Virtual Reality Surgical Simulator Research Articles

Development and validation of an objective virtual reality tool for assessing technical aptitude among potential candidates for surgical training

BackgroundGood technical skills are crucial for surgeons. Yet although surgical training programs strive to assess technical aptitude when selecting surgical residents, valid assessments of such aptitude are still lacking. Surgical simulators have been proposed as a potentially effective tool for this purpose. The current study aims to develop a technical aptitude test using a virtual reality surgical simulator, and to validate its use for the selection of surgical residents.MethodsThe study had three phases. In Phase 1, we developed an initial version of the technical aptitude test using the Lap-X-VR laparoscopic simulator. In Phases 2 and 3 we refined the test and collected empirical data to evaluate four main sources of validity evidence (content, response process, internal structure, and relationships with other variables), and to evaluate the feasibility and acceptability of the test. Specifically, Phase 2 comprised a review of the test by 30 senior surgeons, and in Phase 3 a revised version of the test was administered to 152 interns to determine its psychometric properties.ResultsBoth the surgeons and interns rated the test as highly relevant for selecting surgical residents. Analyses of the data obtained from the trial administration of the test supported the appropriateness of the score calculation process and showed good psychometric properties, including reliability (α = 0.83) and task discrimination (mean discrimination = 0.5, SD = 0.1). The correlations between test scores and background variables revealed significant correlations with gender, surgical simulator experience, and video game experience (ps < 0.001). These variables, however, explained together only 10% of the variance in test scores.ConclusionsWe describe the systematic development of an innovative virtual reality test for assessing technical aptitude in candidates for surgical training, and present evidence for its validity, feasibility and acceptability. Further validation is required to support the application of the test for selection, as well as to discern the impact of gender, surgical simulator experience, and video game experience on the fairness of test results. However, the test appears to be a promising tool that may help training programs assess the suitability of candidates for surgical training.

Virtual Reality Surgical Simulations Using Fusion Three-Dimensional Images

In this section, we defined virtual reality(VR)surgical simulations using fusion three-dimensional(3D)images, which are 3D images created by fusing multiple medical image data. The more detailed the fusion of 3D images, the more knowledge and effort are required. In addition, 3D fusion images vary greatly with each case and depend on the skill and orientation of the image creator and the image processing software used. Some creators produce a fused 3D image with ample details to simulate tissue deformation, whereas others are limited to rough observations and use two-dimensional cross-sectional images for detailed anatomical information. Thus, there is no gold standard for creating fused 3D images or VR surgical simulations. Therefore, it is important to clarify the objective of a VR surgical simulation. An understanding of image-processing technology is useful in terms of software selection and image-processing efficiency. This section outlines the construction of fused 3D images and the use of VR surgical simulations based on actual clinical applications.

Effectiveness of the Eyesi Surgical Simulator for ophthalmology trainees: systematic review and meta-analysis

ObjectifLe simulateur chirurgical Eyesi (VRmagic, Mannheim, Allemagne) est le simulateur de réalité virtuelle le plus souvent utilisé en chirurgie ophtalmologique. Si des études ont révélé que des outils de formation fondés sur la simulation améliorent l'acquisition des compétences, aucune revue de synthèse systématique avec méta-analyse n'a encore été réalisée à l’égard du simulateur chirurgical Eyesi. Notre étude visait donc à effectuer une méta-analyse des études qui comparaient le simulateur chirurgical Eyesi à d'autres méthodes d'enseignement des compétences techniques auprès d’étudiants. MéthodesNotre recherche a porté sur 3 bases de données (MEDLINE, Embase et CENTRAL). Les articles inclus comparaient le simulateur chirurgical Eyesi à d'autres formes d'enseignement des compétences techniques auprès d’étudiants et de résidents dans des facultés de médecine. On a réalisé une méta-analyse par paire qui reposait sur l'inverse de la variance à effets aléatoires. Les différences moyennes standardisées (DMS) ont servi de principal paramètre de mesure afin de tenir compte des différences entre les outils d’évaluation des compétences chirurgicales. RésultatsDes 207 citations évaluées, on a retenu 8 études, totalisant 108 étudiants qui ont eu recours au simulateur chirurgical Eyesi et de 123 étudiants qui ont utilisé une autre forme d'apprentissage. L'amélioration des scores de compétences techniques était significativement supérieure dans le groupe Eyesi (3 études; DMS = 2,02; intervalle de confiance [IC] à 95 % : 1,47–2,57; p < 0,001; I2 = 0 %). On a noté une baisse significative du nombre d’étudiants du groupe Eyesi qui ont fait des erreurs techniques après leur formation (5 études : rapport de cotes = 0,43; IC à 95 % : 0,20–0,90; p = 0,03; I2 = 30 %). Aucune différence significative n'a été enregistrée entre les groupes en ce qui a trait au temps consacré pour exécuter une tâche après la formation (3 études; DMS = 1,96; IC à 95 % : –1,96–5,88; p = 0,33; I2 = 97 %). ConclusionsLe simulateur chirurgical Eyesi pourrait améliorer l'acquisition des compétences techniques (faible degré de certitude des données probantes) et réduire le nombre d'erreurs techniques (très faible degré de certitude des données probantes) lors de l'apprentissage de la chirurgie de la cataracte chez des étudiants. Il y a donc lieu de réaliser d'autres études prospectives sur le module Eyesi qui comporteraient un système de notation standardisée.

