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

Is it all about the money? : The effects of low and high cost simulator training scenarios in surgical training

Background: The learning process is complex and dependent on several factors such as for instance, the environment to learn, prior knowledge and distinct abilities, motivation, goal-orientation as well as the effects of instructor feedback. Medical education, in particular within surgical domains is imperative due to its influence on patient safety. The demand for training surgeons has shifted from the “master-apprentice/practice on patients”, towards a safer modality, involving simulators. The positive effects laparoscopic simulator training has on laparoscopic performance is extensive, as well as its impact on operating room performance. Nonetheless, the difference in learning effect using either low-cost or high-fidelity laparoscopic simulators were not totally clear prior to study start. Aims 1. To examine whether laparoscopic surgical training may be offered at a lower cost, with maintained equivalent level of training and effect in knowledge/learning using a low-cost laparoscopic Blackbox (Paper I). 2. To study the impact of PC-gaming experience, visuospatial ability and gender on the various parameters of the MIST-VR simulator and its effect on the score (Paper II). 3. To further investigate the Blackbox, and if different adjuncts (video analysis) could provide more information regarding the effects of training (Paper III). 4. To study the effects on time to learn laparoscopic knot- and suturing skills in novices using two different laparoscopic needle holders in a more advanced Blackbox, evaluate outcomes regarding performance, ergonomic discomfort and time to perform laparoscopic knot- and suturing skills, as well as to evaluate an objective video evaluation scoring table (OVEST) (Paper IV). Materials and Methods: The participants were medical students from the surgical semester at Karolinska Institutet, Stockholm (Studies I-III) and medical students at Athens University Medical School in Athens, Athens, Greece (Study IV). The studies were conducted at CAMST (Center for Advanced Medical Simulation and Training), Karolinska University Hospital, Stockholm (Studies I-III), and at MPLSC (Medical Physics-Lab Simulation Center), Athens University Medical School, Athens, Greece (Study IV). In conjunction with inclusion, the students (Studies I-II) performed a test (MRT-A; Mental Rotation Test – A) for the assessment of their visuospatial ability, and questionnaires including baseline questions (Studies I-IV). The simulator training/tests were done using different laparoscopic simulators; Blackbox (Studies I and III); LapMentor (Study I); MIST-VR (Studies I-III); Simball box (Study IV). The participants’ simulator performance analyzed; time to completion and economy of movement (Studies I-IV); optical flow metrics (path-length and total number of particles) as displayed by the automated video analysis software (Study III); knot- and suturing skills (Study IV). Results: Studies I and II showed, as previous studies, that the visuospatial ability correlated with the initial simulator training sessions. Study I showed no significant difference in performance between laparoscopic basic skills training regardless of simulator used; low-cost or high-fidelity laparoscopy simulator. Studies I, II and III showed discrepancies between prior PC-gaming experience and the simulator performance, as well as some gender-specific differences. Study III also showed that the use of a low-cost automated video analysis software may be feasibly comparable to the build-in software of the MIST-VR simulator. Study IV presented a shortened time to learn for novices performing laparoscopic knot- and suturing tasks in a simulated environment when using the newly designed laparoscopic needle holder compared to a conventional market needle holder. Conclusions: Laparoscopic simulator training clearly facilitates laparoscopic skills performance. Improved prerequisites of training opportunities for surgeons could potentiate patient safety, especially since enhanced surgical performance improves patient safety. Subsequently, as depicted in this thesis, there is not one single truth or solution, rather different angles and several factors that affect learning in general and surgical performance in particular. Therefore, considerations of for instance individual differences, gender, and motivation, should all be included when producing laparoscopic skills training curriculum for future surgical trainees

A Virtual University Infrastructure For Orthopaedic Surgical Training With Integrated Simulation

This thesis pivots around the fulcrum of surgical, educational and technological factors. Whilst there is no single conclusion drawn, it is a multidisciplinary thesis exploring the juxtaposition of different academic domains that have a significant influence upon each other. The relationship centres on the engineering and computer science factors in learning technologies for surgery. Following a brief introduction to previous efforts developing surgical simulation, this thesis considers education and learning in orthopaedics, the design and building of a simulator for shoulder surgery. The thesis considers the assessment of such tools and embedding into a virtual learning environment. It explains how the performed experiments clarified issues and their actual significance. This leads to discussion of the work and conclusions are drawn regarding the progress of integration of distributed simulation within the healthcare environment, suggesting how future work can proceed

