Computer-based simulation appears to be a valuable teaching tool for non-experts in a highly technical procedural task such as pedicle screw placement that involves sequential learning, depth perception, and understanding triplanar anatomy.

OBJECTIVEGlioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) are common intracranial pathologies encountered by neurosurgeons. They often may have similar radiological findings, making diagnosis difficult without surgical biopsy; however, management is quite different between these two entities. Recently, predictive analytics, including machine learning (ML), have garnered attention for their potential to aid in the diagnostic assessment of a variety of pathologies. Several ML algorithms have recently been designed to differentiate GBM from PCNSL radiologically with a high sensitivity and specificity. The objective of this systematic review and meta-analysis was to evaluate the implementation of ML algorithms in differentiating GBM and PCNSL.METHODSThe authors performed a systematic review of the literature using PubMed in accordance with PRISMA guidelines to select and evaluate studies that included themes of ML and brain tumors. These studies were further narrowed down to focus on works published between January 2008 and May 2018 addressing the use of ML in training models to distinguish between GBM and PCNSL on radiological imaging. Outcomes assessed were test characteristics such as accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).RESULTSEight studies were identified addressing use of ML in training classifiers to distinguish between GBM and PCNSL on radiological imaging. ML performed well with the lowest reported AUC being 0.878. In studies in which ML was directly compared with radiologists, ML performed better than or as well as the radiologists. However, when ML was applied to an external data set, it performed more poorly.CONCLUSIONSFew studies have applied ML to solve the problem of differentiating GBM from PCNSL using imaging alone. Of the currently published studies, ML algorithms have demonstrated promising results and certainly have the potential to aid radiologists with difficult cases, which could expedite the neurosurgical decision-making process. It is likely that ML algorithms will help to optimize neurosurgical patient outcomes as well as the cost-effectiveness of neurosurgical care if the problem of overfitting can be overcome.

The systematic implementation of a simulation curriculum in a neurosurgery training program is feasible, is favorably regarded, and has a positive impact on trainees of all levels, particularly in junior years. All simulation forms, cadaver, physical, and haptic/computerized, have a role in different stages of learning and should be considered in the development of an educational simulation program.

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Virtual computer-based simulators with integrated haptic technology may improve tactile discrimination required for microsurgical technique.

Introduction: The use of intraoperative CT-guidance during the percutaneous treatment of trigeminal neuralgia has become increasingly popular due to the greater ease of foramen ovale cannulation and decreased procedure times. Concerns regarding radiation dose to the patient, however, remain unaddressed. We sought to compare the emitted radiation dose from fluoroscopy with intraoperative CT for these procedures.Methods: A retrospective review of percutaneous lesioning procedures for trigeminal neuralgia performed between 2010 until 2012 at our institution was conducted and radiation doses to the patient were recorded. We subsequently simulated four separate percutaneous trigeminal rhizotomies using the O-arm intraoperative CT (Medtronics, Minneapolis, MN, USA) to cannulate the foramen ovale bilaterally in two formalin-fixed cadaver heads.Results: Seventeen successful percutaneous treatments for trigeminal neuralgia were performed during the study period. Eleven procedures containing complete records were included in the final analysis. For procedures using fluoroscopy, the mean dosage was 15.2 mGys (range: 1.15 - 47.95, 95% CI 7.34 – 22.99). Radiation dosage from the O-arm imaging system was 16.55 mGy for all four cases. An unequal variance t-test did not reach statistical significance (p=0.42).Conclusions: We did not observe a significant difference in radiation dose delivered to subjects when comparing CT-guided foramen ovale cannulation relative to fluoroscopy for percutaneous lesioning of the Gasserian ganglion. Additional study is required under operational settings.

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Background: Shifting paradigms in neurosurgical education are promoting the development of different simulators in order to promote faster and safer surgical training. Neuroendoscopy simulators have been created with the intention of decreasing the learning curve of resident training in neuroendoscopy techniques. The objective was to study the potential usefulness of organized implementation of neuroendoscopy simulators in resident training, with particular attention to resident feedback and cost. Methods: A total of 19 residents from two separate academic institutions performed 83 simulated endoscopic procedures. These were classified as ventricular (n = 49) and skull base (n = 34). In turn, each procedure was classified into one of three difficulty levels (easy, medium, and hard). Evaluations regarding self-perceived performance were completed after each exercise in accordance with a Physician Performance Diagnostic Inventory Scale based on the Likert format. Subject identification was blinded to junior or senior resident. Wilcoxon rank testing was used to compare the self-perceived performance improvement within and between both groups. Results: Perceived improvement was statistically significant for all the ventricular and skull base/pituitary simulation procedures listed (P 5 0.001) based on the Wilcoxon sign rank test. These results were not particularly influenced by simulation exercise group (ventricular vs skull base, P = 0.48), institution (United States vs Brazil, P = 0.44), resident training level (junior vs senior, P = 0.48), or the level of difficulty of the simulation procedure (easy, medium, hard, P = 0.98). The average cost of the ventricular and skull base/pituitary simulation modules was US$6367.50 and US$7065.50, respectively, per program. Conclusion: The use of neuroendoscopic surgery simulators in neurosurgical training is regarded favorably by trainees and should be considered as an adjuvant in neurosurgical simulation training curricula.