OBJECTIVEIn daily practice, neurosurgeons face increasing numbers of patients using aspirin (acetylsalicylic acid, ASA). While many of these patients discontinue ASA 7–10 days prior to elective intracranial surgery, there are limited data to support whether or not perioperative ASA use heightens the risk of hemorrhagic complications. In this study the authors retrospectively evaluated the safety of perioperative ASA use in patients undergoing craniotomy for brain tumors in the largest elective cranial surgery cohort reported to date.METHODSThe authors retrospectively analyzed the medical records of 1291 patients who underwent elective intracranial tumor surgery by a single surgeon from 2007 to 2017. The patients were divided into three groups based on their perioperative ASA status: 1) group 1, no ASA; 2) group 2, stopped ASA (low cardiovascular risk); and 3) group 3, continued ASA (high cardiovascular risk). Data collected included demographic information, perioperative ASA status, tumor characteristics, extent of resection (EOR), operative blood loss, any hemorrhagic and thromboembolic complications, and any other complications.RESULTSA total of 1291 patients underwent 1346 operations. The no-ASA group included 1068 patients (1112 operations), the stopped-ASA group had 104 patients (108 operations), and the continued-ASA group had 119 patients (126 operations). The no-ASA patients were significantly younger (mean age 53.3 years) than those in the stopped- and continued-ASA groups (mean 64.8 and 64.0 years, respectively; p < 0.001). Sex distribution was similar across all groups (p = 0.272). Tumor locations and pathologies were also similar across the groups, except for deep tumors and schwannomas that were relatively less frequent in the continued-ASA group. There were no differences in the EOR between groups. Operative blood loss was not significantly different between the stopped- (186 ml) and continued- (220 ml) ASA groups (p = 0.183). Most importantly, neither hemorrhagic (0.6%, 0.9%, and 0.8%, respectively; p = 0.921) nor thromboembolic (1.3%, 1.9%, and 0.8%; p = 0.779) complication rates were significantly different between the groups, respectively. In addition, the multivariate model revealed no statistically significant predictor of hemorrhagic complications, whereas male sex (odds ratio [OR] 5.9, 95% confidence interval [CI] 1.7–20.5, p = 0.005) and deep-extraaxial-benign (“skull base”) tumors (OR 3.6, 95% CI 1.3–9.7, p = 0.011) were found to be independent predictors of thromboembolic complications.CONCLUSIONSIn this cohort, perioperative ASA use was not associated with the increased rate of hemorrhagic complications following intracranial tumor surgery. In patients at high cardiovascular risk, ASA can safely be continued during elective brain tumor surgery to prevent potential life-threatening thromboembolic complications. Randomized clinical trials with larger sample sizes are warranted to achieve a greater statistical power.

OBJECTIVE Cerebrovascular bypass surgery is a challenging yet important neurosurgical procedure that is performed to restore circulation in the treatment of carotid occlusive diseases, giant/complex aneurysms, and skull base tumors. It requires advanced microsurgical skills and dedicated training in microsurgical techniques. Most available training tools, however, either lack the realism of the actual bypass surgery (e.g., artificial vessel, chicken wing models) or require special facilities and regulations (e.g., cadaver, live animal, placenta models). The aim of the present study was to design a readily accessible, realistic, easy-to-build, reusable, and high-fidelity simulator to train neurosurgeons or trainees on vascular anastomosis techniques even in the operating room. METHODS The authors used an anatomical skull and brain model, artificial vessels, and a water pump to simulate both extracranial and intracranial circulations. They demonstrated the step-by-step preparation of the bypass simulator using readily available and affordable equipment and consumables. RESULTS All necessary steps of a superficial temporal artery-middle cerebral artery bypass surgery (from skin opening to skin closure) were performed on the simulator under a surgical microscope. The simulator was used by both experienced neurosurgeons and trainees. Feedback survey results from the participants of the microsurgery course suggested that the model is superior to existing microanastomosis training kits in simulating real surgery conditions (e.g., depth, blood flow, anatomical constraints) and holds promise for widespread use in neurosurgical training. CONCLUSIONS With no requirement for specialized laboratory facilities and regulations, this novel, low-cost, reusable, high-fidelity simulator can be readily constructed and used for neurosurgical training with various scenarios and modifications.

