Innovations in craniovertebral junction training: harnessing the power of mixed reality and head-mounted displays.

OBJECTIVE: The objective of this study was to analyze the potential and convenience of using mixed reality as a teaching tool for craniovertebral junction (CVJ) anomaly pathoanatomy. METHODS: CT and CT angiography images of 2 patients with CVJ anomalies were used to construct mixed reality models in the HoloMedicine application on the HoloLens 2 headset, resulting in four viewing stations. Twenty-two participants were randomly allocated into two groups, with each participant rotating through all stations for 90 seconds, each in a different order based on their group. At every station, objective questions evaluating the understanding of CVJ pathoanatomy were answered. At the end, subjective opinion on the user experience of mixed reality was provided using a 5-point Likert scale. The objective performance of the two viewing modes was compared, and a correlation between performance and participant experience was sought. Subjective feedback was compiled and correlated with experience. RESULTS: In both groups, there was a significant improvement in median (interquartile range [IQR]) objective performance with mixed reality compared with DICOM: 1) group A: case 1, median 6 (IQR 6-7) versus 5 (IQR 3-6), p = 0.009; case 2, median 6 (IQR 6-7) versus 5 (IQR 3-6), p = 0.02; 2) group B: case 1, median 6 (IQR 5-7) versus 4 (IQR 2-5), p = 0.04; case 2, median 6 (IQR 6-7) versus 5 (IQR 3-7), p = 0.03. There was significantly higher improvement in less experienced participants in both groups for both cases: 1) group A: case 1, r = -0.8665, p = 0.0005; case 2, r = -0.8002, p = 0.03; 2) group B: case 1, r = -0.6977, p = 0.01; case 2, r = -0.7417, p = 0.009. Subjectively, mixed reality was easy to use, with less disorientation due to the visible background, and it was believed to be a useful teaching tool. CONCLUSIONS: Mixed reality is an effective teaching tool for CVJ pathoanatomy, particularly for young neurosurgeons and trainees. The versatility of mixed reality and the intuitiveness of the user experience offer many potential applications, including training, intraoperative guidance, patient counseling, and individualized medicine; consequently, mixed reality has the potential to transform neurosurgery.

Computer vision coaching microsurgical laboratory training: PRIME (Proficiency Index in Microsurgical Education) proof of concept.

Computer vision (CV) feedback could be aimed as a constant tutor to guide ones proficiency during microsurgical practice in controlled environments. Five neurosurgeons with different levels of microsurgical expertise performed simulated vessel dissection and micro-suture in an ex vivo model for posterior computer analysis of recorded videos. A computer program called PRIME (Proficiency Index of Microsurgical Education) used in this research recognized color-labeled surgical instruments, from downloading videos into a platform, with a range of motion greater than 3 mm, for objective evaluation of number of right and left hand movements. A proficiency index of 0 to 1 was pre-established in order to evaluate continuous training improvement. PRIME computer program captured all hand movements executed by participants, except for small tremors or inconsistencies that have a range of motion inferior to 3 mm. Number of left and right hand movements were graphically expressed in order to guide more objective and efficacious training for each trainee, without requiring body sensors and cameras around the operating table. Participants with previous microsurgical experience showed improvement from 0.2 to 0.6 (p < 0.05), while novices had no improvement. Proficiency index set by CV was suggested, in a self-challenge and self-coaching manner. PRIME would offer the capability of constant laboratory microsurgical practice feedback under CV guidance, opening a new window for oriented training without a tutor or specific apparatus regarding all levels of microsurgical proficiency. Prospective, large data study is needed to confirm this hypothesis.

Evaluation of simulation models in neurosurgical training according to face, content, and construct validity: a systematic review.

