Digital Medical Research Center, Shanghai Medical School, Fudan University, and Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention, Shanghai, China.
Neurosurgery. 2011 Apr;68(4):1131-43; discussion 1143. doi: 10.1227/NEU.0b013e318209cc45.
There are many different types of errors in neuronavigation, and the reasons and results of these errors are complex. For a neurosurgeon using the neuronavigation system, it is important to have a clear understanding of when an error may occur, what the magnitude of it is, and how to avoid it or reduce its influence on the final application accuracy. In this article, we classify all the errors into 2 groups according to the working principle of neuronavigation systems. The first group contains the errors caused by the differences between the anatomic structures in the images and that of the real patient, and the second group contains the errors occurring in transforming the position of surgical tools from the patient space to the image space. Each group is further divided into 2 subgroups. We discuss 16 types of errors and classify each of them into one of the subgroups. The classification and analysis of these errors should help neurosurgeons understand the power and limits of neuronavigation systems and use them more properly.
神经导航中有许多不同类型的误差，这些误差的原因和结果都很复杂。对于使用神经导航系统的神经外科医生来说，重要的是要清楚地了解何时可能会出现误差，误差的大小是多少，以及如何避免或减少其对最终应用精度的影响。在本文中，我们根据神经导航系统的工作原理将所有误差分为 2 组。第一组包含由图像中的解剖结构与真实患者的解剖结构之间的差异引起的误差，第二组包含在将手术工具的位置从患者空间转换到图像空间时发生的误差。每组进一步分为 2 个子组。我们讨论了 16 种误差，并将每种误差归入其中一个子组。这些误差的分类和分析应该有助于神经外科医生了解神经导航系统的优缺点，并更正确地使用它们。
