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

Latex vascular injection as method for enhanced neurosurgical training and skills

Background

Tridimensional medical knowledge of human anatomy is a key step in the undergraduate and postgraduate medical education, especially in surgical fields. Training simulation before real surgical procedures is necessary to develop clinical competences and to minimize surgical complications.

Methods

Latex injection of vascular system in brain and in head-neck segment is made after washing out of the vascular system and fixation of the specimen before and after latex injection.

Results

Using this latex injection technique, the vascular system of 90% of brains and 80% of head-neck segments are well-perfused. Latex-injected vessels maintain real appearance compared to silicone, and more flexible vessels compared to resins. Besides, latex makes possible a better perfusion of small vessels.

Conclusions

Latex vascular injection technique of the brain and head-neck segment is a simulation model for neurosurgical training based on real experiencing to improve surgical skills and surgical results.

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.

Nondominant Hand Skills Spatial and Psychomotor Analysis During a Complex Virtual Reality Neurosurgical Task-A Case Series Study

BACKGROUND

Virtual reality surgical simulators provide detailed psychomotor performance data, allowing qualitative and quantitative assessment of hand function. The nondominant hand plays an essential role in neurosurgery in exposing the operative area, assisting the dominant hand to optimize task execution, and hemostasis. Outlining expert-level nondominant hand skills may be critical to understand surgical expertise and aid learner training.

OBJECTIVE

To (1) provide validity for the simulated bimanual subpial tumor resection task and (2) to use this simulation in qualitative and quantitative evaluation of nondominant hand skills for bipolar forceps utilization.

METHODS

In this case series study, 45 right-handed participants performed a simulated subpial tumor resection using simulated bipolar forceps in the nondominant hand for assisting the surgery and hemostasis. A 10-item questionnaire was used to assess task validity. The nondominant hand skills across 4 expertise levels (neurosurgeons, senior trainees, junior trainees, and medical students) were analyzed by 2 visual models and performance metrics.

RESULTS

Neurosurgeon median (range) overall satisfaction with the simulated scenario was 4.0/5.0 (2.0-5.0). The visual models demonstrated a decrease in high force application areas on pial surface with increased expertise level. Bipolar-pia mater interactions were more focused around the tumoral region for neurosurgeons and senior trainees. These groups spent more time using the bipolar while interacting with pia. All groups spent significantly higher time in the left upper pial quadrant than other quadrants.

CONCLUSION

This work introduces new approaches for the evaluation of nondominant hand skills which may help surgical trainees by providing both qualitative and quantitative feedback.

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.

Tool-Tissue Forces in Hemangioblastoma Surgery

OBJECTIVE

Surgical resection of intracranial hemangioblastoma poses technical challenges that may be difficult to impart to trainees. Here, we introduce knowledge of tool-tissue forces in Newton (N), observed during hemangioblastoma surgery.

METHODS

Seven surgeons (2 groups: trainees and mentor), with mentor (n = 1) and trainees (n = 6, PGY 1-6 including clinical fellowship), participated in 6 intracranial hemangioblastoma surgeries. Using sensorized bipolar forceps, we evaluated tool-tissue force profiles of 5 predetermined surgical tasks: 1) dissection, 2) coagulation, 3) retracting, 4) pulling, and 5) manipulating. Force profile for each trial included force duration, average, maximum, minimum, range, standard deviation (SD), and correlation coefficient. Force errors including unsuccessful trial bleeding or incomplete were compared between surgeons and with successful trials.

RESULTS

Force data from 718 trials were collected. The mean (standard deviation) of force used in all surgical tasks and across all surgical levels was 0.20 ± 0.17 N. The forces exerted by trainee surgeons were significantly lower than those of the mentor (0.15 vs. 0.24; P < 0.0001). A total of 18 (4.5%) trials were unsuccessful, 4 of them being unsuccessful trial-bleeding and the rest, unsuccessful trial-incomplete. The force in unsuccessful trial-bleeding was higher than successful trials (0.3 [0.09] vs. 0.17 [0.11]; P = 0.0401). Toward the end of surgery, higher force was observed (0.17 vs. 0.20; P < 0.0001).

