this experience confirmed that it may be integrated into meningioma surgical planning, especially because of its rapidity and cost-effectiveness.

The current gold standard surgical treatment for medication-resistant essential tremor (ET) is deep brain stimulation (DBS). However, recent advances in technologies have led to the development of incisionless techniques, such as magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy. The authors perform a systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement to compare unilateral MRgFUS thalamotomy to unilateral and bilateral DBS in the treatment of ET in terms of tremor severity and quality of life improvement. PubMed, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials and SCOPUS databases were searched. 45 eligible articles, published between 1990 and 2019, were retrieved. 1202 patients were treated with DBS and 477 were treated with MRgFUS thalamotomy. Postoperative tremor improvement was greater following DBS than MRgFUS thalamotomy (p<0.001). A subgroup analysis was carried out stratifying by treatment laterality: bilateral DBS was significantly superior to both MRgFUS and unilateral DBS (p<0.001), but no significant difference was recorded between MRgFUS and unilateral DBS (p<0.198). Postoperative quality of life improvement was significantly greater following MRgFUS thalamotomy than DBS (p<0.001). Complications were differently distributed among the two groups (p<0.001). Persistent complications were significantly more common in the MRgFUS group (p=0.042). While bilateral DBS proves superior to unilateral MRgFUS thalamotomy in the treatment of ET, a subgroup analysis suggests that treatment laterality is the most significant determinant of tremor improvement, thus highlighting the importance of future investigations on bilateral staged MRgFUS thalamotomy., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: In parallel with the progress in neurosurgery, improvements in residents' training strategies have been reported. Increasing focus has been placed on residents' participation in research. Previous studies analyzed neurosurgery residents' contributions to research activities, time dedicated to research, and outcomes. However, few studies investigating these aspects outside the United States are present in the literature., Methods: A 3-section survey was sent to neurosurgery residents in Italy to determine the current opinion, perceptions, and experiences in the research field. A review of the pertinent literature was carried out., Results: Ninety-seven responding residents (response rate of 41.5%) self-reported an average time spent on research of 9.7 ± 11.4 hours/week. In decreasing frequency, residents were working on retrospective cohort studies (27.5%), case reports (21.7%), case series (15.5%), prospective cohort studies (13.4%), and others (16.4%). The most commonly reported factors promoting interest in research were interaction with peers (76.3%), mentorship (70.1%), and conference exposure (52.6%). Reported strategies of program support were heterogeneous with a prevalence for established collaborative agreements (59.8%) and the presence of a study coordinator (37.1%). The most frequently cited limiting factors were regulatory paperwork (70.1%), call schedule (60.8%), and lack of participating students/residents (57.7%)., Conclusions: By describing the current status of Italian residents' participation in research, we provide additional insight into factors supporting research involvement and existing barriers. Strategies for improvement at national and departmental levels are suggested. We encourage further investigations in other countries, to provide useful information in a worldwide framework., (Copyright © 2020 Elsevier Inc. All rights reserved.)

A major complication in cranial and spinal surgery is the post-operative occurrence of a cerebrospinal fluid (CSF) leak. Here we reported a technical note firstly describing the use of Hemopatch® with fibrin glue as a dural sealant in cranial and spinal neurosurgical procedures. Moreover we carried out a review of the literature. Further to the best of our knowledge this was the first series including patients submitted to different spinal surgeries in whom Hemopatch® was used as dural sealant. We prospectively collected the data of 22 patients. In all procedures, fibrin glue was applied after Hemopatch®. The mean age was 59.68 ± 10.79 years and the mean follow-up (FU) was 3.63 ± 1.46 months, respectively. Overall, Hemopatch® with fibrin glue was used in 8 cranial procedures (36.36%; all were retrosigmoid craniotomies) and 14 spinal procedures (63.64%). 9/14 spinal cases (64.28%) were incidental durotomies during a spinal decompression procedure. No CSF leak, no postoperative infection, no adverse reaction were observed during the FU in all cases. The literature search revealed only two retrospective series, reporting only patients submitted to cranial surgery for a total of 56 patients and a CSF leak occurring in 3 patients (5.35%). In conclusion, we firstly reported the feasibility and the safety of using Hemopatch® with fibrin glue as dural sealant in cranial surgery and different spinal procedures. Further larger comparative studies are needed to confirm our initial encouraging results., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objective: Recent years have witnessed an increase in articles describing factors influencing medical student recruitment in neurosurgery, such as undergraduate preparation, impact of research experience, and selection into residency programs. In this study, we provide a comprehensive review of the literature addressing the relationship of medical students within neurosurgery., Methods: A search of the literature was conducted on the PubMed/MEDLINE database to October 2018 to screen for studies on medical student interest and recruitment in neurosurgery. Articles were screened for eligibility and reviewed for inclusion and their findings critically discussed., Results: Sixty-nine articles were included. Most research on the relationship of medical students with neurosurgery was conducted in the United States and United Kingdom. Data analysis was categorized into 2 groups: educational and noneducational factors. Eight areas of interest were identified: baseline undergraduate education, early research involvement, attitude toward neuroscience, mentoring, existence of a gender gap, residency program requirements, availability of educational resources, and networking opportunities., Conclusions: Our study bridges the gap of fragmented knowledge on medical student involvement in neurosurgery with the aim of optimizing existing approaches. We suggest that medical institutions outside the United States and United Kingdom should implement university-based interest groups to stimulate student interest, with reinforced participation of faculty for leading educational initiatives and collaborative research. We advocate the creation of national and international associations to support medical students in approaching neurosurgery early in their education., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Osteoblastomas are rare primary bone tumors with a predilection for the spine. The extraosseous growth pattern is rare, and to our knowledge, only 2 cases of fully extraosseous osteoblastomas have been previously reported., Case Description: A man aged 36 years presented with a 7-month history of low back pain radiating to the gluteal area. On examination, a typical L5 radiculopathy was noted. The radiologic examinations conducted in the previous months pointed out the rapid growth of an extraosseous mass occluding the right L5-S1 foramen. Partial laminectomy was performed to achieve gross total resection. Histological analysis was consistent with osteoblastoma., Conclusions: Osteoblastomas with extraosseous extension are uncommon, and an exclusively extraosseous presentation is anecdotal. This can lead to preoperative misdiagnosis when typical radiologic characteristics of bone-forming tumors are missing. We describe the case of an extraosseous lumbar osteoblastoma whose clinical and radiologic presentation was suggestive of malignancy., (Copyright © 2020 Elsevier Inc. All rights reserved.)