Characterizing the learning curve of a virtual intracorporeal suturing simulator VBLaST-SS©.

BACKGROUND: The virtual basic laparoscopic skill trainer suturing simulator (VBLaST-SS©) was developed to simulate the intracorporeal suturing task in the FLS program. The purpose of this study was to evaluate the training effectiveness and participants' learning curves on the VBLaST-SS© and to assess whether the skills were retained after 2 weeks without training. METHODS: Fourteen medical students participated in the study. Participants were randomly assigned to two training groups (7 per group): VBLaST-SS© or FLS, based on the modality of training. Participants practiced on their assigned system for one session (30 min or up to ten repetitions) a day, 5 days a week for three consecutive weeks. Their baseline, post-test, and retention (after 2 weeks) performance were also analyzed. Participants' performance scores were calculated based on the original FLS scoring system. The cumulative summation (CUSUM) method was used to evaluate learning. Two-way mixed factorial ANOVA was used to compare the effects of group, time point (baseline, post-test, and retention), and their interaction on performance. RESULTS: Six out of seven participants in each group reached the predefined proficiency level after 7 days of training. Participants' performance improved significantly (p < 0.001) after training within their assigned group. The CUSUM learning curve shows that one participant in each group achieved 5% failure rate by the end of the training period. Twelve out of fourteen participants' CUSUM curves showed a negative trend toward achieving the 5% failure rate after further training. CONCLUSION: The VBLaST-SS© is effective in training laparoscopic suturing skill. Participants' performance of intracorporeal suturing was significantly improved after training on both systems and was retained after 2 weeks of no training.

Correction to: Validation of a virtual intracorporeal suturing simulator.

The surname of Sreekanth Arikatla incorrectly appeared as Sreekanth Artikala.

Characterizing the learning curve of the VBLaST-PT(©) (Virtual Basic Laparoscopic Skill Trainer).

BACKGROUND: Mastering laparoscopic surgical skills requires considerable time and effort. The Virtual Basic Laparoscopic Skill Trainer (VBLaST-PT(©)) is being developed as a computerized version of the peg transfer task of the Fundamentals of Laparoscopic Surgery (FLS) system using virtual reality technology. We assessed the learning curve of trainees on the VBLaST-PT(©) using the cumulative summation (CUSUM) method and compared them with those on the FLS to establish convergent validity for the VBLaST-PT(©). METHODS: Eighteen medical students from were assigned randomly to one of three groups: control, VBLaST-training, and FLS-training. The VBLaST and the FLS groups performed a total of 150 trials of the peg-transfer task over a 3-week period, 5 days a week. Their CUSUM scores were computed based on predefined performance criteria (junior, intermediate, and senior levels). RESULTS: Of the six subjects in the VBLaST-training group, five achieved at least the "junior" level, three achieved the "intermediate" level, and one achieved the "senior" level of performance criterion by the end of the 150 trials. In comparison, for the FLS group, three students achieved the "senior" criterion and all six students achieved the "intermediate" and "junior" criteria by the 150th trials. Both the VBLaST-PT(©) and the FLS systems showed significant skill improvement and retention, albeit with system specificity as measured by transfer of learning in the retention test: The VBLaST-trained group performed better on the VBLaST-PT(©) than on FLS (p = 0.003), whereas the FLS-trained group performed better on the FLS than on VBLaST-PT(©) (p = 0.002). CONCLUSIONS: We characterized the learning curve for a virtual peg transfer task on the VBLaST-PT(©) and compared it with the FLS using CUSUM analysis. Subjects in both training groups showed significant improvement in skill performance, but the transfer of training between systems was not significant.

A simulation framework for tool tissue interactions in robotic surgery.

Robotic surgery is preferred over other traditional methods due to reduced complications and improved ergonomics for the operating surgeon. They are also a perfect platform for telesurgery. Automated surgery in which the robot is allowed to do various surgical tasks with minimal intervention is getting wider attention recently. In this paper, we introduce a simulation framework that can realistically simulate tool tissue interactions in robotic surgery, which can be used to design and test various control methodologies for automated surgical tasks. We present preliminary results from simulating a simple model of a surgical robot interacting with a volumetric model while performing a grasping and hold task.

Cost-efficient suturing simulation with pre-computed models.

Suturing is currently one of the most common procedures in minimally invasive surgery (MIS). We present a suturing simulation paradigm with pre-computed finite element models which include detailed needle-tissue and thread-tissue interaction. The interaction forces are derived through a reanalysis technique for haptic feedback. Besides providing deformation updates and high fidelity forces, our simulation is computationally less costly.

Real-time electrocautery simulation for laparoscopic surgical environments.

We present a novel real-time technique for cutting during electrocautery procedures in surgical training. Our algorithm is based on cauterizing the part of the tissue that exceeds the critical vaporization temperature. The resulting topology changes due to cutting are accounted for in real-time. Results presented for the overall electrocautery cutting algorithm show that the real-time costs are minimal and thus allow interactive simulation.

Plug-and-Play Tool Handles for Laparoscopic Surgery Simulators.

With ever growing attention of medical community on the usage of surgical simulators as effective training means, development of robust and cost-effective haptic tool interfaces is very much necessary. We have developed such tool interfaces that can be easily plugged to PHANTOM Omni. Besides simulating actual tools in operating room, they are cost-effective and are easy to build.

Surgical model-view-controller simulation software framework for local and collaborative applications.

PURPOSE: Surgical simulations require haptic interactions and collaboration in a shared virtual environment. A software framework for decoupled surgical simulation based on a multi-controller and multi-viewer model-view-controller (MVC) pattern was developed and tested. METHODS: A software framework for multimodal virtual environments was designed, supporting both visual interactions and haptic feedback while providing developers with an integration tool for heterogeneous architectures maintaining high performance, simplicity of implementation, and straightforward extension. The framework uses decoupled simulation with updates of over 1,000 Hz for haptics and accommodates networked simulation with delays of over 1,000 ms without performance penalty. RESULTS: The simulation software framework was implemented and was used to support the design of virtual reality-based surgery simulation systems. The framework supports the high level of complexity of such applications and the fast response required for interaction with haptics. The efficacy of the framework was tested by implementation of a minimally invasive surgery simulator. CONCLUSION: A decoupled simulation approach can be implemented as a framework to handle simultaneous processes of the system at the various frame rates each process requires. The framework was successfully used to develop collaborative virtual environments (VEs) involving geographically distributed users connected through a network, with the results comparable to VEs for local users.