BACKGROUND: Neurosurgical training has been traditionally based on an apprenticeship model. However, restrictions on clinical exposure reduce trainees' operative experience. Simulation models may allow for a more efficient, feasible, and time-effective acquisition of skills. Our objectives were to use face, content, and construct validity to review the use of simulation models in neurosurgical education. METHODS: PubMed, Web of Science, and Scopus were queried for eligible studies. After excluding duplicates, 1204 studies were screened. Eighteen studies were included in the final review. RESULTS: Neurosurgical skills assessed included aneurysm clipping (n = 6), craniotomy and burr hole drilling (n = 2), tumour resection (n = 4), and vessel suturing (n = 3). All studies assessed face validity, 11 assessed content, and 6 assessed construct validity. Animal models (n = 5), synthetic models (n = 7), and VR models (n = 6) were assessed. In face validation, all studies rated visual realism favourably, but haptic realism was key limitation. The synthetic models ranked a high median tactile realism (4 out of 5) compared to other models. Assessment of content validity showed positive findings for anatomical and procedural education, but the models provided more benefit to the novice than the experienced group. The cadaver models were perceived to be the most anatomically realistic by study participants. Construct validity showed a statistically significant proficiency increase among the junior group compared to the senior group across all modalities. CONCLUSION: Our review highlights evidence on the feasibility of implementing simulation models in neurosurgical training. Studies should include predictive validity to assess future skill on an individual on whom the same procedure will be administered. This study shows that future neurosurgical training systems call for surgical simulation and objectively validated models.

Neurosurgical Assessment of Metrics Including Judgment and Dexterity Using the Virtual Reality Simulator NeuroTouch (NAJD Metrics).

Advances in computer-based technology has created a significant opportunity for implementing new training paradigms in neurosurgery focused on improving skill acquisition, enhancing procedural outcome, and surgical skills assessment. NeuroTouch is a computer-based virtual reality system that can generate output data known as metrics from operator performance during simulated brain tumor resection. These measures of quantitative assessment are used to track and compare psychomotor performance during simulated operative procedures. Data output from the NeuroTouch system is recorded in a comma-separated values file. Data mining from this file and subsequent metrics development requires the use of sophisticated software and engineering expertise. In this article, we introduce a system to extract a series of new metrics using the same data file using Excel software. Based on the data contained in the NeuroTouch comma-separated values file, 13 novel NeuroTouch metrics were developed and classified. Tier 1 metrics include blood loss, tumor percentage resected, and total simulated normal brain volume removed. Tier 2 metrics include total instrument tip path length, maximum force applied, sum of forces utilized, and average forces utilized by the simulated ultrasonic aspirator and suction instrument along with pedal activation frequency of the ultrasonic aspirator. Advanced tier 2 metrics include instrument tips average separation distance, efficiency index, ultrasonic aspirator path length index, coordination index, and ultrasonic aspirator bimanual forces ratio. This system of data extraction provides researchers expedited access for analyzing the data files available for NeuroTouch platform to assess the multiple psychomotor and cognitive neurosurgical skills involved in complex surgical procedures.

Assessment of learning curves on a simulated neurosurgical task using metrics selected by artificial intelligence.

OBJECTIVE: Understanding the variation of learning curves of experts and trainees for a given surgical procedure is important in implementing formative learning paradigms to accelerate mastery. The study objectives were to use artificial intelligence (AI)-derived metrics to determine the learning curves of participants in 4 groups with different expertise levels who performed a series of identical virtual reality (VR) subpial resection tasks and to identify learning curve differences among the 4 groups. METHODS: A total of 50 individuals participated, 14 neurosurgeons, 4 neurosurgical fellows and 10 senior residents (seniors), 10 junior residents (juniors), and 12 medical students. All participants performed 5 repetitions of a subpial tumor resection on the NeuroVR (CAE Healthcare) platform, and 6 a priori-derived metrics selected using the K-nearest neighbors machine learning algorithm were used to assess participant learning curves. Group learning curves were plotted over the 5 trials for each metric. A mixed, repeated-measures ANOVA was performed between the first and fifth trial. For significant interactions (p < 0.05), post hoc Tukey's HSD analysis was conducted to determine the location of the significance. RESULTS: Overall, 5 of the 6 metrics assessed had a significant interaction (p < 0.05). The 4 groups, neurosurgeons, seniors, juniors, and medical students, showed an improvement between the first and fifth trial on at least one of the 6 metrics evaluated. CONCLUSIONS: Learning curves generated using AI-derived metrics provided novel insights into technical skill acquisition, based on expertise level, during repeated VR-simulated subpial tumor resections, which will allow educators to develop more focused formative educational paradigms for neurosurgical trainees.

