Performance Factors in Neurosurgical Simulation and Augmented Reality Image Guidance

Virtual reality surgical simulators have seen widespread adoption in an effort to provide safe, cost-effective and realistic practice of surgical skills. However, the majority of these simulators focus on training low-level technical skills, providing only prototypical surgical cases. For many complex procedures, this approach is deficient in representing anatomical variations that present clinically, failing to challenge users’ higher-level cognitive skills important for navigation and targeting. Surgical simulators offer the means to not only simulate any case conceivable, but to test novel approaches and examine factors that influence performance. Unfortunately, there is a void in the literature surrounding these questions. This thesis was motivated by the need to expand the role of surgical simulators to provide users with clinically relevant scenarios and evaluate human performance in relation to image guidance technologies, patient-specific anatomy, and cognitive abilities. To this end, various tools and methodologies were developed to examine cognitive abilities and knowledge, simulate procedures, and guide complex interventions all within a neurosurgical context. The first chapter provides an introduction to the material. The second chapter describes the development and evaluation of a virtual anatomical training and examination tool. The results suggest that learning occurs and that spatial reasoning ability is an important performance predictor, but subordinate to anatomical knowledge. The third chapter outlines development of automation tools to enable efficient simulation studies and data management. In the fourth chapter, subjects perform abstract targeting tasks on ellipsoid targets with and without augmented reality guidance. While the guidance tool improved accuracy, performance with the tool was strongly tied to target depth estimation – an important consideration for implementation and training with similar guidance tools. In the fifth chapter, neurosurgically experienced subjects were recruited to perform simulated ventriculostomies. Results showed anatomical variations influence performance and could impact outcome. Augmented reality guidance showed no marked improvement in performance, but exhibited a mild learning curve, indicating that additional training may be warranted. The final chapter summarizes the work presented. Our results and novel evaluative methodologies lay the groundwork for further investigation into simulators as versatile research tools to explore performance factors in simulated surgical procedures

Design and evaluation of an augmented reality simulator using leap motion

Advances in virtual and augmented reality (AR) are having an impact on the medical field in areas such as surgical simulation. Improvements to surgical simulation will provide students and residents with additional training and evaluation methods. This is particularly important for procedures such as the endoscopic third ventriculostomy (ETV), which residents perform regularly. Simulators such as NeuroTouch, have been designed to aid in training associated with this procedure. The authors have designed an affordable and easily accessible ETV simulator, and compare it with the existing NeuroTouch for its usability and training effectiveness. This simulator was developed using Unity, Vuforia and the leap motion (LM) for an AR environment. The participants, 16 novices and two expert neurosurgeons, were asked to complete 40 targeting tasks. Participants used the NeuroTouch tool or a virtual hand controlled by the LM to select the position and orientation for these tasks. The length of time to complete each task was recorded and the trajectory log files were used to calculate performance. The resulting data from the novices\u27 and experts\u27 speed and accuracy are compared, and they discuss the objective performance of training in terms of the speed and accuracy of targeting accuracy for each system

Virtual Reality in Neurosurgery- A Neurostimulator – Based Postgraduate Residency Training: A Novel Step Towards Skillful Young Neurosurgeons

Introduction/Objective:  Virtual Reality (VR) is the need of time in every field of life. Recent biotechnological advances have molded the surgeon-computer relationship. Department of Neurosurgery Jinnah Hospital Lahore has updated the postgraduate training program by adding the virtual reality simulator. We aim to explore the current and future roles and applications of VR and simulation in neurosurgical training that may reduce the learning curve, improve conceptual understanding and enhance visuospatial skills. Materials & Methods:  Eight residents were enrolled in this program. They exercised the basic skills of neurosurgery e.g. suction, use of bipolar cautery, handling of CUSA, use of micro scissors, etc., and the automated software recorded each participant’s graph of performance separately. After 1.5 years, they were assessed in real-time on actual patients under the direct supervision of a qualified neurosurgeon. The assessment was done on DOPS (Directly Observed Procedural Skills) Performa. Results:  The results showed that there was a gradual upward learning curve in simulator-based procedures from negative marking to 70% in basic surgical skills and 60% in advanced procedures on average for all the residents whereas the DOPS showed that all residents performed above expectation i.e., 4 or above. Conclusion:  Neurostimulator-based postgraduate training program is opening new horizons for the safe and skillful training of residents. With the advancement of artificial intelligence, its use in training programs will lead to structured and systematic training patterns in the world of neurosurgery

Virtual reality in neurosurgery- a neurostimulator – based postgraduate residency training: a novel step towards skillful young neurosurgeons

