Simulation in neurosurgery: a review of computer-based simulation environments and their surgical applications

CTA-based 3D virtual model for preoperative simulation and intraoperative neuronavigation in the surgical treatment of distal anterior cerebral artery aneurysms

OBJECTIVE

This study aims to assess the efficacy and limitations of Computed Tomography Angiography (CTA)-based 3D virtual models for preoperative simulation and intraoperative neuronavigation in the surgical treatment of Distal Anterior Cerebral Artery (DACA) Aneurysms.

METHODS

A retrospective observational study was conducted, analyzing patients who underwent surgical clipping of DACA aneurysms via an interhemispheric approach from 2016 to 2022. Outcomes measured included qualitative analyses of 3D reconstructions against actual intraoperative anatomy, neuronavigator accuracy, 6-month modified Rankin Scale (mRS), complete exclusion rates, and surgical complications. Patient demographics, clinical characteristics, surgical timing, and intraoperative data were meticulously documented for analysis.

RESULTS

Fifteen patients were included in the study, with a mean age of 52 years. The mean Hunt-Hess score at admission was 2.2, encompassing 2 unruptured and 13 ruptured aneurysms. Intraoperative anatomical visualization perfectly matched the preoperative 3D model in 13 cases, with discrepancies in two. Neuronavigation demonstrated a mean accuracy of 1.76 mm, remaining consistent in 14 patients, and accurately tracking the planned trajectory. Postoperative complications occurred in 26.5 % of patients, including two fatalities, with no navigation-related complications. Incomplete aneurysm occlusion was observed in one case. The mean mRS score at 6 months was 2.46.

CONCLUSIONS

The employment of 3D CTA for preoperative simulation and intraoperative neuronavigation holds significant potential in enhancing the surgical management of DACA aneurysms. Despite some discrepancies and technical limitations, the overall precision of preoperative simulations and the strategic value of intraoperative neuronavigation highlight their utility in improving surgical outcomes.

Life and Death 2: The First Neurosurgical Computer Simulation

SUMMARY STATEMENT

Life and Death 2: The Brain was the first computerized neurosurgical simulator. It was developed as a commercial video game for a general audience. Despite this, it contains many valuable lessons for the simulation and education of nontechnical skills as well as being a historical landmark in the field of neurosurgery and medical simulation.

Patient-Specific, Mechanistic Models of Tumor Growth Incorporating Artificial Intelligence and Big Data

Despite the remarkable advances in cancer diagnosis, treatment, and management over the past decade, malignant tumors remain a major public health problem. Further progress in combating cancer may be enabled by personalizing the delivery of therapies according to the predicted response for each individual patient. The design of personalized therapies requires the integration of patient-specific information with an appropriate mathematical model of tumor response. A fundamental barrier to realizing this paradigm is the current lack of a rigorous yet practical mathematical theory of tumor initiation, development, invasion, and response to therapy. We begin this review with an overview of different approaches to modeling tumor growth and treatment, including mechanistic as well as data-driven models based on big data and artificial intelligence. We then present illustrative examples of mathematical models manifesting their utility and discuss the limitations of stand-alone mechanistic and data-driven models. We then discuss the potential of mechanistic models for not only predicting but also optimizing response to therapy on a patient-specific basis. We describe current efforts and future possibilities to integrate mechanistic and data-driven models. We conclude by proposing five fundamental challenges that must be addressed to fully realize personalized care for cancer patients driven by computational models.

Evaluation of konjac noodle as a microsurgery training model: learning curve analysis

BACKGROUND

classical models of microsurgical anastomosis training are expensive and have ethical implications. Some alternatives join low cost and easiness to store. However, the translation of knowledge acquired by training in these methods into the traditional ones is not clear. This project aims to assess the feasibility of konjac noodles as a reliable microsurgery-training model.

METHODS

10 neurosurgery residents performed an end-to-end anastomosis in a 2-3mm placenta artery. The anastomoses were evaluated quantitatively, recording time; and qualitatively, applying a validated score (Anastomosis Lapse Index - ALI) by three experienced neurosurgeons and verifying the presence of gross leakage through the infusion of fluorescein. Subsequently, they performed 10 non-consecutive sessions of anastomosis training in the konjac noodle. Eventually, a final anastomosis in the placenta model was performed and the same parameters were scored.

RESULTS

we observed a 17min reduction in the mean time to perform the anastomosis in the placenta model after the training in the konjac (p<0.05). There was a non-significant 20% reduction in gross leakage, but the training sessions were not able to consistently improve the ALI score.

CONCLUSIONS

we demonstrate a reduction in anastomosis performing time in placental arteries after training sessions in the konjac noodle model, which can be regarded as a feasible low-cost method, particularly useful in centers with surgical microscopes only in the operation room.

High-fidelity, simulation-based microsurgical training for neurosurgical residents

OBJECTIVE

Simulation is increasingly recognized as an important supplement to operative training. The live rat femoral artery model is a well-established model for microsurgical skills simulation. In this study, the authors present an 11-year experience incorporating a comprehensive, longitudinal microsurgical training curriculum into a Canadian neurosurgery program. The first goal was to evaluate training effectiveness, using a well-studied rating scale with strong validity. The second goal was to assess the impact of the curriculum on objective measures of subsequent operating room performance during postgraduate year (PGY)–5 and PGY-6 training.