Development of a CT-Compatible, Anthropomorphic Skull and Brain Phantom for Neurosurgical Planning, Training, and Simulation.

BACKGROUND: Neurosurgical procedures are complex and require years of training and experience. Traditional training on human cadavers is expensive, requires facilities and planning, and raises ethical concerns. Therefore, the use of anthropomorphic phantoms could be an excellent substitute. The aim of the study was to design and develop a patient-specific 3D-skull and brain model with realistic CT-attenuation suitable for conventional and augmented reality (AR)-navigated neurosurgical simulations. METHODS: The radiodensity of materials considered for the skull and brain phantoms were investigated using cone beam CT (CBCT) and compared to the radiodensities of the human skull and brain. The mechanical properties of the materials considered were tested in the laboratory and subsequently evaluated by clinically active neurosurgeons. Optimization of the phantom for the intended purposes was performed in a feedback cycle of tests and improvements. RESULTS: The skull, including a complete representation of the nasal cavity and skull base, was 3D printed using polylactic acid with calcium carbonate. The brain was cast using a mixture of water and coolant, with 4 wt% polyvinyl alcohol and 0.1 wt% barium sulfate, in a mold obtained from segmentation of CBCT and T1 weighted MR images from a cadaver. The experiments revealed that the radiodensities of the skull and brain phantoms were 547 and 38 Hounsfield units (HU), as compared to real skull bone and brain tissues with values of around 1300 and 30 HU, respectively. As for the mechanical properties testing, the brain phantom exhibited a similar elasticity to real brain tissue. The phantom was subsequently evaluated by neurosurgeons in simulations of endonasal skull-base surgery, brain biopsies, and external ventricular drain (EVD) placement and found to fulfill the requirements of a surgical phantom. CONCLUSIONS: A realistic and CT-compatible anthropomorphic head phantom was designed and successfully used for simulated augmented reality-led neurosurgical procedures. The anatomic details of the skull base and brain were realistically reproduced. This phantom can easily be manufactured and used for surgical training at a low cost.

Crisis Management Simulation: Review of Current Experience.

Crisis management simulation is important in training the next generation of surgeons. In this review, we highlight our experiences with the cavernous carotid injury model. We then delve into other crisis simulation models available for the neurosurgical specialty. The discussion focuses upon how these trainings can continue to evolve. Much work is yet to be done in this exciting arena and we present several avenues for future discovery. Simulation continues to be an important training tool for the surgical learner.

Virtual Reality Anterior Cervical Discectomy and Fusion Simulation on the Novel Sim-Ortho Platform: Validation Studies.

BACKGROUND: Virtual reality spine simulators are emerging as potential educational tools to assess and train surgical procedures in safe environments. Analysis of validity is important in determining the educational utility of these systems. OBJECTIVE: To assess face, content, and construct validity of a C4-C5 anterior cervical discectomy and fusion simulation on the Sim-Ortho virtual reality platform, developed by OSSimTechTM (Montreal, Canada) and the AO Foundation (Davos, Switzerland). METHODS: Spine surgeons, spine fellows, along with neurosurgical and orthopedic residents, performed a simulated C4-C5 anterior cervical discectomy and fusion on the Sim-Ortho system. Participants were separated into 3 categories: post-residents (spine surgeons and spine fellows), senior residents, and junior residents. A Likert scale was used to assess face and content validity. Construct validity was evaluated by investigating differences between the 3 groups on metrics derived from simulator data. The Kruskal-Wallis test was employed to compare groups and a post-hoc Dunn's test with a Bonferroni correction was utilized to investigate differences between groups on significant metrics. RESULTS: A total of 21 individuals were included: 9 post-residents, 5 senior residents, and 7 junior residents. The post-resident group rated face and content validity, median ≥4, for the overall procedure and at least 1 tool in each of the 4 steps. Significant differences (P < .05) were found between the post-resident group and senior and/or junior residents on at least 1 metric for each component of the simulation. CONCLUSION: The C4-C5 anterior cervical discectomy and fusion simulation on the Sim-Ortho platform demonstrated face, content, and construct validity suggesting its utility as a formative educational tool.

Superficial Temporal Artery-Middle Cerebral Artery Bypass Ex Vivo Hybrid Simulator: Face, Content, Construct, and Concurrent Validity.