Virtual Reality Simulator for Training in Myringotomy with Tube Placement

Myringotomy refers to a surgical incision in the eardrum, and it is often followed by ventilation tube placement to treat middle-ear infections. The procedure is difficult to learn; hence, the objectives of this work were to develop a virtual-reality training simulator, assess its face and content validity, and implement quantitative performance metrics and assess construct validity. A commercial digital gaming engine (Unity3D) was used to implement the simulator with support for 3D visualization of digital ear models and support for major surgical tasks. A haptic arm co-located with the stereo scene was used to manipulate virtual surgical tools and to provide force feedback. A questionnaire was developed with 14 face validity questions focusing on realism and 6 content validity questions focusing on training potential. Twelve participants from the Department of Otolaryngology were recruited for the study. Responses to 12 of the 14 face validity questions were positive. One concern was with contact modeling related to tube insertion into the eardrum, and the second was with movement of the blade and forceps. The former could be resolved by using a higher resolution digital model for the eardrum to improve contact localization. The latter could be resolved by using a higher fidelity haptic device. With regard to content validity, 64% of the responses were positive, 21% were neutral, and 15% were negative. In the final phase of this work, automated performance metrics were programmed and a construct validity study was conducted with 11 participants: 4 senior Otolaryngology consultants and 7 junior Otolaryngology residents. Each participant performed 10 procedures on the simulator and metrics were automatically collected. Senior Otolaryngologists took significantly less time to completion compared to junior residents. Junior residents had 2.8 times more errors as compared to experienced surgeons. The senior surgeons also had significantly longer incision lengths, more accurate incision angles, and lower magnification keeping both the umbo and annulus in view. All metrics were able to discriminate senior Otolaryngologists from junior residents with a significance of p \u3c 0.002. The simulator has sufficient realism, training potential and performance discrimination ability to warrant a more resource intensive skills transference study

Development of a Suturing Simulation Device for Synchronous Acqusition of Data

There have been tremendous technological advancements in the field of surgery with new devices and minimally invasive techniques rapidly being developed. As a result, there is a corresponding need to train novice surgeons and residents to use these new technologies. Due to new regulations in medical education, an increasing the amount of surgical skills training is designed for outside the operation room using surgical simulators. In this work, a device called the suture platform was conceptualized for assessing and training basic suturing skills of medical students and novice surgeons. In the traditional approach of “open” surgery, which has not benefitted as much from simulation, suturing is one of the most foundational surgical maneuvers. The specific task developed on the suture platform is called radial suturing and was prescribed by expert surgeons as one of five core “open” vascular skills. In the initial phase of the platform development, a six-axis force sensor was used to obtain data on the device and the procedure was video-recorded for analysis. Pilot data was analyzed using force-based parameters (e.g. peak force) and temporal parameters with the goal of examining if experts were distinguished from novices. During analysis, it became apparent that future development of the device should focus on obtaining synchronized data from video and other sensors. In the next phase of development, a motion sensor was added to capture wrist motion of the trainee and to obtain richer information of the suturing process. The current system consists of a graphical user interface (GUI) that captures data during a radial suturing task that can be analyzed using force, motion and vision metrics to assess and inform surgical suturing skill training

Entering a new era of surgical training : developing 3-dimensional print models for hands-on surgical training and its introduction into the congenital cardiac surgical curriculum

Congenital heart surgery is a technically challenging subspecialty of cardiothoracic surgery. This is due to a combination of factors including the rarity and variety of pathology and the small patient size. This coupled with the increasing public scrutiny and the expectation of excellent patient outcomes for even the most complex pathologies has led to limitations for surgical trainees to develop their surgical competencies in an efficient manner. Simulation has been used successfully to develop technical skills in other surgical specialities but is limited in congenital heart surgery. The objectives of this work were to develop and integrate hands-on simulation methods into the training of congenital heart surgeons using anatomically accurate 3D-printed heart models and to use validated, objective assessment methods to measure performance. The simulation programme was successfully developed and integrated into the regular training of congenital heart surgeons. The objective assessments demonstrated that there was an improvement in procedural performance and time across multiple complex procedures following deliberate practice and rehearsal. Furthermore, surgeons who had participated in the programme retained their technical skills following a prolonged delay supporting the value of simulation. Overall, there is value in the incorporation of hands-on simulation training into congenital heart surgery and it has the potential to be integrated into training programmes globally

