Virtual Neurosurgery- training for the future Michael Vloeberghs1, Tony Glover2, Steve Benford

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Figure 6: Example showing a post-cutting manipulation
Simulation of removing a tumour

The simulator allows the surgeon to cut deeper until a tumour is reached. The cut can then continue around the tumour surface until the tumour is totally separated and subsequently removed. Although the tumour is located within the brain, it can be simulated as a BE surface in full contact with the surrounding brain, i.e. the surface-only feature of BE modelling is preserved. Figure 7 shows a wire frame model containing a tumour underneath the surface.

Figure 7: 3D wire frame of a tumor beneath the surface of the organ
Feedback from surgeons

A preliminary evaluation of the simulator was performed. Two initial sessions were undertaken within the Nottingham University Hospital (NUH) where the system was demonstrated to more than 24 neurosurgical-related staff (ranging from neurosurgeons to theatre nurses). A more refined version of the simulator was then evaluated at a subsequent session in October 2005 with 13 participants who were either consultants or trainee neurosurgeons. Participants tried the simulator for a short period of time (a few minutes each) before giving feedback through a short questionnaire which gathered their opinions about its realism and potential improvements (Table 3). The evaluation only addressed prodding and pinching and making a few cuts. The working prototype was used with basic graphics and only one haptic device.

Preliminary feedback suggests that the current BE-based simulator and the hardware can achieve a sufficient level of realism to have a useful role in surgical training. Participants’ responses suggest that the simulation of pushing felt realistic, but pulling was less realistic since the current system allows an unlimited amount of tissue stretching. The simulation of cutting, while functional, requires further improvements in terms of feel and extra features such as simulating bleeding e.g. augmented reality would be a useful addition.
Table 3. Results of the VR questionnaire put to 13 Neurosurgeons, October 2005
(Scoring system: 1-5, 1=Very Good, 5=Very Bad)



Standard deviation

In general, how easy was the simulator to use?



How realistic did the brain look whilst pushing?



How realistic did pushing the brain feel?



How easy was pushing the brain?



How realistic did the brain look whilst pulling?



How realistic did pinching the brain tissue feel?



How easy was pulling the brain?



How realistic did the brain look whilst cutting?



How realistic did cutting the brain feel?



How easy was cutting the brain?



How realistic was the stereo viewing?



How comfortable was the physical setup?



Could the simulator help you understand basic surgical acts?

Do you think the simulator has a role in surgical training?

VR in surgery simulation:

The application of VR to surgery simulation was first proposed in the early 1990’s (1, 9, 11, 24, 29) and focussed on task simulation. With the increasing computer processing power and the availability of sophisticated input/output devices such as force-feedback devices (26), surgery simulation gained in sophistication and realism.

The lack of sufficient opportunities for trainee surgeons to practice surgery and clinical governance issues gives surgical simulators a role in training. Guidelines regarding surgical competence from the Royal college of Surgeons of England emphasise the parallel between civil aviation training and surgical training and highlight the role of simulation (30). Trainees also voice their concern about training and the time spent exposed to surgery (10, 19, 23). In the previous UK training system, trainees would spend and excess of 30000 hours training in their specialty. In the Modernised Medical Career (MMC) system, the hours are reduced to 15000 i.e. 50%. In comparison a NASA astronaut trains 10000 hours and a long haul airline pilot trains 5000 hrs (10). Building on previous VR work of the first author, this simulator uses “Patient specific” data from MRI (32, 33). Simulation of an actual patient is possible and extends the use of the device to the senior level where simulators have a role in Continuous Medical Training and pre-operative simulation of complex cases.
VR surgery is used in many specialties, such as endoscopy (31), microsurgery (12), neurosurgery (28), urology (14), orthopaedics (7) and ophthalmology (17), and is gradually gaining acceptance in the medical profession (13, 20). Previous simulators have concentrated on endoscopic surgery e.g. operating in a confined space with limited freedom, limiting the simulator to confined spaces and “drag and drop” surgical acts. This simulator approaches Neurosurgery from an “outside in“ perspective and uniquely allows the user to operate on the surface of the brain.
Real-time Boundary Element computations
The Boundary Element (BE) method is well established as an accurate stress analysis technique in which only the surface (boundary) needs to be represented (see, e.g. 2, 3, 8, 25); this is contrast with the finite element (FE) method, which requires representation of the entire model (see, e.g. 4, 5, 6). The interior of a BE domain is not rendered, resulting in a better resolution of the surface. A recent review of deformable models for surgery simulation by Meier et al (21) has identified the BE technique as being one of the most promising routes to surgical simulation..
Two early attempts, published by James, and Pai (15, 16) and Monserrat et al (22), to use BE to simulate deformable objects in VR support the method, demonstrated the basic feasibility of this approach, but did not cover the simulation of cutting, post-cutting deformation or two-handed operations. The BE work presented in this paper has built on this baseline, further extending the use of BE in surgical simulation (18, 34, 35).

An overview of a unique BE-based VR Neurosurgery simulator is presented which features real-time visual and haptic feedback allowing the user to perform the basic Neurosurgical acts on the brain. The research team has created the BE algorithms for this complex simulation and have proven that the surface-only modelling capability of the BE techniques are highly suitable for VR surgery.

Initial trials of the system by Neurosurgeons have indicated that a sufficient degree of realism can be achieved and that such simulators can play a useful role in surgical training. There are many challenges to address, which include more realism by use of augmented reality to simulate bleeding, tearing of tissue etc.
The authors believe simulation techniques, especially VR with haptic feedback as described in this paper, will in part address the concerns raised by training and governance bodies regarding training hours and litigation.

The authors wish to acknowledge the financial support of the UK, Engineering and Physical Sciences Research Council (EPSRC) research grant GR/R84030.
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