Bimanual Psychomotor Performance in Neurosurgical Resident Applicants Assessed Using NeuroTouch, a Virtual Reality Simulator

Assessment of High-fidelity Anatomical Models for Performing Pterional Approach: A Practical Clinic in American Association of Neurological Surgeons Meeting 2024

BACKGROUND

Over the last decade, simulation models have been increasingly applied as an adjunct for surgical training in neurosurgery. We aim through a practical course at a national neurosurgical conference to evaluate 3D non-cadaveric simulation models along with augmented reality for learning and practicing the pterional craniotomy approach among a wide variety of participants including medical students, neurosurgery residents, and attending neurosurgeons.

METHODS

Our course was conducted during an international neurosurgery meeting with 93 participants but the course surveys (pre- and post-course) were completed by 42 participants.

RESULTS

Most participants were medical students (31; 73.8%). Participants with no experience (the majority) in cadaver lab dissections, craniotomy as first operator, and as second operator represented 12 (27.9%), 29 (69%), and 22 (52.4%), respectively. Participants with moderate experience in cadaver lab dissections were 23 (53.5%). Post-course survey respondents noted positive feedback in most items queried including enhancement of familiarity and acquiring skills, confidence with neurosurgery instruments, confidence with microscope, part of standard training, traditional training, and lifelong training.

CONCLUSIONS

Simulation model combining augmented reality with physical simulation for hybrid experience can be a promising and valuable tool especially for medical students or early career neurosurgical residents.

Virtual, Augmented, and Mixed Reality Applications for Surgical Rehearsal, Operative Execution, and Patient Education in Spine Surgery: A Scoping Review

Background and Objectives: Advances in virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies have resulted in their increased application across many medical specialties. VR's main application has been for teaching and preparatory roles, while AR has been mostly used as a surgical adjunct. The objective of this study is to discuss the various applications and prospects for VR, AR, and MR specifically as they relate to spine surgery. Materials and Methods: A systematic review was conducted to examine the current applications of VR, AR, and MR with a focus on spine surgery. A literature search of two electronic databases (PubMed and Scopus) was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The study quality was assessed using the MERSQI score for educational research studies, QUACS for cadaveric studies, and the JBI critical appraisal tools for clinical studies. Results: A total of 228 articles were identified in the primary literature review. Following title/abstract screening and full-text review, 46 articles were included in the review. These articles comprised nine studies performed in artificial models, nine cadaveric studies, four clinical case studies, nineteen clinical case series, one clinical case-control study, and four clinical parallel control studies. Teaching applications utilizing holographic overlays are the most intensively studied aspect of AR/VR; the most simulated surgical procedure is pedicle screw placement. Conclusions: VR provides a reproducible and robust medium for surgical training through surgical simulations and for patient education through various platforms. Existing AR/MR platforms enhance the accuracy and precision of spine surgeries and show promise as a surgical adjunct.

Neurosurgical Education Using Cadaver-Free Brain Models and Augmented Reality: First Experiences from a Hands-On Simulation Course for Medical Students

Background and Objectives: Neurosurgery has been underrepresented in the medical school curriculum. Advances in augmented reality and 3D printing have opened the way for early practical training through simulations. We assessed the usability of the UpSurgeOn simulation-based training model and report first experiences from a hands-on neurosurgery course for medical students. Materials and Methods: We organized a two-day microneurosurgery simulation course tailored to medical students. On day one, three neurosurgeons demonstrated anatomical explorations with the help of life-like physical simulators (BrainBox, UpSurgeOn). The surgical field was projected onto large high-definition screens by a robotic-assisted exoscope (RoboticScope, BHS Technologies). On day two, the students were equipped with microsurgical instruments to explore the surgical anatomy of the pterional, temporal and endoscopic retrosigmoid approaches. With the help of the RoboticScope, they simulated five clipping procedures using the Aneurysm BrainBox. All medical students filled out a digital Likert-scale-based questionnaire to evaluate their experiences. Results: Sixteen medical students participated in the course. No medical students had previous experience with UpSurgeOn. All participants agreed that the app helped develop anatomical orientation. They unanimously agreed that this model should be part of residency training. Fourteen out of sixteen students felt that the course solidified their decision to pursue neurosurgery. The same fourteen students rated their learning experience as totally positive, and the remaining two rated it as rather positive. Conclusions: The UpSurgeOn educational app and cadaver-free models were perceived as usable and effective tools for the hands-on neuroanatomy and neurosurgery teaching of medical students. Comparative studies may help measure the long-term benefits of UpSurgeOn-assisted teaching over conventional resources.

Performance in a Simulated Virtual Reality Anterior Cervical Discectomy and Fusion Task: Disc Residual, Rate of Removal, and Efficiency Analyses

BACKGROUND AND OBJECTIVES

Anterior cervical discectomy and fusion (ACDF) is among the most common spine procedures. The Sim-Ortho virtual reality simulator platform contains a validated ACDF simulated task for performance assessment. This study aims to develop a methodology to extract three-dimensional data and reconstruct and quantitate specific simulated disc tissues to generate novel metrics to analyze performance metrics of skilled and less skilled participants.