METHODS

PGY-2 neurosurgery residents completed a 1-year curriculum spanning 17 training sessions divided into 5 modules of increasing fidelity. Both perfused duck wing and live rat vessel training models were used. Three modules comprised live microvascular anastomosis. Trainee performance was video recorded and blindly graded using the Objective Structured Assessment of Technical Skills Global Rating Scale. Eleven participants who completed the training curriculum and 3 subjects who had not participated had their subsequent operative performances evaluated when they were at the PGY-5 and PGY-6 levels.

RESULTS

Eighteen participants completed 106 microvascular anastomoses during the study. There was significant improvement in 6 measurable skills during the curriculum. The mean overall score was significantly higher on the fifth attempt compared with the first attempt for all 3 live anastomotic modules (p < 0.001). Each module had a different improvement profile across the skills assessed. Those who completed the microvascular skills curriculum demonstrated a greater number of independent evaluations during superficial surgical exposure, deep exposure, and primary maneuvers at the PGY-5 and PGY-6 levels.

CONCLUSIONS

High-fidelity microsurgical simulation training leads to significant improvement in microneurosurgical skills. Transfer of acquired skills to the operative environment and durability for at least 3 to 4 years show encouraging preliminary results and are subject to ongoing investigation.

Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology

Digital twins employ mathematical and computational models to virtually represent a physical object (e.g., planes and human organs), predict the behavior of the object, and enable decision-making to optimize the future behavior of the object. While digital twins have been widely used in engineering for decades, their applications to oncology are only just emerging. Due to advances in experimental techniques quantitatively characterizing cancer, as well as advances in the mathematical and computational sciences, the notion of building and applying digital twins to understand tumor dynamics and personalize the care of cancer patients has been increasingly appreciated. In this review, we present the opportunities and challenges of applying digital twins in clinical oncology, with a particular focus on integrating medical imaging with mechanism-based, tissue-scale mathematical modeling. Specifically, we first introduce the general digital twin framework and then illustrate existing applications of image-guided digital twins in healthcare. Next, we detail both the imaging and modeling techniques that provide practical opportunities to build patient-specific digital twins for oncology. We then describe the current challenges and limitations in developing image-guided, mechanism-based digital twins for oncology along with potential solutions. We conclude by outlining five fundamental questions that can serve as a roadmap when designing and building a practical digital twin for oncology and attempt to provide answers for a specific application to brain cancer. We hope that this contribution provides motivation for the imaging science, oncology, and computational communities to develop practical digital twin technologies to improve the care of patients battling cancer.

Educational impact of early COVID-19 operating room restrictions on neurosurgery resident training in the United States: A multicenter study

Background

The coronavirus (COVID-19) pandemic has caused unprecedented suspensions of neurosurgical elective surgeries, a large proportion of which involve spine procedures. The goal of this study is to report granular data on the impact of early COVID-19 pandemic operating room restrictions upon neurosurgical case volume in academic institutions, with attention to its secondary impact upon neurosurgery resident training. This is the first multicenter quantitative study examining these early effects upon neurosurgery residents caseloads.

Methods

A retrospective review of neurosurgical caseloads among seven residency programs between March 2019 and April 2020 was conducted. Cases were grouped by ACGME Neurosurgery Case Categories, subspecialty, and urgency (elective vs. emergent). Residents caseloads were stratified into junior (PGY1-3) and senior (PGY4-7) levels. Descriptive statistics are reported for individual programs and pooled across institutions.

Results

When pooling across programs, the 2019 monthly mean (SD) case volume was 214 (123) cases compared to 217 (129) in January 2020, 210 (115) in February 2020, 157 (81), in March 2020 and 82 (39) cases April 2020. There was a 60% reduction in caseload between April 2019 (207 [101]) and April 2020 (82 [39]). Adult spine cases were impacted the most in the pooled analysis, with a 66% decrease in the mean number of cases between March 2020 and April 2020. Both junior and senior residents experienced a similar steady decrease in caseloads, with the largest decreases occurring between March and April 2020 (48% downtrend).

Conclusions

Results from our multicenter study reveal considerable decreases in caseloads in the neurosurgical specialty with elective adult spine cases experiencing the most severe decline. Both junior and senior neurosurgical residents experienced dramatic decreases in case volumes during this period. With the steep decline in elective spine cases, it is possible that fellowship directors may see a disproportionate increase in spine fellowships in the coming years. In the face of the emerging Delta and Omicron variants, programs should pay attention toward identifying institution-specific deficiencies and developing plans to mitigate the negative educational effects secondary to such caseloads reduction.

