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Virtual Reality Surgical Training at the University of Washington

Virtual Reality Surgical Training at the University of Washington. Presented By: Timothy Kowalewski Robert Sweet MD, Urology Suzanne Weghorst, Human Interface Technology Lab Prof. Blake Hannaford, Electrical Engineering. TURP/Urology. Skin Suturing. Sinus Surgery. O.R. vs V.R.

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Virtual Reality Surgical Training at the University of Washington

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  1. Virtual RealitySurgical Training at the University of Washington Presented By: Timothy Kowalewski Robert Sweet MD, Urology Suzanne Weghorst, Human Interface Technology Lab Prof. Blake Hannaford, Electrical Engineering

  2. TURP/Urology Skin Suturing Sinus Surgery O.R. vs V.R. “It’s no longer blood and guts, it’s bits and bytes” (Col. Richard Satava, MD) Prof. Of Surgery, UW; DARPA

  3. What is TURP? • Transuretheral Resection of the Prostate • Gold-standard for treating obstructive urinary symptoms • Challenging to teach and learn

  4. What is TURP? • Transuretheral Resection of the Prostate • Gold-standard for treating obstructive urinary symptoms • Challenging to teach and learn

  5. National Average Number of TURPS performed by residents Source: ACGME 1990 1992 1994 1996 1998 TURP: a good model for Simulation • Apparent training gap • Common problem • Objective assessment • High risk to patients Sweet, et al. Journal of Endourology. October, 2002.

  6. TURP: a good model for Simulation 99%: Validated Simulator Useful in Training • Mainstay operation • Apparent demand • Amenable to current technology 98%: TURP is the Gold Standard of care …YES 75%: Validated Simulator Useful after Residency

  7. Methods • Simulator Construction  Virtual anatomy and visual elements  Real-time force / tactile feedback  O.R. instrumentation  External physical model  Auditory cues

  8. Methods • Simulator Construction • Training Video  Definition of task and errors  Statement of goal: “Efficiently resect as much tissue as possible while avoiding errors and minimizing blood loss, amount of irrigant used, coagulation current and number of cuts…” Special Thanks to Anthony Gallager, Ph.D

  9. Methods • Simulator Construction • Training Video • Pre-Task Questionnaire  Demographics, gender, professional experience, education, ‘video game’ experience, TURP-related questions, etc…  Stratification of database

  10. Methods • Simulator Construction • Training Video • Pre-Task Questionnaire • Pre-Compiled, 5-minute Task  Three trained, non-medical technicians  Consistent, pre-determined responses  Privacy and Anonymity

  11. Methods • Simulator Construction • Training Video • Pre-Task Questionnaire • Pre-Compiled, 5-minute Task • Post-Task Questionnaire  Critique of simulator according to its elements  Open feedback

  12. Methods • Simulator Construction • Training Video • Pre-Task Questionnaire • Pre-Compiled, 5-minute Task • Post-Task Questionnaire • AUA Annual Conference  72 Experts  19 Trainees  19 Novices

  13. Metrics • Grams of tissue resected • Amount of irrigant used • Quantity of ambient blood • Number and severity of bleeding vessels • Instrument position and interaction • Number of cuts at tissue • ~ 12 Hz resolution • Combinations thereof …

  14. Results: Face Validity • Do you feel the UW TURP Simulator would be useful as a training tool?

  15. Results: Face Validity • Would you like to see it implemented into the curriculum of residency programs?

  16. Results: Face Validity • Do you feel it would be useful as a tool for accreditation?

  17. Totally acceptable Moderately acceptable Slightly acceptable Acceptability threshold Slightly unacceptable Moderately unacceptable Totally unacceptable Results: Content Validity • Categorical Standardized Likert scale of global acceptability

  18. ( p < ) 0.0001 - 0.0001+ 0.0001+ 0.001+ 0.002+ 0.002+ 0.002+ 0.006+ 0.016+ 0.020 - 0.032 - 0.080+ 0.097 - Results: Novices vs. Experts Result of Levene-conditioned two-tailed T-test quantifies resolving potential of selected metrics to determine differences between novices and experts.

  19. Results: Construct Validity Performance of Errors

  20. Construct/Concurrent Validity(Cross-sectional) • Metrics correlationsmimicked the operating room. • Experts and trainees weremore efficient at cutting than novices. (P<.01) • Experts weremore efficient at coagulating bleeders than trainees who were more efficient than novices. (P<.05, P<.01) • Performance among expertsdid not exhibit “decay” • Video game experience influenced performance in novices andexperts only.

  21. Conclusions • Established Face and Content Validity • Established Construct Validity (X-sectional) • Addressed Concurrent Validity (incomplete) • NO assessment predictive validity or longitudinal studies - - - For Version 1.0 - - -

  22. Anatomy ID Module Coagulation Module Advanced Resection Module Version 2.0Predictive and Construct Validation Study Cutting Module

  23. http://www.hitl.washington.edu/people/tmk/TURP/TURPwww

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