METHODS

We used open-source platforms to develop a methodology to extract three-dimensional information from ACDF simulation data. Metrics generated included, efficiency index, disc volumes removed from defined regions, and rate of tissue removal from superficial, central, and deep disc regions. A pilot study was performed to assess the utility of this methodology to assess expertise during the ACDF simulated procedure.

RESULTS

The system outlined, extracts data allowing the development of a methodology which accurately reconstructs and quantitates 3-dimensional disc volumes. In the pilot study, data sets from 27 participants, divided into postresident, resident, and medical student groups, allowed assessment of multiple novel metrics, including efficiency index (surgical time spent in actively removing disc), where the postresident group spent 61.8% of their time compared with 53% and 30.2% for the resident and medical student groups, respectively ( P = .01). During the annulotomy component, the postresident group removed 47.4% more disc than the resident groups and 102% more than the medical student groups ( P = .03).

CONCLUSION

The methodology developed in this study generates novel surgical procedural metrics from 3-dimensional data generated by virtual reality simulators and can be used to assess surgical performance.

Objects May Be Farther Than They Appear: Depth Compression Diminishes Over Time with Repeated Calibration in Virtual Reality

Prior research in depth perception and perceptuo-motor calibration have primarily focused on participants completing experiments in single sessions and therefore do not empirically evaluate changes over time. Further, these studies do not typically take into account the amount of experience that the participants have in virtual reality (VR) prior to participation, the role of experience during participation, or calibration that may occur throughout the experiment session. In this contribution, we conducted a novel empirical evaluation of how calibration affects perception-action coordination over time. We recruited novice VR users and they completed eight sessions of a depth perception reaching experiment over the course of 12 weeks. During these experiments, we examined how participants' ability to estimate depth in a virtual environment changed as they gradually gained experience. While previous literature has shown that participants tend to underestimate distances, we found that this underestimation diminished over time as they gained experience in the virtual environment. Our study highlights the need for carrying out VR studies over time and the influence that longitudinal calibration can have on spatial perception in long-term VR experiences.

Extended Reality in Neurosurgical Education: A Systematic Review

Surgical simulation practices have witnessed a rapid expansion as an invaluable approach to resident training in recent years. One emerging way of implementing simulation is the adoption of extended reality (XR) technologies, which enable trainees to hone their skills by allowing interaction with virtual 3D objects placed in either real-world imagery or virtual environments. The goal of the present systematic review is to survey and broach the topic of XR in neurosurgery, with a focus on education. Five databases were investigated, leading to the inclusion of 31 studies after a thorough reviewing process. Focusing on user performance (UP) and user experience (UX), the body of evidence provided by these 31 studies showed that this technology has, in fact, the potential of enhancing neurosurgical education through the use of a wide array of both objective and subjective metrics. Recent research on the topic has so far produced solid results, particularly showing improvements in young residents, compared to other groups and over time. In conclusion, this review not only aids to a better understanding of the use of XR in neurosurgical education, but also highlights the areas where further research is entailed while also providing valuable insight into future applications.

Interval assessment using task- and procedure-based simulations: an attempt to supplement neurosurgical residency curriculum

OBJECTIVE

The longer learning curve and smaller margin of error make nontraditional, or "out of operating room" simulation training, essential in neurosurgery. In this study, the authors propose an evaluation system for residents combining both task-based and procedure-based exercises and also present the perception of residents regarding its utility.

METHODS

Residents were evaluated using a combination of task-based and virtual reality (VR)–based exercises. The results were analyzed in terms of the seniority of the residents as well as their laboratory credits. Questionnaire-based feedback was sought from the residents regarding the utility of this evaluation system incorporating the VR-based exercises.

RESULTS

A total of 35 residents were included in this study and were divided into 3 groups according to seniority. There were 11 residents in groups 1 and 3 and 13 residents in group 2. On the overall assessment of microsuturing skills including both 4-0 and 10-0 microsuturing, the suturing skills of groups 2 and 3 were observed to be better than those of group 1 (p = 0.0014). Additionally, it was found that microsuturing scores improved significantly with the increasing laboratory credits (R2 = 0.72, p < 0.001), and this was found to be the most significant for group 1 residents (R2 = 0.85, p < 0.001). Group 3 residents performed significantly better than the other two groups in both straight (p = 0.02) and diagonal (p = 0.042) ring transfer tasks, but there was no significant difference between group 1 and group 2 residents (p = 0.35). Endoscopic evaluation points were also found to be positively correlated with previous laboratory training (p = 0.002); however, for the individual seniority groups, the correlation failed to reach statistical significance. The 3 seniority groups performed similarly in the cranial and spinal VR modules. Group 3 residents showed significant disagreement with the utility of the VR platform for improving surgical dexterity (p = 0.027) and improving the understanding of surgical procedures (p = 0.034). Similarly, there was greater disagreement for VR-based evaluation to identify target areas of improvement among the senior residents (groups 2 and 3), but it did not reach statistical significance (p = 0.194).

CONCLUSIONS

The combination of task- and procedure-based assessment of trainees using physical and VR simulation models can supplement the existing neurosurgery curriculum. The currently available VR-based simulations are useful in the early years of training, but they need significant improvement to offer beneficial learning opportunities to senior trainees.

