P.215 Tumor Heatmaps – Feedback Tool for Virtual Reality Neurosurgical
                        Simulation

Background: Performance Heatmaps were designed to visualize the spatial distribution of performance metrics during resection of complex tumors. This novel methodology provides experts (neurosurgeons) and trainees (residents and medical students) with visual feedback on their neurosurgical performance during operative procedures. Methods: Neurosurgeons (NS), senior residents (SR), junior residents (JR) and medical students (MS) performed resection of a complex tumor on the NeuroVR simulation platform. Metrics including time spent, force applied, and tumor volume removed were used to create Performance Heatmaps for each group. Results: During complex operative procedures, greater expertise correlated increased time spent in critical areas (NS = 121.0 s, SR = 103.0 s, JR = 86.1 s, MS = 84.9 s), increased force application (NS = 387 N, SR = 317 N, JR = 340 N, MS = 304 N), and increased tumor removal (NS = .096 cc, SR = .081 cc, JR = .074 cc, MS = .069 cc). Conclusions: Performance Heatmaps further our understanding of neurosurgical expertise by identifying key differences between experts (neurosurgeons) and trainees (residents and medical students). With the adoption of competency-based curricula, intuitive feedback tools will prove essential for trainees seeking surgical mastery.

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Subjective anxiety ratings before and after stressful neurosurgical virtual reality tumor resection task

Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques ◽

10.1017/cjn.2015.190 ◽

2015 ◽

Vol 42 (S1) ◽

pp. S42-S42

Author(s):

A Winkler-Schwartz ◽

J Fares ◽

B Khalid ◽

M Baggiani ◽

S Christie ◽

...

Keyword(s):

Virtual Reality ◽

Medical Students ◽

Tumor Resection ◽

Tumor Removal ◽

Surgical Performance ◽

Surgical Simulators ◽

Surgical Expertise ◽

Before And After ◽

Operative Performance ◽

Junior Residents

Background: The availability of virtual reality (VR) surgical simulators affords the opportunity to assess the influence of stress on neurosurgical operative performance in a controlled laboratory environment. This study sought to examine the effect of a stressful VR neurosurgical task on the subjective anxiety ratings of participants with varying levels of surgical expertise. Methods: Twenty four participants comprised of six staff neurosurgeons, six senior neurosurgical residents (PGY4-6), six junior neurosurgical residents (PGY1-3), and six senior medical students took part in a bimanual VR tumor removal task with a component of sudden uncontrollable intra-operative bleeding. State Trait Anxiety Inventory (STAI) questionnaires were completed immediately pre and post the stress stimulus. The STAI questionnaire consisted of six items (calm, tense, upset, relaxed, content and worried) measured on a Likert scale. Results: Significant increases in subjective anxiety ratings were noted in junior residents (p=0.005) and medical students (p=0.025) while no significant changes were observed for staff and senior neurosurgical residents. Conclusions: Staff and senior residents more effectively mitigate stress compared to junior colleagues in a VR operative environment. Further physiological correlates are needed to determine whether this increased anxiety is paralleled by physiological arousal and altered surgical performance.

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P.079 Development of a performance model for virtual reality tumor resections

Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques ◽

10.1017/cjn.2018.181 ◽

2018 ◽

Vol 45 (s2) ◽

pp. S37-S37 ◽

Cited By ~ 2

Author(s):

R Sawaya ◽

G Alsideiri ◽

A Bugdadi ◽

A Winkler-Schwartz ◽

H Azarnoush ◽

...

