Introduction

The focus of this chapter is virtual reality simulation and its role in urological applications. Virtual reality is one component of a true renaissance that is occurring in the surgical education curriculum. As hardware and software technology improve, it becomes possible to simulate a wider variety of surgical scenarios. Not only is it possible to prepare for such scenarios outside of the operating room but it is now possible to use the computer to automatically evaluate student performance and identify their specific training needs.

Every year at least 44,000 Americans die of medical errors. Medical errors are the seventh leading cause of death in the United States, greater than car accidents, breast cancer, or AIDS.

Pharmacy errors are no longer the leading cause of medical complications; procedural errors are. Indeed, there is an ever-increasing public scrutiny of medical training and the use of the operating room for teaching purposes.

Simulation is a promising alternative to training inside the operating room. Factors that support a shift toward simulation training include diminished resident work hours, increased operating room costs, the ACGME competency movement, and special training issues associated with the acquisition of minimally invasive surgical skills.

Many authors argue that the operating room is not the best environment for training (1,2). In fact, a recent survey of program directors demonstrated that 92% of respondents felt that there is a need for technical skills training outside of the operating room (3). However, the fact remains that to date there is a paucity of effective evaluation tools available that fully implement the power of simulation training as appropriate for a procedural skills training curriculum (4). Physical model simulators have been employed in many centers and have been shown to be effective in training some basic technical skills. Unfortunately, many of these training models do not convey a sense of "presence" to the student, and the models are not often coupled with objective metrics and training feedback. Virtual reality models represent an attractive solution to the above-mentioned shortcomings of physical model simulators. In particular, virtual reality simulation is very amenable to minimally invasive surgery and great strides have been made in select applications.

When considering virtual reality in surgery, the key is to obtain "mimesis," or to trick the mind into believing that it is immersed in a real-life task.

It is important to acknowledge that even the most advanced simulators do not replicate the exact look and feel of a real procedure. However, for a simulator to be effective, the mind must set aside a sense of disbelief when encountering an artificial yet similar set of visual, tactile, auditory, and olfactory sensations. The student should feel that there are real consequences to mistakes made with a virtual patient, just as there would be with a real patient.

Professional athletes, musicians, actors, performers, and even surgeons have employed simulation training in a variety of fashions for decades.

Training might focus on a subtask or an entire procedure in order for the student to achieve necessary technical skills.

On the simplest level, mental imagery techniques can be used to associate technical aspects of a procedure with cognitive rehearsal. This alone works well for relatively predictable activities, such as a 50 m swim or a gymnastic floor routine. The athlete commits to memory a list of steps required for performing a certain routine and then envisions performing each of those steps by the athlete. However, such training becomes difficult in situations where there is a reliance on multiple people, as they work with complex equipment while battling the physical forces of nature. For example, simulating scenarios on the battlefield or in outer space can be very complex and training errors can have serious repercussions. In these "less controlled environments," the aid of computer simulation to associate technical and cognitive learning can be very advantageous. Not only does simulation reinforce the learning of a particular technique but also how to deal with unexpected situations.

Simulation has been prevalent in industries such as aerospace, engineering, and the military since the 1950s. Complex tasks are evaluated not only to understand the overall problem but also to define individual components and how each part contributes to form the entire system. At the core of this process are information systems, which provide virtual prototyping of models. The tools include process and flow diagrams, interface requirement documents, and an overall design plan (5).

Aerospace, military, industrial, and medical simulation applications all share the common pretense that for a trainee to interact with a complex system, there must be a thorough understanding of the overall system and the relevance of each subcomponent. Such an understanding is necessary for a trainee to undertake the learning of many skill tasks that may involve life and death decisions.

A number of reasons for the limited role of simulation in the field of medicine compared to other industries have been postulated. One might blame the circumspect nature of medical professionals and their inability to see the "big picture" of technological advancements while trying to address patient demands with minor, incremental improvements (6). Another factor is the lack of a true funding source for efforts in surgical education. There is a significant shortfall in resources provided by government funding agency for supporting medical postgraduate education initiatives (7). The government does allocate money to residency programs. However, this money does not go to educational initiatives directly, but goes to the hospital to cover salaries and overhead assumed to exist because of the perceived inefficiencies associated with the training of residents. The end result is that medical institutions have little money allocated to buy surgery simulators and consequently the market for commercially developed simulators is quite small. Just the same, medical professionals expect the quality of surgical simulators to exceed that of common video games, even though the market for video games is many orders of magnitude greater than that of surgery simulators. Compounded by the reality that there are still a number of unsolved technical issues that prevent the creation of a truly accurate virtual prototype of the human body, there remains a large gap between expectations from the medical community and what industry is capable of delivering.

When considering virtual reality in surgery, the key is to obtain "mimesis," or to trick the mind into believing that it is immersed in a real-life task.

Training might focus on a subtask or an entire procedure in order for the student to achieve necessary technical skills.

Aerospace, military, industrial, and medical simulation applications all share the common pretense that for a trainee to interact with a complex system, there must be a thorough understanding of the overall system and the relevance of each subcomponent.

As compared to industrial and military applications, simulating the biological world includes additional complex layers of interactivity and unpredictability.

Excited by the potential for virtual reality training, pioneering academic surgeons began widely promoting virtual reality technology. However, the initial hype led to false expectations and the surgical community became highly critical of early surgery simulation.

Successful simulation projects now involve not only collaborations between members of the medical and computer sciences but also the cognitive sciences.

Simulation fidelity should be matched with training requirements because high fidelity simulators are not necessary for all tasks. It is the embedded instructional features in a simulator that make training effective.

As compared to industrial and military applications, simulating the biological world includes additional complex layers of interactivity and unpredictability.

When considering the modeling of mechanical systems and how they interact with the physics of nature, we have a pretty thorough understanding of the overall system and the contribution of the individual components. Unfortunately, we have just barely scratched the surface of understanding on how genes and cells interact with each other and what this means from a physiological standpoint. Clearly, this becomes even more complex when considering and attempting to predict the output of important psychosocial factors and surgical manipulations on the "black box" organ of the human body: the brain. This is a critical thing to consider, which often frustrates our engineering colleagues who like to translate phenomenon into formulas. How then are we to simulate what we may not understand completely in the real world? Currently, the information systems for our model—the human patient—merely consist of the patient's chart (history, physical examination, and laboratory studies), and imaging modalities (the video monitor, magenatic resonance imaging, computed tomography, ultrasound, etc.) (5,8). Regrettably, these data are insufficient to create a true virtual prototype of our model. Such a human surrogate in cyberspace would be based on patient-specific data from historical, genetic, molecular, biochemical, physiological, and digital imaging sources (9). However, even without the complete data set necessary to create a truly accurate model, virtual reality still continues to aid us in the process of understanding the human body through virtual analysis that employs "block box" methodologies such as neural networks, genetic algorithms, and hidden Markov models (10).

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