Virtual-Augmented Reality and Life-Like Neurosurgical Simulator for Training: First Evaluation of a Hands-On Experience for Residents

Background

In the recent years, growing interest in simulation-based surgical education has led to various practical alternatives for medical training. More recently, courses based on virtual reality (VR) and three-dimensional (3D)-printed models are available. In this paper, a hybrid (virtual and physical) neurosurgical simulator has been validated, equipped with augmented reality (AR) capabilities that can be used repeatedly to increase familiarity and improve the technical skills in human brain anatomy and neurosurgical approaches.

Methods

The neurosurgical simulator used in this study (UpSurgeOn Box, UpSurgeOn Srl, Assago, Milan) combines a virtual component and a physical component with an intermediate step to provide a hybrid solution. A first reported and evaluated practical experience on the anatomical 3D-printed model has been conducted with a total of 30 residents in neurosurgery. The residents had the possibility to choose a specific approach, focus on the correct patient positioning, and go over the chosen approach step-by-step, interacting with the model through AR application. Next, each practical surgical step on the 3D model was timed and qualitatively evaluated by 3 senior neurosurgeons. Quality and usability-grade surveys were filled out by participants.

Results

More than 89% of the residents assessed that the application and the AR simulator were very helpful in improving the orientation skills during neurosurgical approaches. Indeed, 89.3% of participants found brain and skull anatomy highly realistic during their tasks. Moreover, workshop exercises were considered useful in increasing the competency and technical skills required in the operating room by 85.8 and 84.7% of residents, respectively. Data collected confirmed that the anatomical model and its application were intuitive, well-integrated, and easy to use.

Conclusion

The hybrid AR and 3D-printed neurosurgical simulator could be a valid tool for neurosurgical training, capable of enhancing personal technical skills and competence. In addition, it could be easy to imagine how patient safety would increase and healthcare costs would be reduced, even if more studies are needed to investigate these aspects. The integration of simulators for training in neurosurgery as preparatory steps for the operating room should be recommended and further investigated given their huge potential.

Continuous monitoring of surgical bimanual expertise using deep neural networks in virtual reality simulation

In procedural-based medicine, the technical ability can be a critical determinant of patient outcomes. Psychomotor performance occurs in real-time, hence a continuous assessment is necessary to provide action-oriented feedback and error avoidance guidance. We outline a deep learning application, the Intelligent Continuous Expertise Monitoring System (ICEMS), to assess surgical bimanual performance at 0.2-s intervals. A long-short term memory network was built using neurosurgeon and student performance in 156 virtually simulated tumor resection tasks. Algorithm predictive ability was tested separately on 144 procedures by scoring the performance of neurosurgical trainees who are at different training stages. The ICEMS successfully differentiated between neurosurgeons, senior trainees, junior trainees, and students. Trainee average performance score correlated with the year of training in neurosurgery. Furthermore, coaching and risk assessment for critical metrics were demonstrated. This work presents a comprehensive technical skill monitoring system with predictive validation throughout surgical residency training, with the ability to detect errors.

The Orthopaedic Resident Selection Process: Proposed Reforms and Lessons From Other Specialties

INTRODUCTION

Proposals for substantive reforms to the orthopaedic resident selection process are growing, given increasing applicant competitiveness, burgeoning inefficiencies and inequities of the current system, and impending transition of Step 1 to pass/fail. The COVID-19 pandemic has further catalyzed the need for reforms, offering unprecedented opportunities to pilot novel changes. However, a comprehensive collation of all proposed and implemented orthopaedic reforms is currently lacking. Thus, we aimed to characterize proposed orthopaedic-specific resident selection reforms in the context of reforms implemented by other specialties.

METHODS

EMBASE, MEDLINE, Scopus, and Web of Science databases were searched for references proposing reforms to the orthopaedic resident selection process published from 2005 to 2020. An inductive approach to qualitative content analysis was used to categorize reforms.

RESULTS

Twenty-six articles proposing 13 unique reforms to the orthopaedic resident selection process were identified. The most commonly proposed reforms included noncognitive assessments (n = 8), application caps (n = 7), standardized letters of recommendation (n = 5), program-specific supplemental applications (n = 5), creation of a centralized database of standardized program information (n = 4), use of a standardized applicant composite score (n = 4), and a moratorium on postinterview communication (n = 4). Importantly, nearly all of these reforms have also been proposed or implemented by other specialties.

DISCUSSION

Numerous reforms to the orthopaedic resident selection process have been suggested over the past 15 years, several of which have been implemented on a program-specific basis, including noncognitive assessments, supplemental applications, and standardized letters of recommendation. Careful examination of applicant and program experiences and Match outcomes after these reforms is imperative to inform future directions.

Volumetric comparative analysis of anatomy through far-lateral approach: surgical space and exposed tissues

Background

The three-dimensional (3D) visualization model has ability to quantify the surgical anatomy of far-lateral approach. This study was designed to disclose the relationship between surgical space and exposed tissues in the far-lateral approach by the volumetric analysis of 3D model.

Methods

The 3D skull base models were constructed using MRI and CT data of 15 patients (30 sides) with trigeminal neuralgia. Surgical corridors of the far-lateral approach were simulated by triangular pyramids to represent two surgical spaces exposing bony and neurovascular tissues. Volumetric comparison of surgical anatomy was performed using pair t test.

