Three-Dimensional Photography and Computer Modeling as a Reconstructive Surgical Training Tool

三维摄影和计算机建模作为重建外科手术训练工具

阅读:2

Abstract

BACKGROUND: Reconstructive surgery operations are often complex, staged, and have a steep learning curve. As a vocational training requiring thorough three-dimensional (3D) understanding of reconstructive techniques, the use of 3D photography and computer modeling can accelerate this learning for surgical trainees. OBJECTIVES: The authors illustrate the benefits of introducing a streamlined reconstructive pathway that integrates 3D photography and computer modeling, to create a learning database for use by trainees and patients alike, to improve learning and comprehension. METHODS: A computer database of 3D photographs and associated computer models was developed for 35 patients undergoing reconstructive facial surgery at the Royal Free Hospital, London, UK. This was used as a training and teaching tool for 20 surgical trainees, with an MCQ questionnaire assessing knowledge and a Likert scale questionnaire assessing satisfaction with the understanding of core reconstructive techniques, given before and after teaching sessions. Data were analyzed using the Mann-Whitney U test for trainee knowledge and Wilcoxon rank sum test for trainee satisfaction. RESULTS: Trainee (n = 20) knowledge showed a statistically significant improvement, P < .01, as did trainee satisfaction, P < .05, after a teaching session using 3D photography and computer models for facial reconstruction. CONCLUSIONS: Three-dimensional photography and computer modeling are useful teaching and training tools for reconstructive facial surgery. The authors advocate the implementation of an integrated pathway for patients with facial defects to include 3D photography and computer modeling wherever possible, to develop internal databases for training trainees as well as patients. This algorithm can be extrapolated to other aspects of reconstructive surgery.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。