Three-Dimensional Modeling for Augmented and Virtual Reality-Based Posterior Fossa Approach Selection Training: Technical Overview of Novel Open-Source Materials.

Lucas P Carlstrom, Christopher S Graffeo, Avital Perry, Bachtri T Nguyen, Amy E Alexander, Michael J Holroyd, Maria Peris-Celda, Colin L W Driscoll, Michael J Link, Jonathan M Morris
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引用次数: 1

Abstract

Background: Selection of skull base approaches is a critical skill for complex cranial surgery, which demands nuanced understanding of neuroanatomy and pathology.

Objective: To develop novel pedagogical resources for approach selection education and assessment.

Methods: A prospectively maintained skull base registry was screened for posterior fossa tumors amenable to 3-dimensional (3D) modeling of multiple operative approaches. Inclusion criteria were high-resolution preoperative and postoperative computed tomography and MRI studies (≤1 mm) and consensus that at least 3 posterior fossa craniotomies would provide feasible access. Cases were segmented using Mimics and modeled using 3-Matic. Clinical Vignettes, Approach Selection Questionnaire, and Clinical Application Questionnaire were compiled for implementation as a teaching/testing tool.

Results: Seven cases were selected, each representing a major posterior fossa approach group. 3D models were rendered using clinical imaging for the primary operative approach, as well as a combination of laboratory neuroanatomic data and extrapolation from comparable craniotomies to generate 2 alternative approaches in each patient. Modeling data for 3D figures were uploaded to an open-sourced database in a platform-neutral fashion (.x3d) for virtual/augmented reality and 3D printing applications. A semitransparent model of each approach without pathology and with key deep structures visualized was also modeled and included for comprehensive understanding.

Conclusion: We report a novel series of open-source 3D models for skull base approach selection training, with supplemental resources. To the best of our knowledge, this is the first such series designed for pedagogical purposes in skull base surgery or centered on open-source principles.

基于增强和虚拟现实的后窝入路选择训练的三维建模:新型开源材料的技术概述。
背景:颅底入路的选择是复杂颅脑外科手术的一项关键技能,这需要对神经解剖学和病理学有细致的了解。目的:为方法选择、教育和评价开发新的教学资源。方法:对后窝肿瘤进行前瞻性的颅底登记,以适应多种手术入路的三维(3D)建模。纳入标准是术前和术后高分辨率的计算机断层扫描和MRI研究(≤1mm),并一致认为至少3次后颅窝开颅术可以提供可行的通路。使用Mimics对病例进行分割,并使用3-Matic建模。编制临床小短文、方法选择问卷和临床应用问卷作为教学/测试工具实施。结果:选择7例,分别代表一个主要的后窝入路组。利用临床影像绘制主要手术入路的3D模型,并结合实验室神经解剖学数据和可比较开颅手术的推断,为每位患者生成2个备选入路。3D图形的建模数据以平台中立的方式(.x3d)上传到开源数据库,用于虚拟/增强现实和3D打印应用。每个入路的半透明模型,没有病理和关键的深层结构可视化,也被建模和包括全面理解。结论:我们报告了一系列新颖的开源3D模型,用于颅底入路选择训练,并提供了补充资源。据我们所知,这是第一个为颅底外科教学目的或以开源原则为中心设计的系列。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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