Application of 3D Printing Support Material for Neurosurgical Simulation

Brain dissection, an intricate neurosurgical skill, is central to life-saving procedures such as intrinsic brain tumor excision and resective epilepsy surgery. The aims of this manuscript are to outline the selection process of a suitable material for the development of a dissectible brain simulator and to present the use of support material, SUP 706, manufactured by Stratasys Ltd. as a non-waste alternative for sustainably engineering solutions for surgical education. A feasibility study was conducted through qualitative function deployment (QFD) followed by a material selection process. End-user requirements and manufacturing product characteristics were incorporated into the workflow. Three materials, silicone, TissueMatrix™ and support material each formed the primary component of the first two prototypes. Expert feedback, manufacturing cost, safety profiling, functional fidelity and post-processing time data were collected and analyzed. The unique break-away feature of moist support material was found to be more suitable than using silicone or TissueMatrix™ for demonstrating brain dissection techniques. In addition, support material displayed higher functional fidelity by mimicking surgical tissues such as pia mater, gray and white matter, and blood vessels. The cost of the support material prototype was 39% less that of TissueMatrix™ and roughly the same as the silicone model. It took twice as long to post-process the support material prototype than it did the TissueMatrix™ design. Support material lost its ideal dissection properties and began to disintegrate after 30 - 45 minutes. In conclusion 3D printer support material is a low-cost material for a dissectible brain simulator.Clinical Relevance- The use of support material as the primary material in developing a dissectible brain simulator is a promising way of advancing neurosurgical education.

A High-Fidelity Hybrid Virtual Reality Simulator of Aneurysm Clipping Repair With Brain Sylvian Fissure Exploration for Vascular Neurosurgery Training

INTRODUCTION

Microsurgery clipping is one of the most challenging surgical interventions in neurosurgery. The opportunities to train residents are scarce, but the need for accumulating practice is mandatory. New simulating tools are needed for skill learning.

METHODS

The design, implementation, and assessment of a new hybrid aneurysm clipping simulator are presented. It consists of an ergonomic workstation with a patient head mannequin and a physics-based virtual reality simulation with bimanual haptic feedback. The simulator recreates scenarios of microsurgery from the patient fixation and the exploration of the brain lobes through Sylvian fissure and vascular structures to the aneurysm clipping. Skill metrics were introduced, including monitoring of gestures movements, exerted forces, tissue displacements, and precision in clipping.

RESULTS

Two experimental conditions were tested: (1) simple clipping without brain tissue exploration and (2) clipping the aneurysm with brain Sylvian fissure exploration. Differences in the bimanual gestures were observed between both conditions. The quantitative measurements of tissue displacement of the brain lobes exhibited more tissue retrieval for the surgical gestures of neurosurgeons. Appraisal with questionnaires showed positive scores by neurosurgeons in all items evaluating the usability and realism of the simulator.

CONCLUSIONS

The simulator was well accepted and feasible for training purposes. The analysis of the interactions with virtual tissues offers information to establish differential and common patterns between tested groups and thus useful metrics for skill evaluation of practitioners. Future work can lead to other tasks during the intervention and the inclusion of more clinical cases.

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.

Potential Efficacy of Multimodal Mixed Reality in Epilepsy Surgery

BACKGROUND

Mixed reality (MR) technology, which can fuse things in real and virtual space in real time, has been used mainly for simulation in neurosurgical training.

OBJECTIVE

To develop MR technology into multimodal MR for intraoperative guidance during epilepsy surgery.

METHODS

A 33-yr-old male patient suffered from intractable general tonic seizures due to left temporal meningoencephalocele. Preoperative scalp electroencephalograms localized interictal epileptic activity on the left temporal lobe. Iomazenil single photon emission tomography revealed temporal lobe lateralization. Magnetic resonance imaging (MRI) demonstrated left basal temporal meningoencephalocele extending into the pterygopalatine fossa through a bone defect at the base of the greater sphenoid wing. A 3-dimensional model was created for MR based on multimodal data including computed tomography, MRI tractography, and digital subtraction angiography, which enabled 3-dimensional visualization of abnormal subcortical fiber connections between the meningoencephalocele and the epileptic focus.

RESULTS

By using intraoperative multimodal MR, we were able to safely remove the meningoencephalocele and perform epileptic focus resection. The patient was seizure-free postoperatively, and no adverse effects were noted.

CONCLUSION

Intraoperative multimodal MR was a feasible and effective technique, and it can be applied for a wide range of epilepsy surgeries.

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.

Force quantification and simulation of pedicle screw tract palpation using direct visuo-haptic volume rendering

Purpose

We present a feasibility study for the visuo-haptic simulation of pedicle screw tract palpation in virtual reality, using an approach that requires no manual processing or segmentation of the volumetric medical data set.

Methods

In a first experiment, we quantified the forces and torques present during the palpation of a pedicle screw tract in a real boar vertebra. We equipped a ball-tipped pedicle probe with a 6-axis force/torque sensor and a motion capture marker cluster. We simultaneously recorded the pose of the probe relative to the vertebra and measured the generated forces and torques during palpation. This allowed us replaying the recorded palpation movements in our simulator and to fine-tune the haptic rendering to approximate the measured forces and torques. In a second experiment, we asked two neurosurgeons to palpate a virtual version of the same vertebra in our simulator, while we logged the forces and torques sent to the haptic device.

Results

In the experiments with the real vertebra, the maximum measured force along the longitudinal axis of the probe was 7.78 N and the maximum measured bending torque was 0.13 Nm. In an offline simulation of the motion of the pedicle probe recorded during the palpation of a real pedicle screw tract, our approach generated forces and torques that were similar in magnitude and progression to the measured ones. When surgeons tested our simulator, the distributions of the computed forces and torques were similar to the measured ones; however, higher forces and torques occurred more frequently.

