Development and Validation of a Mixed Reality Configuration of a Simulator for a Minimally Invasive Spine Surgery Using the Workspace of a Haptic Device and Simulator Users

Most surgical simulators leverage virtual or bench models to simulate reality. This study proposes and validates a method for workspace configuration of a surgical simulator which utilizes a haptic device for interaction with a virtual model and a bench model to provide additional tactile feedback based on planned surgical manoeuvers. Numerical analyses were completed to determine the workspace and position of a haptic device, relative to the bench model, used in the surgical simulator, and the determined configuration was validated using device limitations and user data from surgical and nonsurgical users. For the validation, surgeons performed an identical surgery on a cadaver prior to using the simulator, and their trajectories were then compared to the determined workspace for the haptic device. The configuration of the simulator was determined appropriate through workspace analysis and the collected user trajectories. Statistical analyses suggest differences in trajectories between the participating surgeons which were not affected by the imposed haptic workspace. This study, therefore, demonstrates a method to optimally position a haptic device with respect to a bench model while meeting the manoeuverability needs of a surgical procedure. The validation method identified workspace position and user trajectory towards ideal configuration of a mixed reality simulator.

Low-Cost, Low-Fidelity, Self-Made Arthroscopic Surgical Simulators: A Systematic Review

Purpose: To systematically review the literature regarding low-cost, low-fidelity, self-made arthroscopic surgical simulators and provide an overview of their use in the teaching of arthroscopic surgical skills. Methods: Systematic review of the literature following PRISMA (Preferred Reporting Items for Systematic Reviews and MetaAnalyses) guidelines. Results: A total of 10 studies met inclusion criteria. All studies utilized low-cost, low-fidelity, self-made arthroscopic simulators of varying designs. Five studies (50%) utilized low-cost, self-made arthroscopic cameras and three (30%) utilized commercial surgical arthroscopic cameras. One study (10%) demonstrated face validity, five (50%) demonstrated construct validity, and three (30%) demonstrated transfer validity. The assessed arthroscopic tasks varied, but generally consisted of a combination of triangulation, object grasping, and tissue manipulation. Seven (70%) studies evaluated total simulator construction costs, with six (60%) studies achieving total construction costs of < $80 US Dollars. Conclusions: A growing body of literature supports the use of low-cost, low-fidelity, self-made arthroscopic surgical simulators. The cost-effectiveness and practicality of these simulators remains a major benefit to their overall utility when compared to their commercially available and high-fidelity counterparts. Furthermore, studies utilizing low-fidelity arthroscopic simulators are beginning to place a large importance on the achievement of face, construct, and transfer validity. Evidence suggests that the true utility of low-cost, low-fidelity arthroscopic surgical simulators stem not from their ability to replicate operating room conditions, but rather from their ability to provide practical training in basic and essential arthroscopic skills that will then be further refined through possible additional simulation and future surgical training.

The Impact of the COVID-19 Pandemic on Ophthalmology Residents: A Narrative Review

The ongoing outbreak of the coronavirus disease 2019 (COVID-19) pandemic has drastically affected medical societies. We aim to provide an overview and summarize the information published so far concerning the impact of the COVID-19 pandemic on ophthalmology residency programs and the mental wellbeing of trainees, and to establish factors to help maintain successful residency training to ensure high-quality, specialist ophthalmic training. A literature search was conducted in October 2021 of the PubMed database for articles assessing the impact of the COVID-19 pandemic on the mental health of ophthalmology trainees and on ophthalmology residency programs. Cross-sectional survey studies, editorials, articles in scientific journals, letters to editors, and commentaries were considered; finally, 19 studies were included after excluding abstract-only publications and conference posters. The studies’ demographic details, participant characteristics, interventions, outcomes, and limitations were extracted. Our summarized information showed the alarmingly significant impact of the COVID-19 pandemic on ophthalmology trainees’ mental health and the associated considerable changes in ophthalmic training programs. Thus, in future, virtual training and surgical simulators should be permanently introduced, in addition to traditional teaching, to complete successful ophthalmology residency programs. Additionally, we emphasize the need for a widely facilitated and encouraged access to psychological support programs for healthcare workers, including ophthalmologists.