BACKGROUND: Cerebrovascular bypass surgical procedures require highly developed dexterity and refined bimanual technical skills. To attain such a level of prowess, neurosurgeons and residents have traditionally relied on "flat" models (without depth of field), such as chicken wings, live rats, silicone vessels, and other materials that stray far from the reality of the operating room, albeit more accessible. We have explored the use of a hybrid ex vivo simulator that takes advantage of the availability of placenta vessels and retains the complexity of surgery performed on a human skull to create a more realistic method for the development of cerebrovascular bypass surgical skills. METHODS: Twelve ex vivo simulators were constructed using 3 human placentas and 1 synthetic human skull for each. Face, content, construct, and concurrent validity were assessed by 12 neurosurgeons (6 trained vascular surgeons and 6 general neurosurgeons) and compared with those of other bypass models. RESULTS: The fidelity grade was ranked as low (Linkert scale score, 1-2), medium (score, 3), and high (score, 4-5). The face and content validity of the model showed high fidelity to superficial temporal artery-middle cerebral artery bypass surgery. Construct validity showed that cerebrovascular neurosurgeons had better performance, and concurrent validity highlighted that all surgical steps were present. CONCLUSION: The simulator was found to have strong face and content, construct, and concurrent validity for microsurgical cerebrovascular training, allowing for simulation of all surgical steps of the bypass procedure. The hybrid simulator seems to be a promising method for shortening the bypass surgery learning curve. However, more studies are required to evaluate the predictive validity of the model.

Quality Assurance During Brain Aneurysm Microsurgery-Operative Error Teaching.

INTRODUCTION: Quality assurance (QA) is a way to prevent mistakes in advance. Although it has been previously reported for surgical setup, there is no effective approach for minimizing microsurgical technical errors before an operation is done. Neurosurgery resident operative errors during brain aneurysm surgery could be foreseen by practicing in an ex vivo hybrid simulator with microscopic fluorescein vessel flow image. METHODS: Five vascular neurosurgeons and 8 junior/senior neurosurgical residents voluntarily joined this research initiative. The following methodology was adopted: 1) Identification of the 7 most-common resident operative performance errors during brain aneurysm surgery; 2) Design of exercises to prevent common mistakes in brain aneurysm microsurgery using a placenta simulator; and 3) Blinded staff neurosurgeon evaluation of resident performance during real brain aneurysm microsurgery. RESULTS: All key steps to perform such intervention were accomplished with a simulator that uses 2 placentas, a synthetic cranium, and microscopic fluorescein vessel flow image. Neurosurgery residents trained in this model had better surgical performance with fewer perioperative mistakes (P < 0.05). Fine microsurgical dissection of the arachnoid membrane and aneurysm sac were the most commonly improved tasks among the 7 common operative mistakes. Brain parenchyma traction with secondary bleeding was the only error not prevented after previous simulator training. CONCLUSIONS: There was a left-shift on the quality assurance line with residents who practiced brain aneurysm microsurgical errors in an ex vivo model. A multicentric prospective study is necessary to confirm the hypothesis that real operative error could be reduced after training in a realistic simulator.

A new model of soft tissue with constraints for interactive surgical simulation.

BACKGROUND AND OBJECTIVES: An accurate and real-time model of soft tissue is critical for surgical simulation for which a user interacts haptically and visually with simulated patients. This paper focuses on the real-time deformation model of brain tissue for the interactive surgical simulation, such as neurosurgical simulation. METHODS: A new Finite Element Method (FEM) based model with constraints is proposed for the brain tissue in neurosurgical simulation. A new energy function of constraints characterizing the interaction between the virtual instrument and the soft tissue is incorporated into the optimization problem derived from the implicit integration scheme. Distance and permanent deformation constraints are introduced to describe the interaction in the convexity meningioma dissection and hemostasis. The proposed model is particularly suitable for GPU-based computing, making it possible to achieve real-time performance. RESULTS AND CONCLUSIONS: Simulation results show that the simulated soft tissue exhibits the behaviors of adhesion and permanent deformation under the constraints. Experiments show that the proposed model is able to converge to the exact solution of the implicit Euler method after 96 iterations. The proposed model was implemented in the development of a neurosurgical simulator, in which surgical procedures such as dissection of convexity meningioma and hemostasis were simulated.