Results

The morphometric results were almost the same in the two surgical spaces except the vagus nerve (CN X) exposed only in one corridor, whereas the volumetric comparison represented the statistical significant differences of surgical space and bony and neurovascular tissues involved in the two corridors (P<0.001). The differences of bony and neurovascular tissues failed to equal the difference of surgical space.

Conclusions

For far-lateral approach, the increase of exposure for the bony and neurovascular tissues is not necessarily matched with the increase of surgical space. The volumetric comparative analysis is helpful to provide more detailed anatomical information in the surgical design.

Utilizing a multilayer perceptron artificial neural network to assess a virtual reality surgical procedure

BACKGROUND

Virtual reality surgical simulators are a safe and efficient technology for the assessment and training of surgical skills. Simulators allow trainees to improve specific surgical techniques in risk-free environments. Recently, machine learning has been coupled to simulators to classify performance. However, most studies fail to extract meaningful observations behind the classifications and the impact of specific surgical metrics on the performance. One benefit from integrating machine learning algorithms, such as Artificial Neural Networks, to simulators is the ability to extract novel insights into the composites of the surgical performance that differentiate levels of expertise.

OBJECTIVE

This study aims to demonstrate the benefits of artificial neural network algorithms in assessing and analyzing virtual surgical performances. This study applies the algorithm on a virtual reality simulated annulus incision task during an anterior cervical discectomy and fusion scenario.

DESIGN

An artificial neural network algorithm was developed and integrated. Participants performed the simulated surgical procedure on the Sim-Ortho simulator. Data extracted from the annulus incision task were extracted to generate 157 surgical performance metrics that spanned three categories (motion, safety, and efficiency).

SETTING

Musculoskeletal Biomechanics Research Lab; Neurosurgical Simulation and Artificial Intelligence Learning Center, McGill University, Montreal, Canada.

PARTICIPANTS

Twenty-three participants were recruited and divided into 3 groups: 11 post-residents, 5 senior and 7 junior residents.

RESULTS

An artificial neural network model was trained on nine selected surgical metrics, spanning all three categories and achieved 80% testing accuracy.

CONCLUSIONS

This study outlines the benefits of integrating artificial neural networks to virtual reality surgical simulators in understanding composites of expertise performance.

A systematic review of virtual reality for the assessment of technical skills in neurosurgery

OBJECTIVE

Virtual reality (VR) and augmented reality (AR) systems are increasingly available to neurosurgeons. These systems may provide opportunities for technical rehearsal and assessments of surgeon performance. The assessment of neurosurgeon skill in VR and AR environments and the validity of VR and AR feedback has not been systematically reviewed.

METHODS

A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted through MEDLINE and PubMed. Studies published in English between January 1990 and February 2021 describing the use of VR or AR to quantify surgical technical performance of neurosurgeons without the use of human raters were included. The types and categories of automated performance metrics (APMs) from each of these studies were recorded.

RESULTS

Thirty-three VR studies were included in the review; no AR studies met inclusion criteria. VR APMs were categorized as either distance to target, force, kinematics, time, blood loss, or volume of resection. Distance and time were the most well-studied APM domains, although all domains were effective at differentiating surgeon experience levels. Distance was successfully used to track improvements with practice. Examining volume of resection demonstrated that attending surgeons removed less simulated tumor but preserved more normal tissue than trainees. More recently, APMs have been used in machine learning algorithms to predict level of training with a high degree of accuracy. Key limitations to enhanced-reality systems include limited AR usage for automated surgical assessment and lack of external and longitudinal validation of VR systems.

CONCLUSIONS

VR has been used to assess surgeon performance across a wide spectrum of domains. The VR environment can be used to quantify surgeon performance, assess surgeon proficiency, and track training progression. AR systems have not yet been used to provide metrics for surgeon performance assessment despite potential for intraoperative integration. VR-based APMs may be especially useful for metrics that are difficult to assess intraoperatively, including blood loss and extent of resection.

Quantitation of Tissue Resection Using a Brain Tumor Model and 7-T Magnetic Resonance Imaging Technology

BACKGROUND

Animal brain tumor models can be useful educational tools for the training of neurosurgical residents in risk-free environments. Magnetic resonance imaging (MRI) technologies have not used these models to quantitate tumor, normal gray and white matter, and total tissue removal during complex neurosurgical procedures. This pilot study was carried out as a proof of concept to show the feasibility of using brain tumor models combined with 7-T MRI technology to quantitatively assess tissue removal during subpial tumor resection.

METHODS

Seven ex vivo calf brain hemispheres were used to develop the 7-T MRI segmentation methodology. Three brains were used to quantitate brain tissue removal using 7-T MRI segmentation methodology. Alginate artificial brain tumor was created in 4 calf brains to assess the ability of 7-T MRI segmentation methodology to quantitate tumor and gray and white matter along with total tissue volumes removal during a subpial tumor resection procedure.

RESULTS

Quantitative studies showed a correlation between removed brain tissue weights and volumes determined from segmented 7-T MRIs. Analysis of baseline and postresection alginate brain tumor segmented 7-T MRIs allowed quantification of tumor and gray and white matter along with total tissue volumes removed and detection of alterations in surrounding gray and white matter.

CONCLUSIONS

This pilot study showed that the use of animal tumor models in combination with 7-T MRI technology provides an opportunity to increase the granularity of data obtained from operative procedures and to improve the assessment and training of learners.