Keyword(s):

Virtual Reality ◽

Brain Tumor ◽

Medical Students ◽

Tumor Volume ◽

Performance Model ◽

Total Force ◽

Haptic Information ◽

Tumor Removal ◽

Hypothetical Model ◽

And Task

Background: This work proposes a hypothetical model that integrates human factors (e.g. inherent ability and acquired expertise) and task factors (e.g. pre-procedural data, visual and haptic information) to better understand the hand ergonomics adaptation needed for optimal safety and efficiency during simulated brain tumor resections. Methods: Hand ergonomics of neurosurgeons, residents and medical students were assessed during simulated brain tumors resection on the NeuroVR virtual reality neurosurgical simulation platform. Spatial distribution of time expended, force applied, and tumor volume removed, and other metrics were analyzed in each tumor quadrant (Q1 to Q4). Results: Significant differences were observed between the most favorable hand ergonomics condition (Q2) and the unfavorable hand ergonomics condition (Q4). Neurosurgeons applied more total force, more mean force, and removed less tumor per unit of force applied in Q4. However, total volume removed was not significant between the two quadrants indicating hand ergonomics adaptation in order to maximize tumor removal. In comparison, hand ergonomics of medical students remained unchanged in all quadrants, indicating a learning phenomenon. Conclusions: Neurosurgeons are more capable of adapting their hand ergonomics during simulated brain tumor resections. Our proposed hypothetical model integrates our findings with the literature and highlights the importance of experience in the acquisition of adaptive hand ergonomics.

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Development of a performance model for virtual reality tumor resections

Journal of Neurosurgery ◽

10.3171/2018.2.jns172327 ◽

2019 ◽

Vol 131 (1) ◽

pp. 192-200 ◽

Cited By ~ 2

Author(s):

Robin Sawaya ◽

Ghusn Alsideiri ◽

Abdulgadir Bugdadi ◽

Alexander Winkler-Schwartz ◽

Hamed Azarnoush ◽

...

Keyword(s):

Virtual Reality ◽

Brain Tumor ◽

Medical Students ◽

Direct Contact ◽

Tumor Volume ◽

Tumor Resection ◽

Performance Model ◽

Hypothetical Model ◽

Study Results ◽

And Task

OBJECTIVEPrevious work from the authors has shown that hand ergonomics plays an important role in surgical psychomotor performance during virtual reality brain tumor resections. In the current study they propose a hypothetical model that integrates the human and task factors at play during simulated brain tumor resections to better understand the hand ergonomics needed for optimal safety and efficiency. They hypothesize that 1) experts (neurosurgeons), compared to novices (residents and medical students), spend a greater proportion of their time in direct contact with critical tumor areas; 2) hand ergonomic conditions (most favorable to unfavorable) prompt participants to adapt in order to optimize tumor resection; and 3) hand ergonomic adaptation is acquired with increasing expertise.METHODSIn an earlier study, experts (neurosurgeons) and novices (residents and medical students) were instructed to resect simulated brain tumors on the NeuroVR (formerly NeuroTouch) virtual reality neurosurgical simulation platform. For the present study, the simulated tumors were divided into four quadrants (Q1 to Q4) to assess hand ergonomics at various levels of difficulty. The spatial distribution of time expended, force applied, and tumor volume removed was analyzed for each participant group (total of 22 participants).RESULTSNeurosurgeons spent a significantly greater percentage of their time in direct contact with critical tumor areas. Under the favorable hand ergonomic conditions of Q1 and Q3, neurosurgeons and senior residents spent significantly more time in Q1 than in Q3. Although forces applied in these quadrants were similar, neurosurgeons, having spent more time in Q1, removed significantly more tumor in Q1 than in Q3. In a comparison of the most favorable (Q2) to unfavorable (Q4) hand ergonomic conditions, neurosurgeons adapted the forces applied in each quadrant to resect similar tumor volumes. Differences between Q2 and Q4 were emphasized in measures of force applied per second, tumor volume removed per second, and tumor volume removed per unit of force applied. In contrast, the hand ergonomics of medical students did not vary across quadrants, indicating the existence of an “adaptive capacity” in neurosurgeons.CONCLUSIONSThe study results confirm the experts’ (neurosurgeons) greater capacity to adapt their hand ergonomics during simulated neurosurgical tasks. The proposed hypothetical model integrates the study findings with various human and task factors that highlight the importance of learning in the acquisition of hand ergonomic adaptation.

