We would like to welcome you to this Special Issue on Medical Simulation, the first of its kind not only for SIMULATION: Transactions of The Society for Modeling and Simulation International, but for any technical journal. Our respective backgrounds are an indication of the technical and clinical breadth of medical simulation, as we approach the subject as primarily medical image analysis and biomechanics experts respectively, each with a variety of clinical interests spanning virtual reality (VR)–based neuro-, orthopedic and ear-nose-and-throat surgery. Moreover, we believe that the breadth of the papers that comprise this issue reflects an even broader perspective. After all, medical simulation can be seen as encompassing mannequin-based training, as well as nonsurgical areas such as pharmacological and physiological modeling, the latter of which is increasingly multi-scale and integrative. One of the most compelling reasons for publishing an issue dedicated to medical simulation, and for emphasizing this area on a regular basis within the journal SIMULATION, is its inherently open-ended aspect. After all, if we view the current state of medical modeling and simulation (M&S), especially interactive M&S for training, in terms of the degree of its penetration in comparison with the amount of material that must be covered in medical school and in most residency programs, there is a large amount of research still left to be done. Moreover, medical M&S is also characterized by conflicting requirements that will have to be resolved for it to make a serious dent in the requirements of these programs. For example, VR-based medical M&S will require therapy models (e.g., cutting and resection models) that reconcile real-time interactivity with realistic, nonlinear tissue response. It will also need a methodology for generating patient-specific anatomical models of sufficient descriptiveness to meet the exacting requirements of senior clinicians, which entails dealing with another set of conflicting requirements: The need to keep a ceiling on the element count in a simulation, which entails large elements, versus the need to account for critical tissues, which presupposes small elements. New methodologies will have to be perfected for both specifying requirements and validation, in a manner that leads to meaningful simulation-based training that is predictive of future caseloads. From a requirements standpoint, we will have to exploit methods for specifying what goes on in a surgical intervention or medical process in a manner that leads to broadly usable top-down requirements analysis, which in turn may contrast with the artful aspect of clinical or surgical practice. From a validation standpoint, it may not be enough to merely distinguish between expert and novice clinicians, since the economy of movement of the expert in his or her surgical gestures immediately comes into play as soon as we integrate a haptic device into the simulation. As described in the call for papers, the clinical need that justifies pursuing medical simulation with a strong predictive aspect lies in two marked tendencies in modern clinical practice: the compression of training schedules of residents and the constant influx of new therapeutic technologies. Recent compressions in training can adversely affect the development of clinical skill, particularly in the traditional framework whereby residents observe senior clinicians and gradually assume responsibility. Interactive medical simulation can provide a means for accelerating resident training, allowing junior clinicians to take a more active role than in the traditional framework, which can result in measurable improvements to both skill and patient outcome. Increasingly however, if we are successful in reconciling difficult conflicts in requirements (such as interactivity and complex tissue response), we will find that the market for simulation is not merely medical schools looking to train students and residents, but all clinicians who are interested in a patient-specific dynamic exercise in surgical planning, in a manner that leads to finding the best among competing options, for example the surgical path that best spares eloquent and critical tissues to get to a tumor.
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