Conclusions

We demonstrated the suitability of direct visual and haptic volume rendering to simulate a specific surgical procedure. Our approach of fine-tuning the simulation by measuring the forces and torques that are prevalent while palpating a real vertebra produced promising results.

Electronic supplementary material

The online version of this article (10.1007/s11548-020-02258-0) contains supplementary material, which is available to authorized users.

Development and initial evaluation of a novel simulation model for comprehensive brain tumor surgery training

Background

Increasing technico-manual complexity of procedures and time constraints necessitates effective neurosurgical training. For this purpose, both screen- and model-based simulations are under investigation. Approaches including 3D printed brains, gelatin composite models, and virtual environments have already been published. However, quality of brain surgery simulation is limited due to discrepancies in visual and haptic experience. Similarly, virtual training scenarios are still lacking sufficient real-world resemblance. In this study, we introduce a novel simulator for realistic neurosurgical training that combines real brain tissue with 3D printing and augmented reality.

Methods

Based on a human CT scan, a skull base and skullcap were 3D printed and equipped with an artificial dura mater. The cerebral hemispheres of a calf’s brain were placed in the convexity of the skullcap and tumor masses composed of aspic, water, and fluorescein were injected in the brain. The skullcap and skull base were placed on each other, glued together, and filled up with an aspic water solution for brain fixation. Then, four surgical scenarios were performed in the operating room as follows: (1) simple tumor resection, (2) complex tumor resection, (3) navigated biopsy via burr hole trepanation, and (4) retrosigmoidal craniotomy. Neuronavigation, augmented reality, fluorescence, and ocular—as well as screen-based (exoscopic)—surgery were available for the simulator training. A total of 29 participants performed at least one training scenario of the simulator and completed a 5-item Likert-like questionnaire as well as qualitative interviews. The questionnaire assessed the realism of the tumor model, skull, and brain tissue as well as the capability for training purposes.

Results

Visual and sensory realism of the skull and brain tissue were rated,”very good,” while the sensory and visual realism of the tumor model were rated “good.” Both overall satisfaction with the model and eligibility of the microscope and neurosurgical instruments for training purposes were rated with “very good.” However, small size of the calf’s brain, its limited shelf life, and the inability to simulate bleedings due to the lack of perfusion were significant drawbacks.

Conclusion

The combination of 3D printing and real brain tissue provided surgical scenarios with very good real-life resemblance. This novel neurosurgical model features a versatile setup for surgical skill training and allows for efficient training of technological support like image and fluorescence guidance, exoscopic surgery, and robotic technology.

Electronic supplementary material

The online version of this article (10.1007/s00701-020-04359-w) contains supplementary material, which is available to authorized users.

Current and future usefulness and potential of virtual simulation in improving outcomes and reducing complications in endovascular treatment of unruptured intracranial aneurysms

BACKGROUND

Simulation training has been used in the aviation industry and surgical specialties for many years, but integration into neurointerventional practice is lagging behind.

OBJECTIVE

To investigate how neurointerventionalists perceive the usefulness and limitations of simulation tools for the treatment of unruptured intracranial aneurysms (UIAs), and to identify simulation applications that were perceived to be most valuable for endovascular UIA treatment.

METHODS

A web-based international multidisciplinary survey was conducted among neurointerventionalists. Participants were asked for their perceptions on the usefulness of current simulation tools and the potential impact of future simulation tools in endovascular UIA treatment. They identified simulation applications that could add most value to endovascular UIA treatment and help to specifically reduce endovascular UIA treatment complications.

RESULTS

233 neurointerventionalists from 38 countries completed the survey, most of whom (157/233 (67.4%)) had access to a simulator as a trainee, but only 15.3% used it frequently. Most participants (117/233 (50.2%)) considered currently available simulation tools relatively useful for endovascular UIA treatment, with greater value for trainees than for staff. Simulation of new devices (147/233 (63.1%)) and virtual practice runs in individual patient anatomy (119/233 (51.1%)) were considered most valuable for reducing endovascular UIA treatment complications.

CONCLUSION

Although neurointerventionalists perceived currently available simulation tools relatively useful, they did not use them regularly during their training. A priori testing of new devices and practice runs in individual patient anatomy in a virtual environment were thought to have the greatest potential for reducing endovascular UIA treatment complications.

Development and Evaluation of Pediatric Mixed-Reality Model for Neuroendoscopic Surgical Training

OBJECTIVE

Neurosurgical training requires several years of supervised procedures and represents a long and challenging process. The development of surgical simulation platforms is essential to reducing the risk of potentially intraoperative severe errors arising from inexperience. To present and perform a phase I validation process of a mixed reality simulation (realistic and virtual simulators combined) for neuroendoscopic surgical training.

METHODS

Tridimensional videos were developed by the 3DS Max program. Physical simulators were made with a synthetic thermoretractile and thermosensible rubber, which, when combined with different polymers, produces >30 different textures that simulate consistencies and mechanical resistance of human tissues. Questionnaires regarding the role of virtual and realistic simulators were applied to experienced neurosurgeons to assess the applicability of the mixed-reality simulation for neuroendoscopic surgical training.

RESULTS

The model was considered as a potential tool for training new residents in neuroendoscopic surgery. It was also adequate for practical application with inexperienced surgeons. According to the overall score, 83% of the surgeons believed that the realistic physical simulator presents distortions when compared with the real anatomic structure, afterwards the model improved 66% tridimensional reconstruction and 66% reported that the virtual simulator allowed a multiangular perspective ability.