Biomechanical modeling and computer simulation of the brain during neurosurgery.

Computational biomechanics of the brain for neurosurgery is an emerging area of research recently gaining in importance and practical applications. This review paper presents the contributions of the Intelligent Systems for Medicine Laboratory and its collaborators to this field, discussing the modeling approaches adopted and the methods developed for obtaining the numerical solutions. We adopt a physics-based modeling approach and describe the brain deformation in mechanical terms (such as displacements, strains, and stresses), which can be computed using a biomechanical model, by solving a continuum mechanics problem. We present our modeling approaches related to geometry creation, boundary conditions, loading, and material properties. From the point of view of solution methods, we advocate the use of fully nonlinear modeling approaches, capable of capturing very large deformations and nonlinear material behavior. We discuss finite element and meshless domain discretization, the use of the total Lagrangian formulation of continuum mechanics, and explicit time integration for solving both time-accurate and steady-state problems. We present the methods developed for handling contacts and for warping 3D medical images using the results of our simulations. We present two examples to showcase these methods: brain shift estimation for image registration and brain deformation computation for neuronavigation in epilepsy treatment.

Development and validation of the Skills Assessment in Microsurgery for Brain Aneurysms (SAMBA) instrument for predicting proficiency in aneurysm surgery.

OBJECTIVE: Surgical performance evaluation was first described with the OSATS (Objective Structured Assessment of Technical Skills) and modified for aneurysm microsurgery simulation with the OSAACS (Objective Structured Assessment of Aneurysm Clipping Skills). These methods rely on the subjective opinions of evaluators, however, and there is a lack of objective evaluation for proficiency in the microsurgical treatment of brain aneurysms. The authors present a new instrument, the Skill Assessment in Microsurgery for Brain Aneurysms (SAMBA) scale, which can be used similarly in a simulation model and in the treatment of unruptured middle cerebral artery (MCA) aneurysms to predict surgical performance; the authors also report on its validation. METHODS: The SAMBA scale was created by consensus among 5 vascular neurosurgeons from 2 different neurosurgical departments. SAMBA results were analyzed using descriptive statistics, Cronbach's alpha indexes, and multivariate ANOVA analyses (p < 0.05). RESULTS: Expert, intermediate-level, and novice surgeons scored, respectively, an average of 33.9, 27.1, and 16.4 points in the real surgery and 33.3, 27.3, and 19.4 points in the simulation. The SAMBA interrater reliability index was 0.995 for the real surgery and 0.996 for the simulated surgery; the intrarater reliability was 0.983 (Cronbach's alpha). In both the simulation and the real surgery settings, the average scores achieved by members of each group (expert, intermediate level, and novice) were significantly different (p < 0.001). Scores among novice surgeons were more diverse (coefficient of variation = 12.4). CONCLUSIONS: Predictive validation of the placenta brain aneurysm model has been previously reported, but the SAMBA scale adds an objective scoring system to verify microsurgical ability in this complex operation, stratifying proficiency by points. The SAMBA scale can be used as an interface between learning and practicing, as it can be applied in a safe and controlled environment, such as is provided by a placenta model, with similar results obtained in real surgery, predicting real surgical performance.

Human Placenta Simulator for Intracranial-Intracranial Bypass: Vascular Anatomy and 5 Bypass Techniques.

BACKGROUND: Intracranial-intracranial (IC-IC) bypass surgery involves the use of significant technical bimanual skills. Indications for this procedure are limited, so training in a simulator with brain vessels similarity could maintain microsurgical dexterity. Our goal is to describe the human placenta vascular anatomy to guide IC-IC bypasses apprenticeship. METHODS: Human placenta vascular anatomy was reported and validated with comparison to brain main vessels after studying the vascular tree of 100 placentas. Five simulated IC-IC bypasses (end to end, end to lateral, lateral to lateral, aneurysm bridge, and aneurysm exiting branch transposition) were developed and construct and concurrent validated. Statistical analysis using the t variance test was performed with a confidence interval of 0.95. RESULTS: A total of 1200 placenta vessels were used for test-retest validation with a reliability index of 0.95. All 100 human placentas were suitable to perform the 5 different bypasses. Construct validity showed a P < 0.005. Concurrent validity highlighted the technical differences among simulators. CONCLUSIONS: An ex vivo bypass model offers great similarity to main brain vessels with the possibility to practice a variety of IC-IC bypass techniques in a single simulator. Placenta vascular anatomy knowledge can improve laboratory microsurgical training.