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

British Journal of Surgery ◽

10.1093/bjs/znab361.022 ◽

2021 ◽

Vol 108 (Supplement_7) ◽

Author(s):

Recai Yilmaz ◽

Alexander Winkler-Schwartz ◽

Aiden Reich ◽

Rolando Del Maestro

Keyword(s):

Neural Network ◽

Virtual Reality ◽

Deep Learning ◽

Medical Students ◽

Deep Neural Network ◽

Performance Metrics ◽

Technical Skills ◽

Surgical Performance ◽

Surgical Simulators ◽

Surgical Technical

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.

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O51: ARTIFICIAL INTELLIGENCE UTILIZING RECURRENT NEURAL NETWORKS TO CONTINUOUSLY MONITOR COMPOSITES OF SURGICAL EXPERTISE

British Journal of Surgery ◽

10.1093/bjs/znab117.051 ◽

2021 ◽

Vol 108 (Supplement_1) ◽

Author(s):

R Yilmaz ◽

A Winkler-Schwartz ◽

N Mirchi ◽

A Reich ◽

R Del Maestro

Keyword(s):

Neural Network ◽

Artificial Intelligence ◽

Virtual Reality ◽

Medical Students ◽

Recurrent Neural Network ◽

Haptic Feedback ◽

Performance Metrics ◽

Tumor Resection ◽

Technical Skills ◽

Surgical Expertise

Abstract Introduction Many surgical adverse events occur secondary to technical errors related to poor bimanual skills, fatigue and lack of the required expertise. We developed AI algorithms to continuously assess surgical bimanual technical performance during virtual reality simulated surgical tasks. To our knowledge, this is the first attempt in surgery to train AI algorithms to continuously monitor and evaluate bimanual skills comprehensively. Method Fifty individuals from four expertise levels (14 experts/neurosurgeons, 14 senior residents, 10 junior residents, 12 medical students) performed two virtual reality simulated surgical tasks with haptic feedback: a subpial tumor resection 5 times and a complex, realistically simulated brain tumor operation once. Each task required complete tumor removal while minimizing bleeding and damage to surrounding tissues using a simulated ultrasonic aspirator and a bipolar. A recurrent neural network continually tracked individual bimanual performance utilizing 16 performance metrics generated every 0.2 seconds. Result The recurrent neural network algorithm was successfully trained using neurosurgeons and medical students' data, learning the composites of expertise comparing high and lower skill levels. The trained algorithm outlined and monitored technical skills every 0.2 second continuously organizing performance of each surgical task into three levels: ‘excellent’, ‘average’ and ‘poor’. The percentage time spent on each level was calculated and significant differences found between all four groups for ‘excellent’ and ‘poor’ levels. Conclusion AI-powered surgical simulators provide an advanced assessment and training tool. AI's ability to continuous assess bimanual technical skills during surgery may further define the composites necessary to train surgical expertise. Abbrev AI: artificial intelligence Take-home message By advanced artificial intelligence algorithms surgeon's bi-manual technical skills can be assessed continuously, time periods of poor performance which increase the possibility of errors in performance can be identified.

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Face, Content, and Construct Validity of a Virtual Reality Otoscopy Simulator and Applicability to Medical Training

Otolaryngology ◽

10.1177/01945998211032897 ◽

2021 ◽

pp. 019459982110328

Author(s):

Tobias Albrecht ◽

Christoph Nikendei ◽

Mark Praetorius

Keyword(s):