CONCLUSIONS

This model provides a highly effective way of working with 3-dimensional data and significantly enhances the learning of surgical anatomy and operative strategies. The combination of virtual and realistic tools may safely improve and abbreviate the surgical learning curve.

Assessing performance of augmented reality-based neurosurgical training

This paper presents a novel augmented reality (AR)-based neurosurgical training simulator which provides a very natural way for surgeons to learn neurosurgical skills. Surgical simulation with bimanual haptic interaction is integrated in this work to provide a simulated environment for users to achieve holographic guidance for pre-operative training. To achieve the AR guidance, the simulator should precisely overlay the 3D anatomical information of the hidden target organs in the patients in real surgery. In this regard, the patient-specific anatomy structures are reconstructed from segmented brain magnetic resonance imaging. We propose a registration method for precise mapping of the virtual and real information. In addition, the simulator provides bimanual haptic interaction in a holographic environment to mimic real brain tumor resection. In this study, we conduct AR-based guidance validation and a user study on the developed simulator, which demonstrate the high accuracy of our AR-based neurosurgery simulator, as well as the AR guidance mode’s potential to improve neurosurgery by simplifying the operation, reducing the difficulty of the operation, shortening the operation time, and increasing the precision of the operation.

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.

Usefulness of High-Resolution Three-Dimensional Multifusion Medical Imaging for Preoperative Planning in Patients with Cerebral Arteriovenous Malformation

BACKGROUND

Successful resection of arteriovenous malformation (AVM) depends on preoperative assessment of the detailed morphology of the AVM. Simultaneous detailed three-dimensional visualization of the feeding arteries, draining veins, and surrounding structures is needed. The aim of this study was to evaluate the usefulness of high-resolution three-dimensional multifusion medical imaging (HR-3DMMI) for preoperative planning of AVM resection.

METHODS

HR-3DMMI combined magnetic resonance imaging, magnetic resonance angiography, thin-slice computed tomography, and three-dimensional rotational angiography. Surface rendering was mainly used for creation of HR-3DMMI using multiple thresholds to create three-dimensional models. HR-3DMMI technique was used in 8 patients for preoperative planning, and imaging findings were compared with operative findings.

RESULTS

All feeding arteries and draining veins were found intraoperatively at the same position as estimated preoperatively and were occluded as planned preoperatively.

CONCLUSIONS

HR-3DMMI technique demonstrated the precise locations of feeding arteries, draining veins, and surrounding important tissues, such as corticospinal tract and arcuate fiber, preoperatively and estimated the appropriate route for resection of the AVM. HR-3DMMI is expected to be a very useful support tool for surgery of AVM.

Simulation Training Methods in Neurological Surgery

Simulation training plays a paramount role in medicine, especially when it comes to mastering surgical skills. By simulating, students gain not only confidence, but expertise, learning to apply theory in a safe environment. As the technological arsenal improved, virtual reality and physical simulators have developed and are now an important part of the Neurosurgery training curriculum. Based on deliberate practice in a controlled space, simulation allows psychomotor skills augment without putting neither patients nor students at risk. When compared to the master-apprentice ongoing model of teaching, simutation becomes even more appealing as it is time-efficient, shortening the learning curve and ultimately leading to error reduction, which is reflected by diminished health care costs in the long run. In this chapter we will discuss the current state of neurosurgery simulation, highlight the potential benefits of this approach, assessing specific training methods and making considerations towards the future of neurosurgical simulation.

The Role of Mixed Reality Simulation for Surgical Training in Spine: Phase 1 Validation

STUDY DESIGN

This study shows the first phase of validation of a new model for realistic training on spine surgery, conducted from January 2014 to November 2015.

OBJECTIVE

To propose and validate a new tool for neurosurgical education, associating virtual and realistic simulation (mixed reality), for spine surgery.

SUMMARY OF BACKGROUND DATA

Surgical simulation is a relatively new filed that has a lot to offer to neurosurgical education. Training a new surgeon may take years of hands-on procedures, increasing the risk to patient's safety. The development of surgical simulation platforms is therefore essential to reducing the risk of potentially serious risks and improving outcome.

METHODS

Sixteen experienced spinal surgeons evaluated these simulators and answered the questionnaire regarding the simulation as a beneficial education tool. They evaluated the simulators in regard to dissection by planes, identification of pathology (lumbar canal stenosis), instrumentation and simulation of cerebrospinal fluid (CSF) leak, and the relevant aspects of the computerized tomography (CT) imaging.

RESULTS

The virtual and physical simulators for spine surgery were approved by an expert surgery team, and considered adequate for educational purposes. The proportion of the answers was estimated by the confidence intervals.

CONCLUSION

The surgery team considered that this virtual simulation provides a highly effective training environment, and it significantly enhances teaching of surgical anatomy and operative strategies in the neurosurgical field. A mixture of physical and virtual simulation provided the desired results of enhancing the requisite psychomotor and cognitive skills, previously acquired only during a surgical apprenticeship. The combination of these tools may potentially improve and abbreviate the learning curve for trainees, in a safe environment.

LEVEL OF EVIDENCE

3.