Resident Selection in the Wake of United States Medical Licensing Examination Step 1 Transition to Pass/Fail Scoring

INTRODUCTION

The numeric score for the United States Medical Licensing Examination Step 1 is one of the only universal, objective, scaled criteria for comparing the many students who apply to orthopaedic surgery residency. However, on February 12, 2020, it was announced that Step 1 would be transitioning to pass/fail scoring. The purpose of this study was to (1) determine the most important factors used for interview and resident selection after this change and (2) to assess how these factors have changed compared with a previous report on resident selection.

METHODS

A survey was distributed to the program directors (PDs) of all 179 orthopaedic surgery programs accredited by the Accreditation Council for Graduate Medical Education. Questions focused on current resident selection practices and the impact of the Step 1 score transition on expected future practices.

RESULTS

A total of 78 PDs (44%) responded to the survey. Over half of PDs (59%) responded that United States Medical Licensing Examination Step 2 clinical knowledge (CK) score is the factor that will increase most in importance after Step 1 transitions to pass/fail, and 90% will encourage applicants to include their Step 2 CK score on their applications. The factors rated most important in resident selection from zero to 10 were subinternship performance (9.05), various aspects of interview performance (7.49 to 9.01), rank in medical school (7.95), letters of recommendation (7.90), and Step 2 CK score (7.27). Compared with a 2002 report, performance on manual skills testing, subinternship performance, published research, letters of recommendations, and telephone call on applicants' behalf showed notable increases in importance.

DISCUSSION

As Step 2 CK is expected to become more important in the residency application process, current applicant stress on Step 1 scores may simply move to Step 2 CK scores. Performance on subinternships will remain a critical aspect of residency application, as it was viewed as the most important resident selection factor and has grown in importance compared with a previous report.

Tremor Assessment during Virtual Reality Brain Tumor Resection

OBJECTIVE

Assessment of physiological tremor during neurosurgical procedures may provide further insights into the composites of surgical expertise. Virtual reality platforms may provide a mechanism for the quantitative assessment of physiological tremor. In this study, a virtual reality simulator providing haptic feedback was used to study physiological tremor in a simulated tumor resection task with participants from a "skilled" group and a "novice" group.

DESIGN

The task involved using a virtual ultrasonic aspirator to remove a series of virtual brain tumors with different visual and tactile characteristics without causing injury to surrounding tissue. Power spectral density analysis was employed to quantitate hand tremor during tumor resection. Statistical t test was used to determine tremor differences between the skilled and novice groups obtained from the instrument tip x, y, z coordinates, the instrument roll, pitch, yaw angles, and the instrument haptic force applied during tumor resection.

SETTING

The study was conducted at the Neurosurgical Simulation and Artificial Intelligence Learning Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.

PARTICIPANTS

The skilled group comprised 23 neurosurgeons and senior residents and the novice group comprised 92 junior residents and medical students.

RESULTS

The spectral analysis allowed quantitation of physiological tremor during virtual reality tumor resection. The skilled group displayed smaller physiological tremor than the novice group in all cases. In 3 out of 7 cases the difference was statistically significant.

CONCLUSIONS

The first investigation of the application of a virtual reality platform is presented for the quantitation of physiological tremor during a virtual reality tumor resection task. The goal of introducing such methodology to assess tremor is to highlight its potential educational application in neurosurgical resident training and in helping to further define the psychomotor skill set of surgeons.

Roadmap for Developing Complex Virtual Reality Simulation Scenarios: Subpial Neurosurgical Tumor Resection Model

BACKGROUND

Advancement and evolution of current virtual reality (VR) surgical simulation technologies are integral to improve the available armamentarium of surgical skill education. This is especially important in high-risk surgical specialties. Such fields including neurosurgery are beginning to explore the utilization of virtual reality simulation in the assessment and training of psychomotor skills. An important issue facing the available VR simulation technologies is the lack of complexity of scenarios that fail to replicate the visual and haptic realities of complex neurosurgical procedures. Therefore there is a need to create more realistic and complex scenarios with the appropriate visual and haptic realities to maximize the potential of virtual reality technology.

METHODS

We outline a roadmap for creating complex virtual reality neurosurgical simulation scenarios using a step-wise description of our team's subpial tumor resection project as a model.

RESULTS

The creation of complex neurosurgical simulations involves integrating multiple modules into a scenario-building roadmap. The components of each module are described outlining the important stages in the process of complex VR simulation creation.

CONCLUSIONS

Our roadmap of a stepwise approach for the creation of complex VR-simulated neurosurgical procedures may also serve as a guide to aid the development of other VR scenarios in a variety of surgical fields. The generation of new VR complex simulated neurosurgical procedures, by surgeons for surgeons, with the help of computer scientists and engineers may improve the assessment and training of residents and ultimately improve patient care.

EANS Basic Brain Course (ABC): combining simulation to cadaver lab for a new concept of neurosurgical training

BACKGROUND

Neurosurgical training has traditionally been based on an apprenticeship model that requires considerable time and exposure to surgeries. Unfortunately, nowadays these requirements are hampered by several limitations (e.g., decreased caseload, worktime restrictions). Furthermore, teaching methods vary among residency programs due to cultural differences, monetary restrictions, and infrastructure conditions, with the possible consequence of jeopardizing residents' training.