Virtual Reality ◽

Medical Students ◽

Construct Validity ◽

Content Validity ◽

Medical Training ◽

Controlled Trial ◽

Correct Diagnosis ◽

Age Groups ◽

Tertiary Referral Center ◽

The Face

Objective Otologic diseases are common in all age groups and can significantly impair the function of this important sensory organ. To make a correct diagnosis, the correct handling of the otoscope and a correctly performed examination are essential. A virtual reality simulator could make it easier to teach this difficult-to-teach skill. The aim of this study was to assess the face, content, and construct validity of the novel virtual reality otoscopy simulator and the applicability to otologic training. Study Design Face and content validity was assessed with a questionnaire. Construct validity was assessed in a prospectively designed controlled trial. Setting Training for medical students at a tertiary referral center. Method The questionnaire used a 6-point Likert scale. The otoscopy was rated with a modified Objective Structured Assessment of Technical Skills. Time to complete the task and the percentage of the assessed eardrum surface were recorded. Results The realism of the simulator and the applicability to medical training were assessed across several items. The ratings suggested good face and content validity as well as usefulness and functionality of the simulator. The otolaryngologists significantly outperformed the student group in all categories measured (P < .0001), suggesting construct validity of the simulator. Conclusion In this study, we could demonstrate face, content, and construct validity for a novel high-fidelity virtual reality otoscopy simulator. The results encourage the use of the otoscopy simulator as a complementary tool to traditional teaching methods in a curriculum for medical students.

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Comparison of the effectiveness of lecture instruction and virtual reality-based serious gaming instruction on the medical students’ learning outcome about approach to coma

BMC Medical Education ◽

10.1186/s12909-021-02771-z ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Meysam Siyah Mansoory ◽

Mohammad Rasool Khazaei ◽

Seyyed Mohsen Azizi ◽

Elham Niromand

Keyword(s):

Virtual Reality ◽

Medical Students ◽

Learning Outcomes ◽

Learning Outcome ◽

Serious Game ◽

Control Group ◽

Serious Gaming ◽

E Learning ◽

The Mean ◽

Lecture Instruction

Abstract Background New approaches to e-learning and the use of virtual reality technology and serious game in medical education are on the rise. Therefore, the purpose of this study was to compare the effectiveness of lecture method and virtual reality-based serious gaming (VRBSG) method on students learning outcomes about the approach to coma. Methods We adopted a randomized trial method for this study and selected 50 medical students dividing them into experimental and control groups. Students’ learning outcome was measured with a 10-item test. Serious game usability scale was used to evaluate the usability of the serious game. Descriptive and inferential statistics were used for data analysis by SPSS-22 software. Results Students’ familiarity with e-learning and VRBSG was low. The mean usability of a VRBSG was 126.78 ± 10.34 out of 150. The majority of students were eager to be instructed through VRBSG. The mean score of learning outcomes in the experimental group was significantly higher than the control group (t = − 2.457, P = 0.019). Conclusion Students’ learning outcomes in the VRBSG group in the test approach to coma were significantly better than the lecture group. The usability of the serious game instruction method was high. Taken together, instruction through VRBSG had an effective role in medical students’ learning.

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Self-Assessment of Problem Solving Disposition in Medical Students

Journal of Biomedical Education ◽

10.1155/2014/161204 ◽

2014 ◽

Vol 2014 ◽

pp. 1-6

Author(s):

Silvia Lizett Olivares-Olivares ◽

Mildred Vanessa López-Cabrera

Keyword(s):

Health Care ◽

Medical Education ◽

Medical Students ◽

Problem Solving ◽

Medical Schools ◽

Self Assessment ◽

Competency Based Education ◽

Competency Based ◽

Future Demands ◽

Disposition Model

Medical schools are committed to both students and society to develop capabilities required to succeed in health care environments. Present diagnosis and treatment methods become obsolete faster, demanding that medical schools incorporate competency-based education to keep pace with future demands. This study was conducted to assess the problem solving disposition of medical students. A three-subcategory model of the skill is proposed. The instrument was validated on content by a group of 17 experts in medical education and applied to 135 registered students on the sixth year of the M.D. Physician Surgeon program at a private medical school. Cronbach’s alpha indicated an internal consistency of 0.751. The findings suggest that selected items have both homogeneity and validity. The factor analysis resulted in components that were associated with three problem-solving subcategories. The students’ perceptions are higher in the pattern recognition and application of general strategies for problem solving subcategories of the Problem solving disposition model.

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Independent validation of simbiosys tumorscope to predict response to neoadjuvant chemotherapy (NACT) in early breast cancer (EBC).