Development of a brain simulator for intracranial targeting: Technical note

Learning and enhancing of manual skills in the field of neurosurgery requires an intensive training which can be maintained by using virtual reality (VR)-based or physical model (PM)-based simulators. However, both simulator types are limited to one specific intracranial procedure, e.g. the application of an external ventricular drainage (EVD), and they do not provide any accuracy verification. We present a brain simulator which consists of a 3D human skull model having five electroconductive balls in its interior. The installed balls represent intracranial target points providing various accuracy problems in neuronavigation. They are electrically contacted to lamps getting an optical signal by touching them with a current-carrying target tool. The simulator fulfills two requirements: First, it can prove the accuracy of navigation systems and algorithms. Second, it allows becoming familiar with a navigation system's application in an ex vivo setting. It could be a helpful device in neurosurgical skills labs.

Filling the gap between the OR and virtual simulation: a European study on a basic neurosurgical procedure

BACKGROUND

Currently available simulators are supposed to allow young neurosurgeons to hone their technical skills in a safe environment, without causing any unnecessary harm to their patients caused by their inexperience. For this training method to be largely accepted in neurosurgery, it is necessary to prove simulation efficacy by means of large-scale clinical validation studies.

METHODS

We correlated and analysed the performance at a simulator and the actual operative skills of different neurosurgeons (construct validity). We conducted a study involving 92 residents and attending neurosurgeons from different European Centres; each participant had to perform a virtual task, namely the placement of an external ventricular drain (EVD) at a neurosurgical simulator (ImmersiveTouch). The number of attempts needed to reach the ventricles and the accuracy in positioning the catheter were assessed.

RESULTS

Data suggests a positive correlation between subjects who placed more EVDs in the previous year and those who get better scores at the simulator (p = .008) (fewer attempts and better surgical accuracy). The number of attempts to reach the ventricle was also analysed; senior residents needed fewer attempts (mean = 2.26; SD = 1.11) than junior residents (mean = 3.12; SD = 1.05) (p = .007) and staff neurosurgeons (mean = 2.89, SD = 1.23). Scoring results were compared by using the Fisher's test, for the analysis of the variances, and the Student's T test. Surprisingly, having a wider surgical experience overall does not correlate with the best performance at the simulator.

CONCLUSION

The performance of an EVD placement on a simulator correlates with the density of the neurosurgical experience for that specific task performed in the OR, suggesting that simulators are able to differentiate neurosurgeons according to their surgical ability. Namely this suggests that the simulation performance reflects the surgeons' consistency in placing EVDs in the last year.

Augmented reality in neurosurgery

Neurosurgery is a medical specialty that relies heavily on imaging. The use of computed tomography and magnetic resonance images during preoperative planning and intraoperative surgical navigation is vital to the success of the surgery and positive patient outcome. Augmented reality application in neurosurgery has the potential to revolutionize and change the way neurosurgeons plan and perform surgical procedures in the future. Augmented reality technology is currently commercially available for neurosurgery for simulation and training. However, the use of augmented reality in the clinical setting is still in its infancy. Researchers are now testing augmented reality system prototypes to determine and address the barriers and limitations of the technology before it can be widely accepted and used in the clinical setting.

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.

Virtual reality-based simulators for spine surgery: a systematic review

BACKGROUND CONTEXT

Virtual reality (VR)-based simulators offer numerous benefits and are very useful in assessing and training surgical skills. Virtual reality-based simulators are standard in some surgical subspecialties, but their actual use in spinal surgery remains unclear. Currently, only technical reviews of VR-based simulators are available for spinal surgery.

PURPOSE

Thus, we performed a systematic review that examined the existing research on VR-based simulators in spinal procedures. We also assessed the quality of current studies evaluating VR-based training in spinal surgery. Moreover, we wanted to provide a guide for future studies evaluating VR-based simulators in this field.

STUDY DESIGN AND SETTING

This is a systematic review of the current scientific literature regarding VR-based simulation in spinal surgery.

METHODS

Five data sources were systematically searched to identify relevant peer-reviewed articles regarding virtual, mixed, or augmented reality-based simulators in spinal surgery. A qualitative data synthesis was performed with particular attention to evaluation approaches and outcomes. Additionally, all included studies were appraised for their quality using the Medical Education Research Study Quality Instrument (MERSQI) tool.

RESULTS

The initial review identified 476 abstracts and 63 full texts were then assessed by two reviewers. Finally, 19 studies that examined simulators for the following procedures were selected: pedicle screw placement, vertebroplasty, posterior cervical laminectomy and foraminotomy, lumbar puncture, facet joint injection, and spinal needle insertion and placement. These studies had a low-to-medium methodological quality with a MERSQI mean score of 11.47 out of 18 (standard deviation=1.81).

CONCLUSIONS

This review described the current state and applications of VR-based simulator training and assessment approaches in spinal procedures. Limitations, strengths, and future advancements of VR-based simulators for training and assessment in spinal surgery were explored. Higher-quality studies with patient-related outcome measures are needed. To establish further adaptation of VR-based simulators in spinal surgery, future evaluations need to improve the study quality, apply long-term study designs, and examine non-technical skills, as well as multidisciplinary team training.

