Roberta Rehder1, Muhammad Abd-El-Barr1, Kristopher Hooten2, Peter Weinstock3, Joseph R Madsen1, Alan R Cohen4. 1. Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, Massachusetts, 02115, USA. 2. Department of Neurosurgery, University of Florida, Gainesville, Florida, USA. 3. Department of Anesthesia, Pediatric Simulator Program Director, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA. 4. Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, Massachusetts, 02115, USA. Alan.Cohen@childrens.harvard.edu.
Abstract
PURPOSE: In an era of residency duty-hour restrictions, there has been a recent effort to implement simulation-based training methods in neurosurgery teaching institutions. Several surgical simulators have been developed, ranging from physical models to sophisticated virtual reality systems. To date, there is a paucity of information describing the clinical benefits of existing simulators and the assessment strategies to help implement them into neurosurgical curricula. Here, we present a systematic review of the current models of simulation and discuss the state-of-the-art and future directions for simulation in neurosurgery. METHODS: Retrospective literature review. RESULTS: Multiple simulators have been developed for neurosurgical training, including those for minimally invasive procedures, vascular, skull base, pediatric, tumor resection, functional neurosurgery, and spine surgery. The pros and cons of existing systems are reviewed. CONCLUSION: Advances in imaging and computer technology have led to the development of different simulation models to complement traditional surgical training. Sophisticated virtual reality (VR) simulators with haptic feedback and impressive imaging technology have provided novel options for training in neurosurgery. Breakthrough training simulation using 3D printing technology holds promise for future simulation practice, proving high-fidelity patient-specific models to complement residency surgical learning.
PURPOSE: In an era of residency duty-hour restrictions, there has been a recent effort to implement simulation-based training methods in neurosurgery teaching institutions. Several surgical simulators have been developed, ranging from physical models to sophisticated virtual reality systems. To date, there is a paucity of information describing the clinical benefits of existing simulators and the assessment strategies to help implement them into neurosurgical curricula. Here, we present a systematic review of the current models of simulation and discuss the state-of-the-art and future directions for simulation in neurosurgery. METHODS: Retrospective literature review. RESULTS: Multiple simulators have been developed for neurosurgical training, including those for minimally invasive procedures, vascular, skull base, pediatric, tumor resection, functional neurosurgery, and spine surgery. The pros and cons of existing systems are reviewed. CONCLUSION: Advances in imaging and computer technology have led to the development of different simulation models to complement traditional surgical training. Sophisticated virtual reality (VR) simulators with haptic feedback and impressive imaging technology have provided novel options for training in neurosurgery. Breakthrough training simulation using 3D printing technology holds promise for future simulation practice, proving high-fidelity patient-specific models to complement residency surgical learning.
Entities:
Keywords:
3D printing; Duty hours; Neurosurgery; Residency; Simulation; Virtual reality
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