Post on 28-Jan-2015
description
Virtual reality, the net and surgical training
Stephen O’Leary
Professor of Otolaryngology The University of Melbourne
Outline
• VR surgical simulation – for surgical training – What it is, how it works – Status and prospects
• Networking and remote surgery
Lessons from Aerospace
• Failure is catastrophic
• Resources are expensive
• Complex tasks
• ZERO tolerance of major error
Lesson from Space Exploration
• No “dressed rehearsal”
• Train for all possibilities “No surprises”
• Reduce “cognitive load”
Courtesy of NASA
Cognitive Load
VR Simulation for Surgery
• Freedom to fail – Practice until minimal standards are met
• Controlled training – Curriculum can be standardised
• Repeatability & Availability
Surgery for Cochlear Implantation
Courtesy of Cochlear
Temporal Bone - Anatomy
• At risk: – Facial nerve function – Sense of taste – Great Vessels – Integrity of Inner Ear:
hearing and balance – The dura
VR Simulation for Ear Surgery
• Scarcity of temporal bones
• To maximise real drilling experience – In the temporal bone laboratory – In the operating theatre
• To provide real-time feedback in training
Classical cortical mastoidectomy
• The skills required for this task: – Surgical Anatomy – Surgical Planning (strategy) – Technical drilling skills (psychomotor)
Surgical Planning
• Surgical “Landmarks”
• Finding surgical landmarks – In the correct order – Using the correct techniques
Courtesy Thomas Somers
Building 3D models
Imaging Data
Building 3D models
Manually segment anatomical structures
Mauro Maijorca, Brian Pyman, Yi Zhao, S. O’Leary
Building 3D models
Generate 3D models Assign colours
Building 3D models
Physical properties Sigmoid: Bleeding
The Prototype System
Force-Feedback (Haptics)
Mentoring across a Network
Simulation and Training
Texts Observation
Temporal Bone Laboratory
Operating Theatre
Simulation and Training
Texts Observation
Temporal Bone Laboratory
Operating Theatre
Virtual Surgery
Validation of VR simulation • Transfer of learning • Sensitivity to levels of expertise • Automated feedback to trainee
Transfer of Learning
Participants: • Novice surgeons
Procedure: • Cortical mastoidectomy
Outcome Measures: • Surgical Anatomy • Surgical Planning • Technical drilling skills
Oral assessment temporal bone
Temporal Bone Laboratory
Virtual Surgery
Oral assessment temporal bone
Repeat task until performance is error free
VR training and recognition of anatomy (on human temporal bone)
VR simulation for assessment
Trainees Experts
VirtualSurgery Cortical Mastoid
Correlate observer & automated metrics
Sensitivity to levels of expertise
Participants: • Novices (9) • Registrars (6) • Experts (12)
• Standardised pre-reading • Performed a canal-wall down mastoidectomy • Metrics: Force, speed, stroke
Time to completion Total Time
0.00
10.00
20.00
30.00
40.00
50.00
60.00
Novice Registrar Expert
Time (m
in)
Total Number of s trokes
0
10000
20000
30000
40000
50000
Novice Registrar E xpertTotal N
o. of stroke
s ap
plied
Total jumps
0.00
500.00
1000.00
1500.00
2000.00
2500.00
3000.00
Novice Registrar ExpertNo. of jum
ps during the sim
ulation
Total voxels eroded
0.E +00
5.E +05
1.E +06
2.E +06
2.E +06
3.E +06
Novice Registrar E xpert
Total V
oxel erode
d
Average force <1cm from critical structures
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
Sigmoid Dura Facial
Average Force (N)
Novice
Registrar
Expert
Self-directed surgical curriculum
• e.g. exposing the dura
Instructional video
• Force, distance
Practice with immediate feedback
• Quality assurance
Comparison with “ideal” end result
• Improve visual recognition
Operative Photos and videos
Aim/research question
Virtual Reality Simulation
Traditional Methods
Study Method: Randomized, Blinded, Control Trial
Didactic Teaching (20)
VR simulation Group (10)
Cortical mastoidectomy
Traditional Group (10)
Cortical mastoidectomy
Assessment • 1 hour time limit • “standardized” temporal bones • Video taped • 3 Blinded assessors • Multifaceted Assessment tool
focusing on 4 areas of performance
Overall Performance
0
10
20
30
40
50
60
70
VR Traditional
ICC = 0.93 P-value <0.001
End product analysis
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
Dura Sigmoid EAC LSCC Incus
VR
Trad
ICC = 0.78 P-value <0.001
Injury size
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
Dura Sigmoid EAC LSCC Incus
VR
Traditional
ICC = 0.88 P-value =0.01
!
!
Formative feedback
• Timely feedback is key to learning • Aim is to provide feedback “expert-like”
feedback • This should facilitate independent
learning on the simulator
Efficacy Real-time feedback
Wijewickrema et al, unpublished data 24 medical students, performing cortical mastoidectomy randomised to receiving feedback or not
Feedback Method
Random Forest algorithm of Bailey , Zhou et al,
Networking and remote surgery
• The Speed of Light (and networks) • Ping and Lag
– Real-time interaction impossible when latency exceeds reaction time
– For training this is not critical – But for surgery…….
Working with lag
Courtesy of NASA
Working with lag
COURTESY OF ST. JOSEPH'S HOSPITAL
Conceding to lag: Tele-presence surgery
Courtesy of NASA
Tele-presence surgery
Assisting surgeons in Remote communities
Tele-present Surgery in space Courtesy NASA
Courtesy NASA
Courtesy NASA
Courtesy NASA
On Mars, this won’t work……
Conclusions
• VR surgery research: – Can discriminate between levels of experience – Transfer of learning to temporal bone dissection – Self-directed learning works – Frontier: automated feedback
• Networking and telemedicine – Remote-control surgery limited by lag – Tele-presence surgery realistic alternative – Simulation ideal for establishing protocols
The people
• Gregor Kennedy – Educational psychologist • Ioanna Ioannou, Sudanthi Widewickrema
- computer engineers • Yi Chen Zhao, Yun Zhou- PhD’s • Ioanna Ioannou, Brian Pyman, Richard Hall,
Kumiko Yukawa, Mauro Maijorca, Peter Harris, Liz Sonenburg (Melb. Uni.)
• M. Hutchins, C. Gunn, A. Krompholz, D. Stevenson (CSIRO)
The organisations
• Melbourne University • CSIRO • Medic Vision
(held license from University/ CSIRO 2006-2010) • Royal Victorian Eye and Ear Hospital • Royal Prince Alfred Hospital • Royal Australasian College of Surgeons • Medtronic Xomed (grant for early validation)
The funding bodies
US Air Force
Courtesy The Age