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.582 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 582-582

Author(s):

Gong He ◽

Frederick Howard ◽

Tushar Pandey ◽

Hiroyuki Abe ◽

Rita Nanda

Keyword(s):

Breast Cancer ◽

Sensitivity And Specificity ◽

Cancer Biology ◽

Tumor Volume ◽

Performance Metrics ◽

External Validation ◽

Pathologic Complete Response ◽

Disease Free Survival ◽

Biophysical Model ◽

Lymph Node Status

582 Background: Despite substantial advances in the understanding of breast cancer biology, the decision to use NACT for EBC is based on tumor size, lymph node status, and subtype. Even with aggressive therapy, the majority of women will not achieve a pathologic complete response (pCR). Investigational treatment regimens, including immunotherapy, can increase pCR rates, but are associated with irreversible immune-related toxicities. Being able to accurately predict pCR could identify candidates for intensification or de-escalation of NACT, allowing for personalized medicine. SimBioSys TumorScope (TS) is a biophysical model that utilizes baseline MRI, receptor status, and planned treatment regimen to simulate response to NACT over time. TS has demonstrated accurate prediction of pCR in prior studies. Here, we describe an independent external validation of TS. Methods: We conducted a retrospective study of University of Chicago patients (pts) who received NACT for EBC from Jan 2010 - March 2020. Pts must have had a pretreatment breast MRI. Tumors were analyzed using TS by investigators who were blinded to response data. TS predicted pCR was predefined as a residual tumor volume < 0.01 cm3 or a 99.9% or greater reduction in tumor volume. Performance metrics of TS were calculated. Results: 144 tumors from 141 pts were analyzed. Average age was 52 yrs; 65% had stage II and 19% had stage III disease. Sensitivity and specificity of TS for predicting pCR were 90.4% and 92.4%, respectively. Of the 7 patients who were predicted to achieve a pCR but did not, 5 had a tumor cellularity < 5%. With a median follow-up of 4.7 yrs, the 4-yr distant disease free survival (DDFS) was 100% for patients predicted to achieve pCR, versus 81.5% for those predicted to have residual disease. Results were generally robust for all subgroups analyzed (Table). Conclusions: TS accurately predicts pCR and DDFS from baseline MRI and clinicopathologic data. Given the high sensitivity and specificity of this assay across breast cancer subtypes, TS can be used to aid in escalation/de-escalation strategies for EBC.[Table: see text]

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Missing the mark: Current practices in teaching the male urogenital examination to Canadian undergraduate medical students

Canadian Urological Association Journal ◽

10.5489/cuaj.3679 ◽

2016 ◽

Vol 10 (7-8) ◽

pp. 281

Author(s):

Kristen McAlpine ◽

Stephen Steele

Keyword(s):

Medical Students ◽

Clinical Training ◽

Clinical Skills ◽

Medical Schools ◽

Clinical Settings ◽

Undergraduate Medical Students ◽

Canadian Medical School ◽

Competency Based ◽

English Speaking ◽

And Training

Introduction: The urogenital physical examination is an important aspect of patient encounters in various clinical settings. Introductory clinical skills sessions are intended to provide support and alleviate students’ anxiety when learning this sensitive exam. The techniques each Canadian medical school uses to guide their students through the initial urogenital examination has not been previously reported.Methods: This study surveyed pre-clerkship clinical skills program directors at the main campus of English-speaking Canadian medical schools regarding the curriculum they use to teach the urogenital examination.Results: A response rate of 100% was achieved, providing information on resources and faculty available to students, as well as the manner in which students were evaluated. Surprisingly, over onethird of the Canadian medical schools surveyed failed to provide a setting in which students perform a urogenital examination on a patient in their pre-clinical years. Additionally, there was no formal evaluation of this skill set reported by almost 50% of Canadian medical schools prior to clinical training years.Conclusions: To ensure medical students are confident and accurate in performing a urogenital examination, it is vital they be provided the proper resources, teaching, and training. As we progress towards a competency-based curriculum, it is essential that increased focus be placed on patient encounters in undergraduate training. Further research to quantify students’ exposure to the urogenital examination during clinical years would be of interest. Without this commitment by Canadian medical schools, we are doing a disservice not only to the medical students, but also to our patient population.

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