Learning brain aneurysm microsurgical skills in a human placenta model: predictive validity.

OBJECTIVE Surgery for brain aneurysms is technically demanding. In recent years, the process to learn the technical skills necessary for these challenging procedures has been affected by a decrease in the number of surgical cases available and progressive restrictions on resident training hours. To overcome these limitations, surgical simulators such as cadaver heads and human placenta models have been developed. However, the effectiveness of these models in improving technical skills is unknown. This study assessed concurrent and predictive validity of brain aneurysm surgery simulation in a human placenta model compared with a "live" human brain cadaveric model. METHODS Two human cadaver heads and 30 human placentas were used. Twelve neurosurgeons participated in the concurrent validity part of this study, each operating on 1 human cadaver head aneurysm model and 1 human placenta model. Simulators were evaluated regarding their ability to simulate different surgical steps encountered during real surgery. The time to complete the entire aneurysm task in each simulator was analyzed. The predictive validity component of the study involved 9 neurosurgical residents divided into 3 groups to perform simulation exercises, each lasting 6 weeks. The training for the 3 groups consisted of educational video only (3 residents), human cadaver only (3 residents), and human placenta only (3 residents). All residents had equivalent microsurgical experience with superficial brain tumor surgery. After completing their practice training, residents in each of the 3 simulation groups performed surgery for an unruptured middle cerebral artery (MCA) aneurysm, and their performance was assessed by an experienced vascular neurosurgeon who watched the operative videos. RESULTS All human cadaver heads and human placentas were suitable to simulate brain aneurysm surgery. In the concurrent validity portion of the experiment, the placenta model required a longer time (p < 0.001) than cadavers to complete the task. The placenta model was considered more effective than the cadaver model in simulating sylvian fissure splitting, bipolar coagulation of oozing microvessels, and aneurysm neck and dome dissection. Both models were equally effective in simulating neck aneurysm clipping, while the cadaver model was considered superior for simulation of intraoperative rupture and for reproduction of real anatomy during simulation. In the predictive validity portion of the experiment, residents were evaluated for 4 tasks: sylvian fissure dissection, microvessel bipolar coagulation, aneurysm dissection, and aneurysm clipping. Residents trained in the human placenta simulator consistently had the highest overall performance scores when compared with those who had trained in the cadaver model and those who had simply watched operative videos (p < 0.001). CONCLUSIONS The human placenta biological simulator provides excellent simulation for some critical tasks of aneurysm surgery such as splitting of the sylvian fissure, dissection of the aneurysm neck and dome, and bipolar coagulation of surrounding microvessels. When performing surgery for an unruptured MCA aneurysm, residents who had trained in the human placenta model performed better than residents trained with other simulation scenarios/models. In this age of reduced exposure to aneurysm surgery and restrictions on resident working hours, the placenta model is a valid simulation for microneurosurgery with striking similarities with real surgery.

The force pyramid: a spatial analysis of force application during virtual reality brain tumor resection.

OBJECTIVE Virtual reality simulators allow development of novel methods to analyze neurosurgical performance. The concept of a force pyramid is introduced as a Tier 3 metric with the ability to provide visual and spatial analysis of 3D force application by any instrument used during simulated tumor resection. This study was designed to answer 3 questions: 1) Do study groups have distinct force pyramids? 2) Do handedness and ergonomics influence force pyramid structure? 3) Are force pyramids dependent on the visual and haptic characteristics of simulated tumors? METHODS Using a virtual reality simulator, NeuroVR (formerly NeuroTouch), ultrasonic aspirator force application was continually assessed during resection of simulated brain tumors by neurosurgeons, residents, and medical students. The participants performed simulated resections of 18 simulated brain tumors with different visual and haptic characteristics. The raw data, namely, coordinates of the instrument tip as well as contact force values, were collected by the simulator. To provide a visual and qualitative spatial analysis of forces, the authors created a graph, called a force pyramid, representing force sum along the z-coordinate for different xy coordinates of the tool tip. RESULTS Sixteen neurosurgeons, 15 residents, and 84 medical students participated in the study. Neurosurgeon, resident and medical student groups displayed easily distinguishable 3D "force pyramid fingerprints." Neurosurgeons had the lowest force pyramids, indicating application of the lowest forces, followed by resident and medical student groups. Handedness, ergonomics, and visual and haptic tumor characteristics resulted in distinct well-defined 3D force pyramid patterns. CONCLUSIONS Force pyramid fingerprints provide 3D spatial assessment displays of instrument force application during simulated tumor resection. Neurosurgeon force utilization and ergonomic data form a basis for understanding and modulating resident force application and improving patient safety during tumor resection.

