Department of Neurological Surgery, University of California, San Francisco, California, USA; Skull Base and Cerebrovascular Laboratory, University of California, San Francisco, California, USA; Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, California, USA.
Department of Neurological Surgery, University of California, San Francisco, California, USA; Skull Base and Cerebrovascular Laboratory, University of California, San Francisco, California, USA.
World Neurosurg. 2019 Jun;126:359-368. doi: 10.1016/j.wneu.2019.03.099. Epub 2019 Mar 18.
Visuospatial features of neuroanatomy are likely the most difficult concepts to learn in anatomy. Three-dimensional (3D) modalities have gradually begun to supplement traditional 2-dimensionanl representations of dissections and illustrations. We have introduced and described the workflow of 2 innovative methods-photogrammetry (PGM) and structured light scanning (SLS)-which have typically been used for reverse-engineering applications. In the present study, we have described a novel application of SLS and PGM that could enhance medical education and operative planning in neurosurgery.
We have described the workflow of SLS and PGM for creating volumetric models (VMs) of neuroanatomical dissections, including the requisite equipment and software. We have also provided step-by-step procedures on how users can postprocess and refine these images according to their specifications. Finally, we applied both methods to 3 dissected hemispheres to demonstrate the quality of the VMs and their applications.
Both methods yielded VMs with suitable clarity and structural integrity for anatomical education, surgical illustration, and procedural simulation.
The application of 3D computer graphics to neurosurgical applications has shown great promise. SLS and PGM can facilitate the construction of VMs with high accuracy and quality that can be used and shared in a variety of 3D platforms. Similarly, the technical demands are not high; thus, it is plausible that neurosurgeons could become quickly proficient and enlist their use in education and surgical planning. Although SLS is preferable in settings in which high accuracy is required, PGM is a viable alternative with a short learning curve.
神经解剖学的视觉空间特征可能是最难学习的解剖学概念。三维（3D）模式已逐渐开始补充传统的解剖和插图二维表示。我们已经介绍并描述了两种创新方法——摄影测量（PGM）和结构光扫描（SLS）——的工作流程，这些方法通常用于逆向工程应用。在本研究中，我们描述了 SLS 和 PGM 的一种新应用，它可以增强神经外科学的医学教育和手术规划。
我们描述了使用 SLS 和 PGM 创建神经解剖学解剖的体积模型（VM）的工作流程，包括必要的设备和软件。我们还提供了用户如何根据自己的规格对这些图像进行后处理和细化的分步说明。最后，我们将这两种方法应用于 3 个解剖半球，以展示 VM 的质量及其应用。
这两种方法都生成了具有适合解剖学教育、手术插图和程序模拟所需的清晰度和结构完整性的 VM。
将 3D 计算机图形应用于神经外科应用具有很大的前景。SLS 和 PGM 可以方便地构建具有高精度和高质量的 VM，这些 VM 可以在各种 3D 平台上使用和共享。同样，技术要求不高；因此，神经外科医生可以很快熟练掌握并将其用于教育和手术规划。虽然 SLS 在需要高精度的情况下更可取，但 PGM 是一种具有较短学习曲线的可行替代方案。