BackgroundVisualizing and comprehending 3-dimensional (3D) neuroanatomy is challenging. Cadaver dissection is limited by low availability, high cost, and the need for specialized facilities. New technologies, including 3D rendering of neuroimaging, 3D pictures, and 3D videos, are filling this gap and facilitating learning, but they also have limitations. This proof-of-concept study explored the feasibility of combining the spatial accuracy of 3D reconstructed neuroimaging data with realistic texture and fine anatomical details from 3D photogrammetry to create high-fidelity cadaveric neurosurgical simulations.MethodsFour fixed and injected cadaver heads underwent neuroimaging. To create 3D virtual models, surfaces were rendered using magnetic resonance imaging (MRI) and computed tomography (CT) scans, and segmented anatomical structures were created. A stepwise pterional craniotomy procedure was performed with synchronous neuronavigation and photogrammetry data collection. All points acquired in 3D navigational space were imported and registered in a 3D virtual model space. A novel machine learning-assisted monocular-depth estimation tool was used to create 3D reconstructions of 2-dimensional (2D) photographs. Depth maps were converted into 3D mesh geometry, which was merged with the 3D virtual model’s brain surface anatomy to test its accuracy. Quantitative measurements were used to validate the spatial accuracy of 3D reconstructions of different techniques.ResultsSuccessful multilayered 3D virtual models were created using volumetric neuroimaging data. The monocular-depth estimation technique created qualitatively accurate 3D representations of photographs. When 2 models were merged, 63% of surface maps were perfectly matched (mean [SD] deviation 0.7 ± 1.9 mm; range −7 to 7 mm). Maximal distortions were observed at the epicenter and toward the edges of the imaged surfaces. Virtual 3D models provided accurate virtual measurements (margin of error &lt;1.5 mm) as validated by cross-measurements performed in a real-world setting.ConclusionThe novel technique of co-registering neuroimaging and photogrammetry-based 3D models can (1) substantially supplement anatomical knowledge by adding detail and texture to 3D virtual models, (2) meaningfully improve the spatial accuracy of 3D photogrammetry, (3) allow for accurate quantitative measurements without the need for actual dissection, (4) digitalize the complete surface anatomy of a cadaver, and (5) be used in realistic surgical simulations to improve neurosurgical education.

BACKGROUND:Understanding the microsurgical neuroanatomy of the brain is challenging yet crucial for safe and effective surgery. Training on human cadavers provides an opportunity to practice approaches and learn about the brain's complex organization from a surgical view. Innovations in visual technology, such as virtual reality (VR) and augmented reality (AR), have immensely added a new dimension to neuroanatomy education. In this regard, a 3-dimensional (3D) model and AR/VR application may facilitate the understanding of the microsurgical neuroanatomy of the brain and improve spatial recognition during neurosurgical procedures by generating a better comprehension of interrelated neuroanatomic structures.OBJECTIVE:To investigate the results of 3D volumetric modeling and AR/VR applications in showing the brain's complex organization during fiber dissection.METHODS:Fiber dissection was applied to the specimen, and the 3D model was created with a new photogrammetry method. After photogrammetry, the 3D model was edited using 3D editing programs and viewed in AR. The 3D model was also viewed in VR using a head-mounted display device.RESULTS:The 3D model was viewed in internet-based sites and AR/VR platforms with high resolution. The fibers could be panned, rotated, and moved freely on different planes and viewed from different angles on AR and VR platforms.CONCLUSION:This study demonstrated that fiber dissections can be transformed and viewed digitally on AR/VR platforms. These models can be considered a powerful teaching tool for improving the surgical spatial recognition of interrelated neuroanatomic structures. Neurosurgeons worldwide can easily avail of these models on digital platforms.