Introduction/Objective: Virtual Reality (VR) is the need of time in every field of life. Recent biotechnological advances have molded the surgeon-computer relationship. Department of Neurosurgery Jinnah Hospital Lahore has updated the postgraduate training program by adding the virtual reality simulator. We aim to explore the current and future roles and applications of VR and simulation in neurosurgical training that may reduce the learning curve, improve conceptual understanding and enhance visuospatial skills. Materials & Methods: Eight residents were enrolled in this program. They exercised the basic skills of neurosurgery e.g. suction, use of bipolar cautery, handling of CUSA, use of micro scissors, etc., and the automated software recorded each participant’s graph of performance separately. After 1.5 years, they were assessed in real-time on actual patients under the direct supervision of a qualified neurosurgeon. The assessment was done on DOPS (Directly Observed Procedural Skills) Performa. Results: The results showed that there was a gradual upward learning curve in simulator-based procedures from negative marking to 70% in basic surgical skills and 60% in advanced procedures on average for all the residents whereas the DOPS showed that all residents performed above expectation i.e., 4 or above. Conclusion: Neurostimulator-based postgraduate training program is opening new horizons for the safe and skillful training of residents. With the advancement of artificial intelligence, its use in training programs will lead to structured and systematic training patterns in the world of neurosurgery

Computerized Evaluatution of Microsurgery Skills Training

The style of imparting medical training has evolved, over the years. The traditional methods of teaching and practicing basic surgical skills under apprenticeship model, no longer occupy the first place in modern technically demanding advanced surgical disciplines like neurosurgery. Furthermore, the legal and ethical concerns for patient safety as well as cost-effectiveness have forced neurosurgeons to master the necessary microsurgical techniques to accomplish desired results. This has lead to increased emphasis on assessment of clinical and surgical techniques of the neurosurgeons. However, the subjective assessment of microsurgical techniques like micro-suturing under the apprenticeship model cannot be completely unbiased. A few initiatives using computer-based techniques, have been made to introduce objective evaluation of surgical skills. This thesis presents a novel approach involving computerized evaluation of different components of micro-suturing techniques, to eliminate the bias of subjective assessment. The work involved acquisition of cine clips of micro-suturing activity on synthetic material. Image processing and computer vision based techniques were then applied to these videos to assess different characteristics of micro-suturing viz. speed, dexterity and effectualness. In parallel subjective grading on these was done by a senior neurosurgeon. Further correlation and comparative study of both the assessments was done to analyze the efficacy of objective and subjective evaluation

Design and Evaluation of Neurosurgical Training Simulator

Surgical simulators are becoming more important in surgical training. Consumer smartphone technology has improved to allow deployment of VR applications and are now being targeted for medical training simulators. A surgical simulator has been designed using a smartphone, Google cardboard 3D glasses, and the Leap Motion (LM) hand controller. Two expert and 16 novice users were tasked with completing the same pointing tasks using both the LM and the medical simulator NeuroTouch. The novice users had an accuracy of 0.2717 bits (SD 0.3899) and the experts had an accuracy of 0.0925 bits (SD 0.1210) while using the NeuroTouch. Novices and experts improved their accuracy to 0.3585 bits (SD 0.4474) and 0.4581 bits (SD 0.3501) while using the LM. There were some tracking problems with the AR display and LM. Users were intrigued by the AR display and most preferred the LM, as they found it to have better usability

Augmented Reality Simulation Modules for EVD Placement Training and Planning Aids

When a novice neurosurgeon performs a psychomotor surgical task (e.g., tool navigation into brain structures), a potential risk of damaging healthy tissues and eloquent brain structures is unavoidable. When novices make multiple hits, thus a set of undesirable trajectories is created, and resulting in the potential for surgical complications. Thus, it is important that novices not only aim for a high-level of surgical mastery but also receive deliberate training in common neurosurgical procedures and underlying tasks. Surgical simulators have emerged as an adequate candidate as effective method to teach novices in safe and free-error training environments. The design of neurosurgical simulators requires a comprehensive approach to development and. In that in mind, we demonstrate a detailed case study in which two Augmented Reality (AR) training simulation modules were designed and implemented through the adoption of Model-driven Engineering. User performance evaluation is a key aspect of the surgical simulation validity. Many AR surgical simulators become obsolete; either they are not sufficient to support enough surgical scenarios, or they were validated according to subjective assessments that did not meet every need. Accordingly, we demonstrate the feasibility of the AR simulation modules through two user studies, objectively measuring novices’ performance based on quantitative metrics. Neurosurgical simulators are prone to perceptual distance underestimation. Few investigations were conducted for improving user depth perception in head-mounted display-based AR systems with perceptual motion cues. Consequently, we report our investigation’s results about whether or not head motion and perception motion cues had an influence on users’ performance