METHODS

The EANS Basic Brain Course originated from a collaboration between the Besta NeuroSim Center in Milano and the Swiss Foundation for Innovation and Training in Surgery in Geneva. It was held for 5 neurosurgical residents (PGY1-3) who participated to this first pilot experience in January 2019. The main goal was to cover the very basic aspects of cranial surgery, including both technical and non-technical skills. The course was developed in modules, starting from the diagnostic paths and communication with patients (played by professional actors), then moving to practical simulation sessions, rapid theoretical lessons, and discussions based on real cases and critical ethical aspects. At the end, the candidates had cadaver lab sessions in which they practiced basic emergency procedures and craniotomies. The interaction between the participants and the faculties was created and maintained using role plays that smoothly improved the cooperation during debriefs and discussions, thus making the sessions exceedingly involving.

RESULTS

At the end of the course, every trainee was able to complete the course curriculum and all the participants expressed their appreciation for this innovative format, with a particular emphasis on the time spent learning non-technical skills, confirming that they feel this to be a fundamental aspect of a comprehensive training in neurosurgery.

CONCLUSIONS

It is possible that this combined concept of training on technical and non-technical skills, using emerging technologies along with pedagogic techniques and cadaver dissection, may become the state-of-the-art for European Neurosurgical training programs in the next future.

Machine Learning Identification of Surgical and Operative Factors Associated With Surgical Expertise in Virtual Reality Simulation

IMPORTANCE

Despite advances in the assessment of technical skills in surgery, a clear understanding of the composites of technical expertise is lacking. Surgical simulation allows for the quantitation of psychomotor skills, generating data sets that can be analyzed using machine learning algorithms.

OBJECTIVE

To identify surgical and operative factors selected by a machine learning algorithm to accurately classify participants by level of expertise in a virtual reality surgical procedure.

DESIGN, SETTING, AND PARTICIPANTS

Fifty participants from a single university were recruited between March 1, 2015, and May 31, 2016, to participate in a case series study at McGill University Neurosurgical Simulation and Artificial Intelligence Learning Centre. Data were collected at a single time point and no follow-up data were collected. Individuals were classified a priori as expert (neurosurgery staff), seniors (neurosurgical fellows and senior residents), juniors (neurosurgical junior residents), and medical students, all of whom participated in 250 simulated tumor resections.

EXPOSURES

All individuals participated in a virtual reality neurosurgical tumor resection scenario. Each scenario was repeated 5 times.

MAIN OUTCOMES AND MEASURES

Through an iterative process, performance metrics associated with instrument movement and force, resection of tissues, and bleeding generated from the raw simulator data output were selected by K-nearest neighbor, naive Bayes, discriminant analysis, and support vector machine algorithms to most accurately determine group membership.

RESULTS

A total of 50 individuals (9 women and 41 men; mean [SD] age, 33.6 [9.5] years; 14 neurosurgeons, 4 fellows, 10 senior residents, 10 junior residents, and 12 medical students) participated. Neurosurgeons were in practice between 1 and 25 years, with 9 (64%) involving a predominantly cranial practice. The K-nearest neighbor algorithm had an accuracy of 90% (45 of 50), the naive Bayes algorithm had an accuracy of 84% (42 of 50), the discriminant analysis algorithm had an accuracy of 78% (39 of 50), and the support vector machine algorithm had an accuracy of 76% (38 of 50). The K-nearest neighbor algorithm used 6 performance metrics to classify participants, the naive Bayes algorithm used 9 performance metrics, the discriminant analysis algorithm used 8 performance metrics, and the support vector machine algorithm used 8 performance metrics. Two neurosurgeons, 1 fellow or senior resident, 1 junior resident, and 1 medical student were misclassified.

CONCLUSIONS AND RELEVANCE

In a virtual reality neurosurgical tumor resection study, a machine learning algorithm successfully classified participants into 4 levels of expertise with 90% accuracy. These findings suggest that algorithms may be capable of classifying surgical expertise with greater granularity and precision than has been previously demonstrated in surgery.

Development of a performance model for virtual reality tumor resections

OBJECTIVE

Previous work from the authors has shown that hand ergonomics plays an important role in surgical psychomotor performance during virtual reality brain tumor resections. In the current study they propose a hypothetical model that integrates the human and task factors at play during simulated brain tumor resections to better understand the hand ergonomics needed for optimal safety and efficiency. They hypothesize that 1) experts (neurosurgeons), compared to novices (residents and medical students), spend a greater proportion of their time in direct contact with critical tumor areas; 2) hand ergonomic conditions (most favorable to unfavorable) prompt participants to adapt in order to optimize tumor resection; and 3) hand ergonomic adaptation is acquired with increasing expertise.

METHODS

In an earlier study, experts (neurosurgeons) and novices (residents and medical students) were instructed to resect simulated brain tumors on the NeuroVR (formerly NeuroTouch) virtual reality neurosurgical simulation platform. For the present study, the simulated tumors were divided into four quadrants (Q1 to Q4) to assess hand ergonomics at various levels of difficulty. The spatial distribution of time expended, force applied, and tumor volume removed was analyzed for each participant group (total of 22 participants).

