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A novel approach to microsurgical teaching in head and neck surgery leveraging modern 3D technologies.
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- معلومة اضافية
- المصدر:
Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
- بيانات النشر:
Original Publication: London : Nature Publishing Group, copyright 2011-
- الموضوع:
- نبذة مختصرة :
The anatomically complex and often spatially restricted conditions of anastomosis in the head and neck region cannot be adequately reproduced by training exercises on current ex vivo or small animal models. With the development of a Realistic Anatomical Condition Experience (RACE) model, complex spatial-anatomical surgical areas and the associated intraoperative complexities could be transferred into a realistic training situation in head and neck surgery. The RACE model is based on a stereolithography file generated by intraoperative use of a three-dimensional surface scanner after neck dissection and before microvascular anastomosis. Modelling of the acquired STL file using three-dimensional processing software led to the model's final design. As a result, we have successfully created an economical, sustainable and realistic model for microsurgical education and provide a step-by-step workflow that can be used in surgical and general medical education to replicate and establish comparable models. We provide an open source stereolithography file of the head-and-neck RACE model for printing for educational purposes. Once implemented in other fields of surgery and general medicine, RACE models could mark a shift in medical education as a whole, away from traditional teaching principles and towards the use of realistic and individualised simulators.
(© 2023. The Author(s).)
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- الموضوع:
Date Created: 20231122 Date Completed: 20231127 Latest Revision: 20231219
- الموضوع:
20231219
- الرقم المعرف:
PMC10663471
- الرقم المعرف:
10.1038/s41598-023-47225-2
- الرقم المعرف:
37990073
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