Examining impact forces during posterior spinal fusion to implement in a novel physics-driven virtual reality surgical simulator.

This study aims to understand the impact forces that surgeons apply to the human spine during a posterior spinal fusion procedure towards the development of a novel spine surgical simulator for training medical residents. The foci of this study are impact forces during graft placement and spinal interbody cage insertion. This study examined the lumbar intervertebral discs of two male cadaveric specimens. Impact forces were collected during graft and spinal cage insertion over multiple levels. An impulse hammer and a camera were used to collect impact forces and displacements, respectively. The results demonstrated a logarithmic relationship between impact forces and cumulative displacement during graft placement. This was also observed between cumulative displacement and number of impacts during spinal cage insertion. A linear relationship was observed for the impact forces and number of impacts during graft placement. Results suggest that surgeons rely on the feedback experienced from impact forces during graft insertion to gauge the amount of graft that was placed in a specific area of the disc. Impact forces during cage insertion provide information about any encountered obstacles. When developing surgical simulators, designing the force feedback system should require modelling these behaviors to effectively impart corresponding skills on a trainee.

Understanding the safe application of electrosurgery: A cross sectional study of surgeons in KSA

ObjectivesTo determine whether surgeons at different levels and in different specialties are aware of the safe and acceptable use of electrosurgery. In addition, we aimed to provide a fundamental understanding of electrosurgery and surgical diathermy. Materials and MethodsA total of 83 doctors from different specialties were randomly selected from several hospitals across KSA. The participants answered a questionnaire featuring 16 questions that addressed 10 domain questions regarding the safe use of electrosurgery. ResultsAnalysis revealed that the respondents either lacked knowledge or were unfamiliar with the use and safety of monopolar and bipolar electrosurgery in terms of application. Some respondents were unable to distinguish between the two protocols; this may have resulted in injuries being incurred by patients under their supervision. ConclusionsElectrosurgery should be formally included in specialty surgical Saudi hospital training programs to increase electrosurgery expertise and surgeons should be re-tested periodically. Our findings may be used to drive future learning. Surgeons may improve their electrosurgery skills by progressing along their learning curve to reach their peak. In addition, surgeons can use virtual reality surgical simulators to practice fundamental and sophisticated electrosurgery skills.

Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task

Virtual reality surgical simulators have facilitated surgical education by providing a safe training environment. Electroencephalography (EEG) has been employed to assess neuroelectric activity during surgical performance. Machine learning (ML) has been applied to analyze EEG data split into frequency bands. Although EEG is widely used in fields requiring expert performance, it has yet been used to classify surgical expertise. Thus, the goals of this study were to (a) develop an ML model to accurately differentiate skilled and less-skilled performance using EEG data recorded during a simulated surgery, (b) explore the relative importance of each EEG bandwidth to expertise, and (c) analyze differences in EEG band powers between skilled and less-skilled individuals. We hypothesized that EEG recordings during a virtual reality surgery task would accurately predict the expertise level of the participant. Twenty-one participants performed three simulated brain tumor resection procedures on the NeuroVR™ platform (CAE Healthcare, Montreal, Canada) while EEG data was recorded. Participants were divided into 2 groups. The skilled group was composed of five neurosurgeons and five senior neurosurgical residents (PGY4-6), and the less-skilled group was composed of six junior residents (PGY1-3) and five medical students. A total of 13 metrics from EEG frequency bands and ratios (e.g., alpha, theta/beta ratio) were generated. Seven ML model types were trained using EEG activity to differentiate between skilled and less-skilled groups. The artificial neural network achieved the highest testing accuracy of 100% (AUROC = 1.0). Model interpretation via Shapley analysis identified low alpha (8–10 Hz) as the most important metric for classifying expertise. Skilled surgeons displayed higher (p = 0.044) low-alpha than the less-skilled group. Furthermore, skilled surgeons displayed significantly lower TBR (p = 0.048) and significantly higher beta (13–30 Hz, p = 0.049), beta 1 (15–18 Hz, p = 0.014), and beta 2 (19–22 Hz, p = 0.015), thus establishing these metrics as important markers of expertise. ACGME Core CompetenciesPractice-Based Learning and Improvement.

The Role of Technology in Ophthalmic Surgical Education During COVID-19.

To describe the effect of COVID-19 on ophthalmic training programs and to review the various roles of technology in ophthalmology surgical education including virtual platforms, novel remote learning curricula, and the use of surgical simulators. COVID-19 caused significant disruption to in-person clinical and surgical patient encounters. Ophthalmology trainees worldwide faced surgical training challenges due to social distancing restrictions, trainee redeployment, and reduction in surgical case volume. Virtual platforms, such as Zoom and Microsoft Teams, were widely used during the pandemic to conduct remote teaching sessions. Novel virtual wet lab and dry lab curricula were developed. Training programs found utility in virtual reality surgical simulators, such as the Eyesi, to substitute experience lost from live patient surgical cases. Although several of these described technologies were incorporated into ophthalmology surgical training programs prior to COVID-19, the pandemic highlighted the importance of developing a formal surgical curriculum that can be delivered virtually. Novel telementoring, collaboration between training institutions, and hybrid formats of didactic and practical training sessions should be continued. Future research should investigate the utility of augmented reality and artificial intelligence for trainee learning.

IMPLICATIONS AND PERCEPTION OF PLASTINATION AMONG MEDICAL UNDERGRADUATES: A BRIEF REVIEW.

The medical students of the newer generation are more enthusiastic and explorers when it comes to acquiring knowledge, especially through the world wide web (www) &amp; multi-media. In an attempt to increase their motivation and enhance anatomy learning various methodologies have been introduced in recent years like problem-based learning, virtual reality surgical simulators, and computer-based learning methods. One such innovative technique is Plastination. Plastinates have become one of the revolutionary innovations in anatomical education and has become an ideal tutoring tool in other elds also like pathology, obstetrics, radiology and surgery. The plastinates are very powerful learning tools as they are very durable and help in gaining anatomical knowledge and strengthen individual capacities for medical scholars exercising a wider variety of learning strategies. This review is intended to survey the utility of these plastinates among the medical undergraduates and to identify their efcacy compared to the dissected wet specimens for gaining anatomy knowledge. The results of this review reveal that the plastinates can only act as adjuncts for learning anatomy and that the medical undergraduates still prefer the traditional method of learning with gross dissected and prosected specimens to gain anatomy knowledge in most of the medical schools

Effects of Sleep Deprivation, Non-Dominant Hand Employment, Caffeine and Alcohol Intake During Surgical Performance: Lessons Learned From the Retina Eyesi Virtual Reality Surgical Simulator.