RESULTS

Neurosurgeons spent a significantly greater percentage of their time in direct contact with critical tumor areas. Under the favorable hand ergonomic conditions of Q1 and Q3, neurosurgeons and senior residents spent significantly more time in Q1 than in Q3. Although forces applied in these quadrants were similar, neurosurgeons, having spent more time in Q1, removed significantly more tumor in Q1 than in Q3. In a comparison of the most favorable (Q2) to unfavorable (Q4) hand ergonomic conditions, neurosurgeons adapted the forces applied in each quadrant to resect similar tumor volumes. Differences between Q2 and Q4 were emphasized in measures of force applied per second, tumor volume removed per second, and tumor volume removed per unit of force applied. In contrast, the hand ergonomics of medical students did not vary across quadrants, indicating the existence of an "adaptive capacity" in neurosurgeons.

CONCLUSIONS

The study results confirm the experts' (neurosurgeons) greater capacity to adapt their hand ergonomics during simulated neurosurgical tasks. The proposed hypothetical model integrates the study findings with various human and task factors that highlight the importance of learning in the acquisition of hand ergonomic adaptation.

A Comparison of Visual Rating Scales and Simulated Virtual Reality Metrics in Neurosurgical Training: A Generalizability Theory Study

BACKGROUND

Adequate assessment and feedback remains a cornerstone of psychomotor skills acquisition, particularly within neurosurgery where the consequence of adverse operative events is significant. However, a critical appraisal of the reliability of visual rating scales in neurosurgery is lacking. Therefore, we sought to design a study to compare visual rating scales with simulated metrics in a neurosurgical virtual reality task.

METHODS

Neurosurgical faculty rated anonymized participant video recordings of the removal of simulated brain tumors using a visual rating scale made up of seven composite elements. Scale reliability was evaluated using generalizability theory, and scale subcomponents were compared with simulated metrics using Pearson correlation analysis.

RESULTS

Four staff neurosurgeons evaluated 16 medical student neurosurgery applicants. Overall scale reliability and internal consistency were 0.73 and 0.90, respectively. Reliability of 0.71 was achieved with two raters. Individual participants, raters, and scale items accounted for 27%, 11%, and 0.6% of the data variability. The hemostasis scale component related to the greatest number of simulated metrics, whereas respect for no-go zones and tissue was correlated with none. Metrics relating to instrument force and patient safety (brain volume removed and blood loss) were captured by the fewest number of rating scale components.

CONCLUSIONS

To our knowledge, this is the first study comparing participant's ratings with simulated performance. Given rating scales capture less well instrument force, quantity of brain volume removed, and blood loss, we suggest adopting a hybrid educational approach using visual rating scales in an operative environment, supplemented by simulated sessions to uncover potentially problematic surgical technique.

Virtual reality and augmented reality in the management of intracranial tumors: A review

Neurosurgeons are faced with the challenge of planning, performing, and learning complex surgical procedures. With improvements in computational power and advances in visual and haptic display technologies, augmented and virtual surgical environments can offer potential benefits for tests in a safe and simulated setting, as well as improve management of real-life procedures. This systematic literature review is conducted in order to investigate the roles of such advanced computing technology in neurosurgery subspecialization of intracranial tumor removal. The study would focus on an in-depth discussion on the role of virtual reality and augmented reality in the management of intracranial tumors: the current status, foreseeable challenges, and future developments.

Is Virtual Reality Surgical Performance Influenced by Force Feedback Device Utilized?

OBJECTIVE

The study objectives were to assess if surgical performance and subjective assessment of a virtual reality simulator platform was influenced by changing force feedback devices.

DESIGN

Participants used the NeuroVR (formerly NeuroTouch) simulator to perform 5 practice scenarios and a realistic scenario involving subpial resection of a virtual reality brain tumor with simulated bleeding. The influence of force feedback was assessed by utilizing the Omni and Entact haptic systems. Tier 1, tier 2, and tier 2 advanced metrics were used to compare results. Operator subjective assessment of the haptic systems tested utilized seven Likert criteria (score 1 to 5).

SETTING

The study is carried out at the McGill Neurosurgical Simulation Research and Training Centre, Montreal Neurological Institute and Hospital, Montreal, Canada.

PARTICIPANTS

Six expert operators in the utilization of the NeuroVR simulator platform.

RESULTS

No significant differences in surgical performance were found between the two haptic devices. Participants significantly preferred the Entact system on all 7 Likert criteria of subjective assessment.

CONCLUSIONS

Our results show no statistical differences in virtual reality surgical performance utilizing the two bimanual haptic devices tested. Subjective assessments demonstrated that participants preferred the Entact system. Our results suggest that to maximize realism of the training experience educators employing virtual reality simulators may find it useful to assess expert opinion before choosing a force feedback device.

Virtual reality simulation of robotic transsphenoidal brain tumor resection: Evaluating dynamic motion scaling in a master-slave system

Background

Integrating simulators with robotic surgical procedures could assist in designing and testing of novel robotic control algorithms and further enhance patient‐specific pre‐operative planning and training for robotic surgeries.

Methods

A virtual reality simulator, developed to perform the transsphenoidal resection of pituitary gland tumours, tested the usability of robotic interfaces and control algorithms. It used position‐based dynamics to allow soft‐tissue deformation and resection with haptic feedback; dynamic motion scaling control was also incorporated into the simulator.