CONCLUSIONS

The quantification of tool-tissue forces during hemangioblastoma surgery with feedback to the surgeon, could well enhance surgical training and allow avoidance of bleeding associated with high force error.

[Pedagogical impact of a MOOC on surgical technique of kidney transplantation]

OBJECTIVE

To evaluate the educational impact of a pilot MOOC (Massive Open Online Course), validated by the French College of Urology Teachers (FCUT), on the surgical technique of kidney transplantation.

MATERIALS AND METHODS

We developed a MOOC on the surgical technique of kidney transplantation, based on a video of a surgical procedure, performed by an expert surgeon. The MOOC has been validated by the FCUT. We have created 2 student groups: 1) MOOC-pre-QCM group: visualization of the MOOC then answer to the MCQs and satisfaction questions; 2) MOOC-post-QCM group: answer to the MCQs then visualization of the MOOC then answers to the satisfaction questions. In total, 20 MCQs on the kidney transplantation technique were completed by the 2 groups. The answers were anonymous.

RESULTS

A total of 142 people answered the MCQs (MOOC-pre-QCM group (n=66) and MOOC-post-QCM group (n=76)). Twenty-nine percent (41/142) of the participants were fellows and 71 % (101/142) were residents. The proportion of fellows and residents was identical between the 2 groups. The rate of correct answers to the 20 MCQs was statistically higher in the MOOC-pre-QCM group, compared to the MOOC-post-QCM group (88.6 % versus 73.3 %, P<0.0001). Ninety-one percent of students found the MOOC "Very Useful" or "Useful". The median MOOC rating, given by students, was 8/10.

CONCLUSION

This study showed a positive impact of the MOOC on theoretical knowledge of kidney transplantation surgical technique. This MOOC could serve as a pilot project for the development of other MOOCs on urological surgery.

LEVEL

3.

Simulation for skills training in neurosurgery: a systematic review, meta-analysis, and analysis of progressive scholarly acceptance

At a time of significant global unrest and uncertainty surrounding how the delivery of clinical training will unfold over the coming years, we offer a systematic review, meta-analysis, and bibliometric analysis of global studies showing the crucial role simulation will play in training. Our aim was to determine the types of simulators in use, their effectiveness in improving clinical skills, and whether we have reached a point of global acceptance. A PRISMA-guided global systematic review of the neurosurgical simulators available, a meta-analysis of their effectiveness, and an extended analysis of their progressive scholarly acceptance on studies meeting our inclusion criteria of simulation in neurosurgical education were performed. Improvement in procedural knowledge and technical skills was evaluated. Of the identified 7405 studies, 56 studies met the inclusion criteria, collectively reporting 50 simulator types ranging from cadaveric, low-fidelity, and part-task to virtual reality (VR) simulators. In all, 32 studies were included in the meta-analysis, including 7 randomised controlled trials. A random effects, ratio of means effects measure quantified statistically significant improvement in procedural knowledge by 50.2% (ES 0.502; CI 0.355; 0.649, p < 0.001), technical skill including accuracy by 32.5% (ES 0.325; CI - 0.482; - 0.167, p < 0.001), and speed by 25% (ES - 0.25, CI - 0.399; - 0.107, p < 0.001). The initial number of VR studies (n = 91) was approximately double the number of refining studies (n = 45) indicating it is yet to reach progressive scholarly acceptance. There is strong evidence for a beneficial impact of adopting simulation in the improvement of procedural knowledge and technical skill. We show a growing trend towards the adoption of neurosurgical simulators, although we have not fully gained progressive scholarly acceptance for VR-based simulation technologies in neurosurgical education.

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.

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 &lt; .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.

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.

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.

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.