The relative efficacy of 3 different freehand frontal ventriculostomy trajectories: a prospective neuronavigation-assisted simulation study.

OBJECTIVE Ventriculostomy is a relatively common neurosurgical procedure, often performed in the setting of acute hydrocephalus. Accurate positioning of the catheter is vital to minimize morbidity and mortality, and several anatomical landmarks are currently used. The aim of this study was to prospectively evaluate the relative performance of 3 recognized trajectories for frontal ventriculostomy using imaging-derived metrics: perpendicular to skull (PTS), contralateral medial canthus/external auditory meatus (CMC/EAM), and ipsilateral medial canthus/external auditory meatus (IMC/EAM). METHODS Participants completed 9 simulated ventriculostomy attempts (3 of each trajectory) on a model head with Medtronic StealthStation coregistered imaging. Performance measures were distance of the ventricular catheter tip to the foramen of Monro (FoM) and presence of the catheter tip in a lateral ventricle. RESULTS Thirty-one individuals of varying seniority and prior ventriculostomy experience performed a total of 279 simulated freehand frontal ventriculostomies. The PTS and CMC/EAM trajectories were found to be significantly more likely to result in both the catheter tip being closer to the FoM and in a lateral ventricle compared with the IMC/EAM trajectory. These findings were not influenced by the prior ventriculostomy experience of the participant, corroborating the significance of these results. CONCLUSIONS The PTS and CMC/EAM trajectories were superior to the IMC/EAM trajectories during freehand frontal ventriculostomy in this study, and further data from studies incorporating varying ventricular sizes and bur hole locations are required to facilitate a change in clinical practice. In addition, neuronavigation and other guidance techniques for ventriculostomy are becoming increasingly popular and may be superior to freehand techniques, necessitating further prospective data evaluating their safety, efficacy, and feasibility for routine clinical use.

Coconut Model for Learning First Steps of Craniotomy Techniques and Cerebrospinal Fluid Leak Avoidance.

INTRODUCTION: Neurosurgery simulation has gained attention recently due to changes in the medical system. First-year neurosurgical residents in low-income countries usually perform their first craniotomy on a real subject. Development of high-fidelity, cheap, and largely available simulators is a challenge in residency training. An original model for the first steps of craniotomy with cerebrospinal fluid leak avoidance practice using a coconut is described. MATERIAL AND METHODS: The coconut is a drupe from Cocos nucifera L. (coconut tree). The green coconut has 4 layers, and some similarity can be seen between these layers and the human skull. The materials used in the simulation are the same as those used in the operating room. PROCEDURE: The coconut is placed on the head holder support with the face up. The burr holes are made until endocarp is reached. The mesocarp is dissected, and the conductor is passed from one hole to the other with the Gigli saw. The hook handle for the wire saw is positioned, and the mesocarp and endocarp are cut. After sawing the 4 margins, mesocarp is detached from endocarp. Four burr holes are made from endocarp to endosperm. Careful dissection of the endosperm is done, avoiding liquid albumen leak. The Gigli saw is passed through the trephine holes. Hooks are placed, and the endocarp is cut. After cutting the 4 margins, it is dissected from the endosperm and removed. The main goal of the procedure is to remove the endocarp without fluid leakage. DISCUSSION: The coconut model for learning the first steps of craniotomy and cerebrospinal fluid leak avoidance has some limitations. It is more realistic while trying to remove the endocarp without damage to the endosperm. It is also cheap and can be widely used in low-income countries. However, the coconut does not have anatomic landmarks. The mesocarp makes the model less realistic because it has fibers that make the procedure more difficult and different from a real craniotomy. CONCLUSION: The model has a potential pedagogic neurosurgical application for freshman residents before they perform a real craniotomy for the first time. Further validity is necessary to confirm this hypothesis.