PurposeDetermine whether real-life surgical experience correlates with scores on a retina virtual simulator and the effects of various challenges on surgical performance.MethodsThe study was performed using the Eyesi Surgical Simulator, a virtual reality retina surgical simulator. Residents, fellows, and retina staff were assessed on surgical simulations to determine surgical skills. Participants were assigned baseline scores on speed, efficiency of movement, and ability to avoid retinal damage. After receiving their baseline scores, participants were challenged to use their non-dominant hand or to use the simulator after sleep deprivation or the intake of caffeine or alcohol.ResultsAt baseline, junior residents had an average score of 943; senior residents, 1045; retina fellows, 1153; and surgical retina staff, 1161. A 12.5% overall improvement in scores was achieved when comparing baseline 1 to baseline 2; a major improvement was recorded in residents (14.5%) compared with fellows and retina staff (9.97%). A statistically significant difference was observed between residents and fellows (P = 0.027), as well as between residents and retina staff (P = 0.04). A significant decrease in performance (15.7%) was observed when the non-dominant hand was used (P = 0.043). Performance after sleep deprivation and alcohol intake decreased, but not with a statistically significant difference (P = 0.6 and P = 0.5, respectively). A trend toward increasing performance was observed after caffeine intake (6.1%; P = 0.06).ConclusionsThe retina virtual simulator is a novel teaching tool for retinal surgery. A significant association was observed between real surgical experience and the retina surgery virtual simulator results based on surgical experience.Translational RelevanceAn association between real surgical experience and retina surgery virtual simulator results was demonstrated. A complete training program with a cut-off threshold score should be validated for retina training programs.

The user experience design of a novel microscope within SurgiSim, a virtual reality surgical simulator.

PurposeVirtual reality (VR) simulation has the potential to advance surgical education, procedural planning, and intraoperative guidance. “SurgiSim” is a VR platform developed for the rehearsal of complex procedures using patient-specific anatomy, high-fidelity stereoscopic graphics, and haptic feedback. SurgiSim is the first VR simulator to include a virtual operating room microscope. We describe the process of designing and refining the VR microscope user experience (UX) and user interaction (UI) to optimize surgical rehearsal and education.MethodsHuman-centered VR design principles were applied in the design of the SurgiSim microscope to optimize the user’s sense of presence. Throughout the UX’s development, the team of developers met regularly with surgeons to gather end-user feedback. Supplemental testing was performed on four participants.ResultsThrough observation and participant feedback, we made iterative design upgrades to the SurgiSim platform. We identified the following key characteristics of the VR microscope UI: overall appearance, hand controller interface, and microscope movement.ConclusionOur design process identified challenges arising from the disparity between VR and physical environments that pertain to microscope education and deployment. These roadblocks were addressed using creative solutions. Future studies will investigate the efficacy of VR surgical microscope training on real-world microscope skills as assessed by validated performance metrics.

Assessing the attitude of surgical trainees towards virtual reality simulation: A national cross-sectional questionnaire study.

We performed a cross sectional study to determine the attitudes of surgical trainees and medical students towards virtual reality (VR) simulation in surgical training. A survey was devised through an iterative process before distribution to surgical trainees, foundation year doctors and medical students through online platforms. The survey was disseminated within the United Kingdom through social media and email correspondence, in co-operation with national surgical organisations. 91 trainees responded from a variety of clinical specialities. VR technology in surgical training was viewed positively, with 91.3% of trainees agreeing that VR should be both an adjunct in surgical training as well as a competency-based assessment tool. Barriers to access were present, with access notably more challenging for senior surgeons. Virtual reality surgical simulation in surgical training is beginning to emerge as a genuine high-fidelity, low-risk solution to the lack of surgical case volume trainees are currently experiencing.

Can virtual reality surgical simulator improve the function of the non-dominant hand in ophthalmic surgeons?

Purpose:Phacoemulsification surgery requires the use of both hands; however, some surgeons may not be comfortable using their non-dominant hand, especially in critical steps such as chopping. This work aims at assessing whether a virtual reality simulator can help cataract surgeons train their non-dominant hand using the capsulorhexis module.Methods:This was a prospective observational study including thirty ophthalmic surgeons; none of them had previous training on the EyeSi surgical simulator. Twenty-three were experienced, and seven were intermediate surgeons. Surgeons were asked to perform capsulorhexis three times using their dominant hand and then using their non-dominant hand. A performance score based on efficiency, target achievement, instrument handling, and tissue treatment was calculated by the simulator.Results:A significant improvement in the score of surgeons using their non-dominant hand from the first trial (69.57 ± 18.9) to the third trial (84.9 ± 9.2) (P < 0.001) was found, whereas such improvement was not noted with the dominant hand (P = 0.12). Twenty-six surgeons managed to reach 90% of the mean score achieved by dominant hand by using their non-dominant hand, 11 (36.7%) from the first trial, seven (23.3%) from the second, and eight (26.7%) from the third.Conclusion:Cataract surgeons showed significant improvement in the scores of their non-dominant hands with simulator training. Thus, it is possible to safely train non-dominant hands for difficult tasks away from the operating room, which would be a fruitful addition to residency training programs.

