Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.
Int J Med Robot. 2013 Mar;9(1):109-18. doi: 10.1002/rcs.1459. Epub 2012 Sep 18.
Commercial image-guided surgery systems rely on the fundamental assumption that preoperative medical images represent the physical state of the patient in the operating room. The guidance display typically consists of a three-dimensional (3D) model derived from medical images and three orthogonal views of the imaging data. A challenging question in image-guided surgery is: what happens when the images used in the guidance display no longer correspond to the current geometric state of the anatomy and guidance information is still desirable?
We modify the conventional display with two techniques for incorporating a displacement field from a finite-element model into the guidance display and present a preliminary study of the effect of our method on performance with a simple surgical task. The topic of this paper is methods for conveying the computational model solution, not the model itself. To address the integration of the computational model solution into the display, a novel method of applying the deformation to the tool tip was developed, which quickly corrects for deformation but also maintains the pristine nature of the preoperative images. We compare the proposed technique to an existing method that applies the deformation field to the image volume.
A pilot study compared mean performance with our method of applying the deformation to the tool tip and the conventional technique. These methods were statistically similar with respect to accuracy of localization (p < 0.05) and amount of time (p < 0.05) required for localization of the target.
These results suggest that our new technique can be used in place of the computationally expensive task of deforming the image volume, without affecting the time or accuracy of the surgical task. Most notably, our work addresses the problem of incorporating deformation correction into the guidance display and offers a first step toward understanding its effect on surgical performance.
商业影像引导手术系统依赖于一个基本假设，即术前医学影像代表了手术室中患者的实际状态。引导显示通常由从医学影像中提取的三维（3D）模型和成像数据的三个正交视图组成。影像引导手术中的一个具有挑战性的问题是：当引导显示中使用的图像不再与解剖结构的当前几何状态相对应，但仍需要引导信息时，会发生什么情况？
我们修改了传统的显示方法，采用了两种技术，将有限元模型的位移场纳入到引导显示中，并对我们的方法在一项简单手术任务中的效果进行了初步研究。本文的主题是用于传达计算模型解决方案的方法，而不是模型本身。为了解决将计算模型解决方案集成到显示中的问题，开发了一种将变形应用于工具尖端的新方法，该方法可以快速纠正变形，但同时也保持了术前图像的原始状态。我们将提出的技术与将变形场应用于图像体积的现有技术进行了比较。
一项初步研究比较了我们将变形应用于工具尖端的方法和传统技术的平均性能。这两种方法在定位的准确性（p<0.05）和定位所需的时间（p<0.05）方面具有统计学相似性。
这些结果表明，我们的新技术可以替代对图像体积进行变形的计算密集型任务，而不会影响手术任务的时间或准确性。值得注意的是，我们的工作解决了将变形校正纳入引导显示的问题，并为理解其对手术性能的影响迈出了第一步。
