Construct validity of the endoscopic sinus surgery simulator: II. Assessment of discriminant validity and expert benchmarking.

OBJECTIVES: To establish discriminant validity of the endoscopic sinus surgery simulator (ES3) (Lockheed Martin, Akron, Ohio) between various health care provider experience levels and to define benchmarking criteria for skills assessment. DESIGN: Prospective multi-institutional comparison study. SETTING: University-based tertiary care institution. PARTICIPANTS: Ten expert otolaryngologists, 14 otolaryngology residents, and 10 medical students. INTERVENTIONS: Subjects completed the ES3's virtual reality curriculum (10 novice mode, 10 intermediate mode, and 3 advanced mode trials). Performance scores were recorded on each trial. Performance differences were analyzed using analysis of variance for repeated measures (experience level as between-subjects factor). MAIN OUTCOME MEASURES: Simulator performance scores, accuracy, time to completion, and hazard disruption. RESULTS: The novice mode accurately distinguished the 3 groups, particularly at the onset of training (mean scores: senior otolaryngologists, 66.0; residents, 42.7; students, 18.3; for the paired comparisons between groups 1 and 2 and groups 1 and 3, P = .04 and .03, respectively). Subjects were not distinguished beyond trial 5. The intermediate mode only discriminated students from other subjects (P = .008). The advanced mode did not show performance differences between groups. Scores on the novice mode predicted those on the intermediate mode, which predicted advanced mode scores (r = 0.687), but no relationship was found between novice and advanced scores. All groups performed equally well and with comparable consistency at the outset of training. Expert scores were used to define benchmark criteria of optimal performance. CONCLUSIONS: This study completes the construct validity assessment of the ES3 by demonstrating its discriminant capabilities. It establishes expert surgeon benchmark performance criteria and shows that the ES3 can train novice subjects to attain those. The refined analysis of trial performance scores could serve educational and skills assessment purposes. Current studies are evaluating the transfer of surgical skills acquired on the ES3 to the operating room (predictive validity).

Virtual cues and functional mobility of people with Parkinson's disease: a single-subject pilot study.

In this study, adults with Parkinson's disease (PD) used virtual cueing spectacles (VCS) mimicking kinesia paradoxa in home and community settings to assess the impact on mobility and participation. We used an ABA single-subject design with repeated measures. Six adults with PD, akinesia, and stage III or IV Hoehn and Yahr rating scale status used VCS in their homes and communities for a week or more. Our main outcome measures included participant counts of losses of balance and freezes, pre-/postintervention completion of the Parkinson's Disease Questionnaire-39, observation of baseline and intervention gait, and an interview regarding user satisfaction with VCS. We also assessed participants' preuse baseline and return to baseline. Use of VCS decreased length of freezes as well as number of freezes for some participants. All participants expressed satisfaction with VCS. VCS shows promise in simulating kinesia paradoxa to improve the gait of some adults with PD in the home and community.

Real-time finite element based virtual tissue cutting.

Tool-tissue interaction is most accurately modeled as an imposed displacement constraint, thus augmenting the traditional finite element equation, Ku=f, to a 2 x 2 block system. This augmentation does two things: it enlarges the system, and it introduces the Schur complement(S) during the solution. This research has focused on efficient methods to update the Schur complement and it's inverse during displacement constraint removal and addition to allow for soft-tissue cutting to occur in real-time. By taking advantage of how the constraints impact the Schur complement, removal and addition of these constraints are handled by either performing a rank-2 or rank-1 update on S(-1), respectively. This greatly reduces the computational load on the CPU; and through use of timing tests shows that the update frequencies are well within an acceptable range for tactile feedback. To further solidify this method as being highly useful, a prototypical simulator has been developed that allows users to haptically perform bi-manual soft-tissue cutting.

Two-handed next generation suturing simulator.

A realistic two-handed surgical suturing simulation would have a broad impact on the way doctors are trained in the field of surgery. Current state-of-the-art in suturing simulators do not accurately represent realistic suturing conditions, leaving many necessary components, i.e. two-handed interaction, skin undermining, skin repositioning etc., out of the model completely. The goal of this research is to develop a next generation immersive suturing simulator that uses an integrated two-handed tension based haptic device for tactile feedback, a hi-fidelity finite element model for more accurate skin, tissue and needle modeling and stereoscopic vision for depth-of-field.

Real-time finite element modeling for surgery simulation: an application to virtual suturing.

Real-time finite element (FE) analysis can be used to represent complex deformable geometries in virtual environments. The need for accurate surgical simulation has spurred the development of many of the new real-time FE methodologies that enable haptic support and real-time deformation. These techniques are computationally intensive and it has proved to be a challenge to achieve the high modeling resolutions required to accurately represent complex anatomies. The authors present a new real-time methodology based on linear FE analysis that is appropriate for a wide range of surgical simulation applications. A methodology is proposed that is characterized by high model resolution, low preprocessing time, unrestricted multipoint surface contact, and adjustable boundary conditions. These features make the method ideal for modeling suturing, which is an element common to almost every surgical procedure. This paper describes constraints in the context of a Suturing Simulator currently being developed by the authors.

Simulation of bleeding in endoscopic procedures using virtual reality.

BACKGROUND AND PURPOSE: An image-based approach has been developed to represent bleeding in a simulator for transurethral resection of the prostate (TURP). Whereas previous groups attempted to simulate bleeding mathematically over tissue surfaces or in blood vessels, our approach focused on macroscopic visualization of bleeding in a fluid environment. The TURP is an ideal procedure for simulator-based training because of its importance as a skill to acquire as well as its long learning curve. The most challenging step in creating a realistic TURP simulator is simulated bleeding. MATERIALS AND METHODS: We took an image-based approach in which we generated blood flow movies of bleeding vessels having different severity and position under variable fluid flow conditions and processed them to separate the blood flow from the background anatomy. We then organized the movies into a parametric database. During the running of the simulation, resection systematically triggers the playback of a blood flow movie (bleeding event). The movie is texture mapped onto a virtual surface that is positioned, oriented, morphed, composited, and looped into the virtual scene. RESULTS AND CONCLUSION: The technique produced an accurate depiction of bleeding vessels one would encounter during a TURP. The image changes readily according to the fluid flow state.

Virtual image grafting: image based generation and visualization of virtual skin defects.

We have developed methods for rapidly generating 3d dermatologic datasets for use in education, training simulations and procedure planning. By compositing local surface features of cutaneous wounds onto patient images and 3d models, one can flexibly generate large patient variability from a small initial 3d library. The wound database is generated from clinically captured photographic images. The wound image is extracted from the image of the surrounding tissue. The 3d anatomy database is generated from MRI scans and from multiple photographic views. Extracted wound images can be moved rotated and scaled and blended in the final composite.