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

Virtual reality surgical simulators provide detailed psychomotor performance data, allowing qualitative and quantitative assessment of hand function. The nondominant hand plays an essential role in neurosurgery in exposing the operative area, assisting the dominant hand to optimize task execution, and hemostasis. Outlining expert-level nondominant hand skills may be critical to understand surgical expertise and aid learner training. To (1) provide validity for the simulated bimanual subpial tumor resection task and (2) to use this simulation in qualitative and quantitative evaluation of nondominant hand skills for bipolar forceps utilization. In this case series study, 45 right-handed participants performed a simulated subpial tumor resection using simulated bipolar forceps in the nondominant hand for assisting the surgery and hemostasis. A 10-item questionnaire was used to assess task validity. The nondominant hand skills across 4 expertise levels (neurosurgeons, senior trainees, junior trainees, and medical students) were analyzed by 2 visual models and performance metrics. Neurosurgeon median (range) overall satisfaction with the simulated scenario was 4.0/5.0 (2.0-5.0). The visual models demonstrated a decrease in high force application areas on pial surface with increased expertise level. Bipolar-pia mater interactions were more focused around the tumoral region for neurosurgeons and senior trainees. These groups spent more time using the bipolar while interacting with pia. All groups spent significantly higher time in the left upper pial quadrant than other quadrants. This work introduces new approaches for the evaluation of nondominant hand skills which may help surgical trainees by providing both qualitative and quantitative feedback.

Quality improvement: understanding the adoption and diffusion of digital technologies related to surgical performance

PurposeQuantifying the performance level of surgeons with digital virtual reality (VR) simulators can help ensure that quality requirements in healthcare are met. In order to better understand integration amongst quality principles, practices and technologies in the adoption and diffusion of VR simulators, the authors applied a technological innovation system (TIS) framework. The purpose of this study is to understand how the adoption and diffusion of VR surgical simulators in a Swedish healthcare context is influenced by various system factors.Design/methodology/approachIn this study, single-case holistic design based on innovation system theory was used to analyse the adoption of digital quality technologies related to surgical performance in Swedish hospitals. The case employs a mixed methods approach triangulating data longitudinally from published documents and expert interviews.FindingsAdoption of digital technologies regarding surgical performance is restricted by system factors relating to inconsistent normative and regulatory requirements for quantified performance criteria to judge surgical expertise. Addressing these systems' weaknesses with evidence-based training programmes can have a significant impact on the further development of the innovation system and can ultimately affect healthcare reliability and quality.Originality/valueThis paper explores quality management (QM) challenges in the context of digital transformation in healthcare. The paper attempts to fill the gap for TIS studies in a healthcare context and highlight the role of innovation function strength along the value chain and in relation to technology cycles to increase the understanding of adoption of digital technologies relating to surgical performance.

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

Abstract 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.

Emerging artificial intelligence applications in otological imaging.

To highlight the recent literature on artificial intelligence (AI) pertaining to otological imaging and to discuss future directions, obstacles and opportunities. The main themes in the recent literature centre around automated otoscopic image diagnosis and automated image segmentation for application in virtual reality surgical simulation and planning. Other applications that have been studied include identification of tinnitus MRI biomarkers, facial palsy analysis, intraoperative augmented reality systems, vertigo diagnosis and endolymphatic hydrops ratio calculation in Meniere's disease. Studies are presently at a preclinical, proof-of-concept stage. The recent literature on AI in otological imaging is promising and demonstrates the future potential of this technology in automating certain imaging tasks in a healthcare environment of ever-increasing demand and workload. Some studies have shown equivalence or superiority of the algorithm over physicians, albeit in narrowly defined realms. Future challenges in developing this technology include the compilation of large high quality annotated datasets, fostering strong collaborations between the health and technology sectors, testing the technology within real-world clinical pathways and bolstering trust among patients and physicians in this new method of delivering healthcare.