Results

Neurosurgeons and residents performed the surgery under constant and dynamic motion scaling conditions (CMS vs DMS). DMS increased dexterity and reduced the risk of damage to healthy brain tissue. Post‐experimental questionnaires indicated that the system was well‐evaluated by experts.

Conclusion

The simulator was intuitively and realistically operated. It increased the safety and accuracy of the procedure without affecting intervention time. Future research can investigate incorporating this simulation into a real micro‐surgical robotic system.

Automaticity of Force Application During Simulated Brain Tumor Resection: Testing the Fitts and Posner Model

OBJECTIVE

The Fitts and Posner model of motor learning hypothesized that with deliberate practice, learners progress through stages to an autonomous phase of motor ability. To test this model, we assessed the automaticity of neurosurgeons, senior residents, and junior residents when operating on 2 identical tumors using the NeuroVR virtual reality simulation platform.

DESIGN

Participants resected 9 identical simulated tumors on 2 occasions (total = 18 resections). These resections were separated by the removal of a variable number of tumors with different visual and haptic complexities to mirror neurosurgical practice. Consistency of force application was used as a metric to assess automaticity and was defined as applying forces 1 standard deviation above or below a specific mean force application. Amount and specific location of force application during second identical tumor resection was compared to that used for the initial tumor.

SETTING

This study was conducted at the McGill Neurosurgical Simulation Research and Training Center, Montreal Neurologic Institute and Hospital, Montreal, Canada.

PARTICIPANTS

Nine neurosurgeons, 10 senior residents, and 8 junior residents.

RESULTS

Neurosurgeons display statistically significant increased consistency of force application when compared to resident groups when results from all tumor resections were assessed. Assessing individual tumor types demonstrates significant differences between the neurosurgeon and resident groups when resecting hard stiffness similar-to-background (white) tumors and medium-stiffness tumors. No statistical difference in consistency of force application was found when junior and senior residents were compared.

CONCLUSION

"Experts" display significantly more automaticity when operating on identical simulated tumors separated by a series of different tumors using the NeuroVR platform. These results support the Fitts and Posner model of motor learning and are consistent with the concept that automaticity improves after completing residency training. The potential educational application of our findings is outlined related to neurosurgical resident training.

Virtual Reality Tumor Resection: The Force Pyramid Approach

BACKGROUND

The force pyramid is a novel visual representation allowing spatial delineation of instrument force application during surgical procedures. In this study, the force pyramid concept is employed to create and quantify dominant hand, nondominant hand, and bimanual force pyramids during resection of virtual reality brain tumors.

OBJECTIVE

To address 4 questions: Do ergonomics and handedness influence force pyramid structure? What are the differences between dominant and nondominant force pyramids? What is the spatial distribution of forces applied in specific tumor quadrants? What differentiates “expert” and “novice” groups regarding their force pyramids?

METHODS

Using a simulated aspirator in the dominant hand and a simulated sucker in the nondominant hand, 6 neurosurgeons and 14 residents resected 8 different tumors using the CAE NeuroVR virtual reality neurosurgical simulation platform (CAE Healthcare, Montréal, Québec and the National Research Council Canada, Boucherville, Québec). Position and force data were used to create force pyramids and quantify tumor quadrant force distribution.

RESULTS

Force distribution quantification demonstrates the critical role that handedness and ergonomics play on psychomotor performance during simulated brain tumor resections. Neurosurgeons concentrate their dominant hand forces in a defined crescent in the lower right tumor quadrant. Nondominant force pyramids showed a central peak force application in all groups. Bimanual force pyramids outlined the combined impact of each hand. Distinct force pyramid patterns were seen when tumor stiffness, border complexity, and color were altered.

CONCLUSION

Force pyramids allow delineation of specific tumor regions requiring greater psychomotor ability to resect. This information can focus and improve resident technical skills training.

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.

Endoscopic Endonasal Transclival Approach versus Dual Transorbital Port Technique for Clip Application to the Posterior Circulation: A Cadaveric Anatomical and Cerebral Circulation Simulation Study

Purpose  Simulation training offers a useful opportunity to appreciate vascular anatomy and develop the technical expertise required to clip intracranial aneurysms of the posterior circulation. Materials and Methods  In cadavers, a comparison was made between the endoscopic transclival approach (ETA) alone and a combined multiportal approach using the ETA and a transorbital precaruncular approach (TOPA) to evaluate degrees of freedom, angles of visualization, and ergonomics of aneurysm clip application to the posterior circulation depending on basilar apex position relative to the posterior clinoids. Results  ETA alone provided improved access to the posterior circulation when the basilar apex was high riding compared with the posterior clinoids. ETA + TOPA provided a significantly improved functional working area for instruments and visualization of the posterior circulation for a midlevel basilar apex. A single-shaft clip applier provided improved visualization and space for instruments. Proximal and distal vascular control and feasibility of aneurysmal clipping were demonstrated. Conclusions  TOPA is a medial orbital approach to the central skull base; a transorbital neuroendoscopic surgery approach. This anatomical simulation provides surgical teams an alternative to the ETA approach alone to address posterior circulation aneurysms, and a means to preoperatively prepare for intraoperative anatomical and surgical instrumentation challenges.