Creation of a novel simulator for minimally invasive neurosurgery: fusion of 3D printing and special effects

OBJECTIVE Recent advances in optics and miniaturization have enabled the development of a growing number of minimally invasive procedures, yet innovative training methods for the use of these techniques remain lacking. Conventional teaching models, including cadavers and physical trainers as well as virtual reality platforms, are often expensive and ineffective. Newly developed 3D printing technologies can recreate patient-specific anatomy, but the stiffness of the materials limits fidelity to real-life surgical situations. Hollywood special effects techniques can create ultrarealistic features, including lifelike tactile properties, to enhance accuracy and effectiveness of the surgical models. The authors created a highly realistic model of a pediatric patient with hydrocephalus via a unique combination of 3D printing and special effects techniques and validated the use of this model in training neurosurgery fellows and residents to perform endoscopic third ventriculostomy (ETV), an effective minimally invasive method increasingly used in treating hydrocephalus. METHODS A full-scale reproduction of the head of a 14-year-old adolescent patient with hydrocephalus, including external physical details and internal neuroanatomy, was developed via a unique collaboration of neurosurgeons, simulation engineers, and a group of special effects experts. The model contains "plug-and-play" replaceable components for repetitive practice. The appearance of the training model (face validity) and the reproducibility of the ETV training procedure (content validity) were assessed by neurosurgery fellows and residents of different experience levels based on a 14-item Likert-like questionnaire. The usefulness of the training model for evaluating the performance of the trainees at different levels of experience (construct validity) was measured by blinded observers using the Objective Structured Assessment of Technical Skills (OSATS) scale for the performance of ETV. RESULTS A combination of 3D printing technology and casting processes led to the creation of realistic surgical models that include high-fidelity reproductions of the anatomical features of hydrocephalus and allow for the performance of ETV for training purposes. The models reproduced the pulsations of the basilar artery, ventricles, and cerebrospinal fluid (CSF), thus simulating the experience of performing ETV on an actual patient. The results of the 14-item questionnaire showed limited variability among participants' scores, and the neurosurgery fellows and residents gave the models consistently high ratings for face and content validity. The mean score for the content validity questions (4.88) was higher than the mean score for face validity (4.69) (p = 0.03). On construct validity scores, the blinded observers rated performance of fellows significantly higher than that of residents, indicating that the model provided a means to distinguish between novice and expert surgical skills. CONCLUSIONS A plug-and-play lifelike ETV training model was developed through a combination of 3D printing and special effects techniques, providing both anatomical and haptic accuracy. Such simulators offer opportunities to accelerate the development of expertise with respect to new and novel procedures as well as iterate new surgical approaches and innovations, thus allowing novice neurosurgeons to gain valuable experience in surgical techniques without exposing patients to risk of harm.

A microcontroller-based simulation of dural venous sinus injury for neurosurgical training

OBJECTIVE Surgical simulation has the potential to supplement and enhance traditional resident training. However, the high cost of equipment and limited number of available scenarios have inhibited wider integration of simulation in neurosurgical education. In this study the authors provide initial validation of a novel, low-cost simulation platform that recreates the stress of surgery using a combination of hands-on, model-based, and computer elements. Trainee skill was quantified using multiple time and performance measures. The simulation was initially validated using trainees at the start of their intern year. METHODS The simulation recreates intraoperative superior sagittal sinus injury complicated by air embolism. The simulator model consists of 2 components: a reusable base and a disposable craniotomy pack. The simulator software is flexible and modular to allow adjustments in difficulty or the creation of entirely new clinical scenarios. The reusable simulator base incorporates a powerful microcomputer and multiple sensors and actuators to provide continuous feedback to the software controller, which in turn adjusts both the screen output and physical elements of the model. The disposable craniotomy pack incorporates 3D-printed sections of model skull and brain, as well as artificial dura that incorporates a model sagittal sinus. RESULTS Twelve participants at the 2015 Western Region Society of Neurological Surgeons postgraduate year 1 resident course ("boot camp") provided informed consent and enrolled in a study testing the prototype device. Each trainee was required to successfully create a bilateral parasagittal craniotomy, repair a dural sinus tear, and recognize and correct an air embolus. Participant stress was measured using a heart rate wrist monitor. After participation, each resident completed a 13-question categorical survey. CONCLUSIONS All trainee participants experienced tachycardia during the simulation, although the point in the simulation at which they experienced tachycardia varied. Survey results indicated that participants agreed the simulation was realistic, created stress, and was a useful tool in training neurosurgical residents. This simulator represents a novel, low-cost approach for hands-on training that effectively teaches and tests residents without risk of patient injury.

An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education

The traditional neurosurgical apprenticeship scheme includes the assessment of trainee’s manual skills carried out by experienced surgeons. However, the introduction of surgical simulation technology presents a new paradigm where residents can refine surgical techniques on a simulator before putting them into practice in real patients. Unfortunately, in this new scheme, an experienced surgeon will not always be available to evaluate trainee’s performance. For this reason, it is necessary to develop automatic mechanisms to estimate metrics for assessing manual dexterity in a quantitative way. Authors have proposed some hardware-software approaches to evaluate manual dexterity on surgical simulators. This paper presents IGlove, a wearable device that uses inertial sensors embedded on an elastic glove to capture hand movements. Metrics to assess manual dexterity are estimated from sensors signals using data processing and information analysis algorithms. It has been designed to be used with a neurosurgical simulator called Daubara NS Trainer, but can be easily adapted to another benchtop- and manikin-based medical simulators. The system was tested with a sample of 14 volunteers who performed a test that was designed to simultaneously evaluate their fine motor skills and the IGlove’s functionalities. Metrics obtained by each of the participants are presented as results in this work; it is also shown how these metrics are used to automatically evaluate the level of manual dexterity of each volunteer.