Utilizing a multilayer perceptron artificial neural network to assess a virtual reality surgical procedure.

Virtual reality surgical simulators are a safe and efficient technology for the assessment and training of surgical skills. Simulators allow trainees to improve specific surgical techniques in risk-free environments. Recently, machine learning has been coupled to simulators to classify performance. However, most studies fail to extract meaningful observations behind the classifications and the impact of specific surgical metrics on the performance. One benefit from integrating machine learning algorithms, such as Artificial Neural Networks, to simulators is the ability to extract novel insights into the composites of the surgical performance that differentiate levels of expertise. This study aims to demonstrate the benefits of artificial neural network algorithms in assessing and analyzing virtual surgical performances. This study applies the algorithm on a virtual reality simulated annulus incision task during an anterior cervical discectomy and fusion scenario. An artificial neural network algorithm was developed and integrated. Participants performed the simulated surgical procedure on the Sim-Ortho simulator. Data extracted from the annulus incision task were extracted to generate 157 surgical performance metrics that spanned three categories (motion, safety, and efficiency). Musculoskeletal Biomechanics Research Lab; Neurosurgical Simulation and Artificial Intelligence Learning Center, McGill University, Montreal, Canada. Twenty-three participants were recruited and divided into 3 groups: 11 post-residents, 5 senior and 7 junior residents. An artificial neural network model was trained on nine selected surgical metrics, spanning all three categories and achieved 80% testing accuracy. This study outlines the benefits of integrating artificial neural networks to virtual reality surgical simulators in understanding composites of expertise performance.

Extended-Reality Technologies: An Overview of Emerging Applications in Medical Education and Clinical Care.

Extended-Reality Technologies: An Overview of Emerging Applications in Medical Education and Clinical Care.

AB206. SOH21AS030. Virtual reality operative simulation in orthopaedic surgical training during periods of restricted clinical hours: systematic review

Background: The public health response to the coronavirus pandemic has imposed limitations upon orthopaedic surgeon’s scheduled care practice, with a consequential diminution of training time for residents within the specialty. A potentially viable option for maintenance of operative competency is the use of virtual reality (VR) surgical simulation. This review looks at the effectiveness of (VR) as a pedagogical method of learning for orthopaedic trainees. Question: Can VR be a viable method of learning and skill retention for orthopaedic trainees during periods of diminished operative time?

Comparisons of orthodontic residents' performance and attitudes using 2D, 3D, and virtual reality surgical simulation methods.

Advances in virtual reality technology for surgical simulation methods may improve diagnosis and treatment planning of complex orthognathic surgery cases. The objectives were to assess orthodontic residents' performance and attitudes when treatment planning orthognathic surgery cases using two-dimensional (2D) digital, three-dimensional (3D) digital, and virtual reality (VR) surgical simulations. The study had a mixed methods study design involving 20 graduate orthodontic residents. Their previous experiences, confidence, and competence with orthodontic diagnosis and surgical treatment planning were assessed with a baseline survey. Each resident completed 2D, 3D, and VR treatment planning and simulation tasks in a randomized order and recorded their diagnosis, objectives, treatment plan, and special surgical concerns for each case using a treatment planning worksheet. The worksheets were scored and quantitative data were analyzed. Attitudinal responses to the simulation experience were captured with a post-survey and interview. The number of total prescribed surgical movements was greater for 3D and VR simulation methods (p=0.001). There were no differences in the overall total written treatment plan analysis score among the three surgical simulation tasks. Participants took longer to complete the VR and 3D tasks (p<0.001) and asked more questions regarding manipulation (p<0.001) and software features (p<0.002) for higher fidelity tools. Analysis of qualitative feedback showed positive attitudes toward higher fidelity tools with regard to visualization, manipulation, and enjoyment of the task. The results demonstrate that simulation methods of increased fidelity (3D and VR) are appropriate alternatives to 2D conventional orthognathic surgical simulation methods when combined with traditional records. Qualitative feedback confirms residents' readiness to adopt VR simulation. However, comprehensive training is needed to increase familiarity and comfort with using the new technology.