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      Creation of a novel simulator for minimally invasive neurosurgery: fusion of 3D printing and special effects

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          Abstract

          OBJECTIVE Recent advances in optics and miniaturization have enabled the development of a growing number of minimally invasive procedures, yet innovative training methods for the use of these techniques remain lacking. Conventional teaching models, including cadavers and physical trainers as well as virtual reality platforms, are often expensive and ineffective. Newly developed 3D printing technologies can recreate patient-specific anatomy, but the stiffness of the materials limits fidelity to real-life surgical situations. Hollywood special effects techniques can create ultrarealistic features, including lifelike tactile properties, to enhance accuracy and effectiveness of the surgical models. The authors created a highly realistic model of a pediatric patient with hydrocephalus via a unique combination of 3D printing and special effects techniques and validated the use of this model in training neurosurgery fellows and residents to perform endoscopic third ventriculostomy (ETV), an effective minimally invasive method increasingly used in treating hydrocephalus. METHODS A full-scale reproduction of the head of a 14-year-old adolescent patient with hydrocephalus, including external physical details and internal neuroanatomy, was developed via a unique collaboration of neurosurgeons, simulation engineers, and a group of special effects experts. The model contains "plug-and-play" replaceable components for repetitive practice. The appearance of the training model (face validity) and the reproducibility of the ETV training procedure (content validity) were assessed by neurosurgery fellows and residents of different experience levels based on a 14-item Likert-like questionnaire. The usefulness of the training model for evaluating the performance of the trainees at different levels of experience (construct validity) was measured by blinded observers using the Objective Structured Assessment of Technical Skills (OSATS) scale for the performance of ETV. RESULTS A combination of 3D printing technology and casting processes led to the creation of realistic surgical models that include high-fidelity reproductions of the anatomical features of hydrocephalus and allow for the performance of ETV for training purposes. The models reproduced the pulsations of the basilar artery, ventricles, and cerebrospinal fluid (CSF), thus simulating the experience of performing ETV on an actual patient. The results of the 14-item questionnaire showed limited variability among participants' scores, and the neurosurgery fellows and residents gave the models consistently high ratings for face and content validity. The mean score for the content validity questions (4.88) was higher than the mean score for face validity (4.69) (p = 0.03). On construct validity scores, the blinded observers rated performance of fellows significantly higher than that of residents, indicating that the model provided a means to distinguish between novice and expert surgical skills. CONCLUSIONS A plug-and-play lifelike ETV training model was developed through a combination of 3D printing and special effects techniques, providing both anatomical and haptic accuracy. Such simulators offer opportunities to accelerate the development of expertise with respect to new and novel procedures as well as iterate new surgical approaches and innovations, thus allowing novice neurosurgeons to gain valuable experience in surgical techniques without exposing patients to risk of harm.

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          State of the evidence on simulation-based training for laparoscopic surgery: a systematic review.

          Summarize the outcomes and best practices of simulation training for laparoscopic surgery.
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            Simulation in surgical training: educational issues and practical implications.

            Surgical skills are required by a wide range of health care professionals. Tasks range from simple wound closure to highly complex diagnostic and therapeutic procedures. Technical expertise, although essential, is only one component of a complex picture. By emphasising the importance of knowledge and attitudes, this article aims to locate the acquisition of surgical skills within a wider educational framework. Simulators can provide safe, realistic learning environments for repeated practice, underpinned by feedback and objective metrics of performance. Using a simple classification of simulators into model-based, computer-based or hybrid, this paper summarises the current state of the art and describes recent technological developments. Advances in computing have led to the establishment of precision placement and simple manipulation simulators within health care education, while complex manipulation and integrated procedure simulators are still in the development phase. Tension often exists between the design and evaluation of surgical simulations. A lack of high quality published data is compounded by the difficulties of conducting longitudinal studies in such a fast-moving field. The implications of this tension are discussed. The emphasis is now shifting from the technology of simulation towards partnership with education and clinical practice. This highlights the need for an integrated learning framework, where knowledge can be acquired alongside technical skills and not in isolation from them. Recent work on situated learning underlines the potential for simulation to feed into and enrich everyday clinical practice.
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              Simulation-Based Medical Education

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                Author and article information

                Journal
                Journal of Neurosurgery: Pediatrics
                Journal of Neurosurgery: Pediatrics
                Journal of Neurosurgery Publishing Group (JNSPG)
                1933-0707
                1933-0715
                July 2017
                July 2017
                : 20
                : 1
                : 1-9
                Article
                10.3171/2017.1.PEDS16568
                28438070
                4529290a-a2d9-40a1-9f93-39bb0ccf7574
                © 2017
                History

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