Simulation in pediatrics: Is it about time?

Pediatrics is a challenging field where “Time is Essence” and the interplay of time-bound dynamics has a huge influence on the outcomes, particularly in an acutely ill child. In this context, simulation based training appears to play a major role in training young Paediatricians to develop critical decision making skills and learning in a risk-free environment. In present times and in future, it is expected that simulation is used by practically every healthcare provider at some or multiple points in the training and certification process.

Endoscopic Management of Cavernous Carotid Surgical Complications: Evaluation of a Simulated Perfusion Model

OBJECTIVE

Endoscopic surgical treatment of pituitary tumors, lateral invading tumors, or aneurysms requires surgeons to operate adjacent to the cavernous sinus. During these endoscopic endonasal procedures, the carotid artery is vulnerable to surgical injury at its genu. The objective of this simulation model was to evaluate trainees regarding management of a potentially life-threatening vascular injury.

METHODS

Cadaveric heads were prepared in accordance with the Oregon Health & Science University body donation program. An endoscopic endonasal approach was used, and a perfusion pump with a catheter was placed in the ipsilateral common carotid artery at its origin in the neck. Learners used a muscle graft to establish vascular control and were evaluated over 3 training sessions. Simulation assessment, blood loss during sessions, and performance metric data were collected for learners.

RESULTS

Vascular control was obtained at a mean arterial pressure of 65 mm Hg using a muscle graft correctly positioned at the arteriotomy site. Learners improved over the course of training, with senior residents (n = 4) performing better across all simulation categories (situation awareness, decision making, communications and teamwork, and leadership); the largest mean difference was in communication and teamwork. Additionally, learner performance concerning blood loss improved between sessions (t = 3.667, P < 0.01).

CONCLUSIONS

In this pilot endoscopic endonasal simulation study, we successfully demonstrate a vascular complication perfusion model. Learners were able to gain direct applicable expertise in endoscopic endonasal techniques, instrumentation use, and teamwork required to optimize the technique. Learners gained skills of vascular complication management that transcend this model.

[Simulation in surgical training]

BACKGROUND

Patient safety during operations hinges on the surgeon's skills and abilities. However, surgical training has come under a variety of restrictions. To acquire dexterity with decreasingly "simple" cases, within the legislative time constraints and increasing expectations for surgical results is the future challenge.

OBJECTIVES

Are there alternatives to traditional master-apprentice learning?

MATERIALS AND METHODS

A literature review and analysis of the development, implementation, and evaluation of surgical simulation are presented.

RESULTS

Simulation, using a variety of methods, most important physical and virtual (computer-generated) models, provides a safe environment to practice basic and advanced skills without endangering patients. These environments have specific strengths and weaknesses.

CONCLUSIONS

Simulations can only serve to decrease the slope of learning curves, but cannot be a substitute for the real situation. Thus, they have to be an integral part of a comprehensive training curriculum. Our surgical societies have to take up that challenge to ensure the training of future generations.

Simulator-Based Angiography and Endovascular Neurosurgery Curriculum: A Longitudinal Evaluation of Performance Following Simulator-Based Angiography Training

This study establishes performance metrics for angiography and neuroendovascular surgery procedures based on longitudinal improvement in individual trainees with differing levels of training and experience.

Over the course of 30 days, five trainees performed 10 diagnostic angiograms, coiled 10 carotid terminus aneurysms in the setting of subarachnoid hemorrhage, and performed 10 left middle cerebral artery embolectomies on a Simbionix Angio Mentor™ simulator. All procedures were nonconsecutive. Total procedure time, fluoroscopy time, contrast dose, heart rate, blood pressures, medications administered, packing densities, the number of coils used, and the number of stent-retriever passes were recorded. Image quality was rated, and the absolute value of technically unsafe events was recorded. The trainees’ device selection, macrovascular access, microvascular access, clinical management, and the overall performance of the trainee was rated during each procedure based on a traditional Likert scale score of 1=fail, 2=poor, 3=satisfactory, 4=good, and 5=excellent. These ordinal values correspond with published assessment scales on surgical technique.

After performing five diagnostic angiograms and five embolectomies, all participants demonstrated marked decreases in procedure time, fluoroscopy doses, contrast doses, and adverse technical events; marked improvements in image quality, device selection, access scores, and overall technical performance were additionally observed (p < 0.05). Similarly, trainees demonstrated marked improvement in technical performance and clinical management after five coiling procedures (p < 0.05). However, trainees with less prior experience deploying coils continued to experience intra-procedural ruptures up to the eighth embolization procedure; this observation likely corresponded with less tactile procedural experience to an exertion of greater force than appropriate for coil placement.

Trainees across all levels of training and prior experience demonstrated a significant performance improvement after completion of our simulator curriculum consisting of five diagnostic angiograms, five embolectomy cases, and 10 aneurysm coil embolizations.