SP2.1.1Continuous Monitoring and Assessment of Surgical Technical Skills Using Deep Learning

Aims Excellent surgical technical skills are of paramount importance to perform surgical procedures, safely and efficiently. Virtual reality surgical simulators can both simulate real operations while providing standardized, risk-free surgical hands-on experience. The integration of AI (artificial intelligence) and virtual reality simulators provides opportunities to carry out comprehensive continuous assessments of surgical performance. We developed and tested a deep learning algorithm which can continuously monitor and assess surgical bimanual performance on virtual reality surgical simulators. Methods Fifty participants from four expertise levels (14 experts/neurosurgeons, 14 senior residents, 10 junior residents, 12 medical students) performed a simulated subpial tumor resection 5 times and a complex simulated brain tumor operation once on the NeuroVR platform. Participants were asked to remove the tumors completely while minimizing bleeding and damage to surrounding tissues employing a simulated ultrasonic aspirator and bipolar forceps. A deep neural network continually tracked the surgical performance utilizing 16 performance metrics generated every 0.2-seconds. Results The deep neural network was successfully trained using neurosurgeons and medical students’ data, learning the composites of expertise comparing high and lower skill levels. The trained algorithm was able to score the technical skills of individuals continuously at 0.2-second intervals. Statistically significant differences in average scores were identified between the 4 groups. Conclusions AI-powered surgical simulators provide continuous assessment of bimanual technical skills during surgery which may further define the composites necessary to train surgical expertise. To our knowledge, this is the first attempt in surgery to continuously assess surgical technical skills using deep learning.

Surgical Education in the 21st Century

Surgical education has evolved drastically since the 19th century. Previously education of surgical residents was limited to on job clinical training following the “see one, do one, teach one” model with knowledge gleaned from textbooks and journals. Presently a growing emphasis has been placed on both patient safety and resident well-being leading to a development of novel training paradigms. The textbook, while remaining a core source of knowledge, is now only one of many resources available to residents. Many residencies have their libraries online, making learning possible almost anywhere, even without physical books in hand. Most programs now incorporate education days where a structured curriculum allows for standardized education; this makes it less likely that residents miss out on mandatory concepts. The 2020 Covid-19 pandemic has led to further evolution of this model, making the classroom virtual yet interactive. Technology has allowed for residents to train on surgical simulators, so that laparoscopic and robotic skills may be practiced before application on a live patient. Altogether residents are afforded multiple ways to learn due to greater availability of time, structured educational modules, and technology.

242 Maintaining Surgical Training During the Covid-19 Pandemic; A Novel Use of Surgical Simulators

Introduction During Covid-19 pandemic, operation theatres limit the number of staff during each session, which causes a decrease in training opportunity. To counteract this lapse, the Orthopaedic Research Institute (ORI) designs an innovative training session. During the nationwide lockdown, the closure of the Institute allowed for the transfer of the VirtaMed ArthrosTM (VA), to our NHS facility. VA is a surgical simulator which enables the participant to practise knee arthroscopy. Method Participants with little arthroscopic experience were included in the study. Three fellowship-trained surgeons conducted daily teaching sessions. Participants were taught necessary arthroscopic skills before undertaking training modules on diagnostic arthroscopy. 90% of the participants attended the session at least three times. At the end of every module, VA generates a score based on parameters which include procedure duration, visualisation of key structures and iatrogenic chondral damage. Structure questionnaires were also used to analyse feedback. Results The overall confidence and module scores progress with each subsequent session. A keystone of success is the location and ease of access to the simulator. Conclusions Surgical simulators are a useful tool for surgical education and training. We should encourage their use in the future, especially in the UK surgical training programme.