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A Novel 3D-Printed Bilateral Sagittal Split Osteotomy Simulation Tool for Resident Education

医学 下牙槽神经 软组织 置信区间 3d打印 生殖成形术 下颌骨(节肢动物口器) 牙科 利多卡因 口腔正畸科 正颌外科 外科 生物医学工程 臼齿 内科学 生物 植物
作者
Katherine J. Zhu,Yu-Rui Zhang,Seray Er,Matthew J. Heron,Jacob B. Hammond,Sha Meng,Jesse Haworth,Edgar Soto,Russell H. Taylor,Robin Yang
出处
期刊:Journal of Craniofacial Surgery [Lippincott Williams & Wilkins]
标识
DOI:10.1097/scs.0000000000011833
摘要

Background: Bilateral sagittal split osteotomy (BSSO) carries a high risk of neurosensory injury. Surgical simulation of BSSO may improve confidence, technical skills, and intuition, leading to improved intraoperative performance. We assessed the face and content validity of a novel three-dimensional (3D) printed mandible with soft tissue component for BSSO simulation. Methods: The simulation model was created using 3D printing and silicone molding. Surgical trainees were asked to perform a simulated BSSO procedure on the simulation model, both with and without the soft tissue component. This task was repeated using a commercially available model. Pre- and post-surveys assessed trainee confidence and evaluated the face and content validity of the model. Statistical analyses compared changes in confidence. Results: The simulation model cost $43 to produce ($11 for one single-use mandible component and $32 for one reusable soft tissue component). Twelve residents, including 6 junior and 6 senior residents, participated. Residents reported a significant increase in their confidence level across all domains ( P <0.01), with first-year residents reporting the greatest increase. Almost all residents agreed or strongly agreed that the simulation model (n=11, 92%), inferior alveolar nerve (n=11, 92%), and soft tissue component (n=9, 75%) were realistic. All residents preferred the simulation model over the commercially available model for BSSO. Conclusions: Our novel mandible model with soft tissue component and inferior alveolar nerve visualization is cost-effective and provides a high-fidelity, anatomically accurate platform for surgical simulation.
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