Simulated ventriculostomy training with conventional neuronavigational equipment used clinically in the operating room: prospective validation study.

OBJECTIVES: Simulation is gaining increasing interest as a method of delivering high-quality, time-effective, and safe training to neurosurgical residents. However, most current simulators are purpose-built for simulation, being relatively expensive and inaccessible to many residents. The purpose of this study was to provide the first comprehensive validity assessment of ventriculostomy performance metrics from the Medtronic StealthStation S7 Surgical Navigation System, a neuronavigational tool widely used in the clinical setting, as a training tool for simulated ventriculostomy while concomitantly reporting on stress measures. DESIGN: A prospective study where participants performed 6 simulated ventriculostomy attempts on a model head with StealthStation-coregistered imaging. The performance measures included distance of the ventricular catheter tip to the foramen of Monro and presence of the catheter tip in the ventricle. Data on objective and self-reported stress and workload measures were also collected. SETTING: The operating rooms of the National Hospital for Neurology and Neurosurgery, Queen Square, London. PARTICIPANTS: A total of 31 individuals with varying levels of prior ventriculostomy experience, varying in seniority from medical student to senior resident. RESULTS: Performance at simulated ventriculostomy improved significantly over subsequent attempts, irrespective of previous ventriculostomy experience. Performance improved whether or not the StealthStation display monitor was used for real-time visual feedback, but performance was optimal when it was. Further, performance was inversely correlated with both objective and self-reported measures of stress (traditionally referred to as concurrent validity). Stress and workload measures were well-correlated with each other, and they also correlated with technical performance. CONCLUSIONS: These initial data support the use of the StealthStation as a training tool for simulated ventriculostomy, providing a safe environment for repeated practice with immediate feedback. Although the potential implications are profound for neurosurgical education and training, further research following this proof-of-concept study is required on a larger scale for full validation and proof that training translates into improved long-term simulated and patient outcomes.

Proficiency performance benchmarks for removal of simulated brain tumors using a virtual reality simulator NeuroTouch.

OBJECTIVE: Assessment of neurosurgical technical skills involved in the resection of cerebral tumors in operative environments is complex. Educators emphasize the need to develop and use objective and meaningful assessment tools that are reliable and valid for assessing trainees' progress in acquiring surgical skills. The purpose of this study was to develop proficiency performance benchmarks for a newly proposed set of objective measures (metrics) of neurosurgical technical skills performance during simulated brain tumor resection using a new virtual reality simulator (NeuroTouch). DESIGN: Each participant performed the resection of 18 simulated brain tumors of different complexity using the NeuroTouch platform. Surgical performance was computed using Tier 1 and Tier 2 metrics derived from NeuroTouch simulator data consisting of (1) safety metrics, including (a) volume of surrounding simulated normal brain tissue removed, (b) sum of forces utilized, and (c) maximum force applied during tumor resection; (2) quality of operation metric, which involved the percentage of tumor removed; and (3) efficiency metrics, including (a) instrument total tip path lengths and (b) frequency of pedal activation. SETTING: All studies were conducted in the Neurosurgical Simulation Research Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada. PARTICIPANTS: A total of 33 participants were recruited, including 17 experts (board-certified neurosurgeons) and 16 novices (7 senior and 9 junior neurosurgery residents). RESULTS: The results demonstrated that "expert" neurosurgeons resected less surrounding simulated normal brain tissue and less tumor tissue than residents. These data are consistent with the concept that "experts" focused more on safety of the surgical procedure compared with novices. By analyzing experts' neurosurgical technical skills performance on these different metrics, we were able to establish benchmarks for goal proficiency performance training of neurosurgery residents. CONCLUSION: This study furthers our understanding of expert neurosurgical performance during the resection of simulated virtual reality tumors and provides neurosurgical trainees with predefined proficiency performance benchmarks designed to maximize the learning of specific surgical technical skills.