A Survey on the Current Status and Future Challenges Towards Objective Skills Assessment in Endovascular Surgery

Minimally-invasive endovascular interventions have evolved rapidly over the past decade, facilitated by breakthroughs in medical imaging and sensing, instrumentation and most recently robotics. Catheter based operations are potentially safer and applicable to a wider patient population due to the reduced comorbidity. As a result endovascular surgery has become the preferred treatment option for conditions previously treated with open surgery and as such the number of patients undergoing endovascular interventions is increasing every year. This fact coupled with a proclivity for reduced working hours, results in a requirement for efficient training and assessment of new surgeons, that deviates from the “see one, do one, teach one” model introduced by William Halsted, so that trainees obtain operational expertise in a shorter period. Developing more objective assessment tools based on quantitative metrics is now a recognised need in interventional training and this manuscript reports the current literature for endovascular skills assessment and the associated emerging technologies. A systematic search was performed on PubMed (MEDLINE), Google Scholar, IEEXplore and known journals using the keywords, “endovascular surgery”, “surgical skills”, “endovascular skills”, “surgical training endovascular” and “catheter skills”. Focusing explicitly on endovascular surgical skills, we group related works into three categories based on the metrics used; structured scales and checklists, simulation-based and motion-based metrics. This review highlights the key findings in each category and also provides suggestions for new research opportunities towards fully objective and automated surgical assessment solutions

Robot-Assisted Minimally Invasive Surgical Skill Assessment—Manual and Automated Platforms

The practice of Robot-Assisted Minimally Invasive Surgery (RAMIS) requires extensive skills from the human surgeons due to the special input device control, such as moving the surgical instruments, use of buttons, knobs, foot pedals and so. The global popularity of RAMIS created the need to objectively assess surgical skills, not just for quality assurance reasons, but for training feedback as well. Nowadays, there is still no routine surgical skill assessment happening during RAMIS training and education in the clinical practice. In this paper, a review of the manual and automated RAMIS skill assessment techniques is provided, focusing on their general applicability, robustness and clinical relevance

Research on real-time physics-based deformation for haptic-enabled medical simulation

This study developed a multiple effective visuo-haptic surgical engine to handle a variety of surgical manipulations in real-time. Soft tissue models are based on biomechanical experiment and continuum mechanics for greater accuracy. Such models will increase the realism of future training systems and the VR/AR/MR implementations for the operating room

AUTOMATIC PERFORMANCE LEVEL ASSESSMENT IN MINIMALLY INVASIVE SURGERY USING COORDINATED SENSORS AND COMPOSITE METRICS

Skills assessment in Minimally Invasive Surgery (MIS) has been a challenge for training centers for a long time. The emerging maturity of camera-based systems has the potential to transform problems into solutions in many different areas, including MIS. The current evaluation techniques for assessing the performance of surgeons and trainees are direct observation, global assessments, and checklists. These techniques are mostly subjective and can, therefore, involve a margin of bias. The current automated approaches are all implemented using mechanical or electromagnetic sensors, which suffer limitations and influence the surgeon’s motion. Thus, evaluating the skills of the MIS surgeons and trainees objectively has become an increasing concern. In this work, we integrate and coordinate multiple camera sensors to assess the performance of MIS trainees and surgeons. This study aims at developing an objective data-driven assessment that takes advantage of multiple coordinated sensors. The technical framework for the study is a synchronized network of sensors that captures large sets of measures from the training environment. The measures are then, processed to produce a reliable set of individual and composed metrics, coordinated in time, that suggest patterns of skill development. The sensors are non-invasive, real-time, and coordinated over many cues such as, eye movement, external shots of body and instruments, and internal shots of the operative field. The platform is validated by a case study of 17 subjects and 70 sessions. The results show that the platform output is highly accurate and reliable in detecting patterns of skills development and predicting the skill level of the trainees