Department of Radiology, Imaging Science and Information Systems (ISIS) Center, Georgetown University Medical Center, Washington, DC 20007, USA.
Med Phys. 2010 Oct;37(10):5298-305. doi: 10.1118/1.3475941.
C-arm based cone-beam CT (CBCT) has been recently introduced as an in-situ 3D soft tissue imaging modality. When combined with image-guided navigation, it provides a streamlined clinical workflow with, potentially, improved interventional accuracy. A key component in these systems is image to patient registration. The most common registration method relies on fiducial markers placed on the patient's skin. The fiducials are localized in the volumetric image and in the interventional environment. When using C-arm CBCT, the small spatial extent of the volumetric reconstruction makes this registration approach challenging, as the volume must include both the anatomy of interest and the fiducials. The authors have previously proposed a semiautomatic localization approach that addresses this challenge, with evaluation carried out using anthropomorphic phantoms. To truly evaluate the algorithm's utility, the evaluation must be carried out using clinical data. In this article, the authors extend the evaluation of the approach to data sets acquired in a clinical trial.
Nine CBCT data sets were obtained in three interventional radiology procedures as part of a clinical trial evaluating a commercial navigation system. Fiducials were localized in the volumetric coordinate system directly from the projection images using the evaluated localization approach. Localization was assessed using two quality measures fiducial registration error to quantify precision and fiducial localization error to quantify accuracy. The fiducials used in this study are 6 mm spheres embedded in a custom registration phantom used by the navigation system.
In all cases, the proposed approach was able to localize all five fiducial markers embedded in the registration phantom. The approach's mean (std) fiducial registration error was 0.29 (0.13) mm. The mean (std) localization difference as compared to direct volumetric localization was 0.82 (0.34) mm.
Based on the current evaluation using data from clinical cases, the authors conclude that the localization approach is sufficiently accurate for use in thoracic-abdominal interventions, and that it can simplify the current workflow while reducing cumulative radiation to the patient due to repeated CBCT scans.
C 臂锥形束 CT(CBCT)最近作为一种原位 3D 软组织成像方式被引入。当与图像引导导航结合使用时,它提供了一种简化的临床工作流程,具有潜在的提高介入准确性。这些系统的一个关键组成部分是图像到患者的配准。最常见的注册方法依赖于放置在患者皮肤上的基准标记。基准标记在容积图像和介入环境中被定位。在使用 C 臂 CBCT 时,由于体积必须包括感兴趣的解剖结构和基准标记,因此容积重建的小空间范围使得这种注册方法具有挑战性。作者之前提出了一种半自动定位方法来解决这个挑战,该方法已经在人体模型上进行了评估。为了真正评估该算法的实用性,必须使用临床数据进行评估。在本文中,作者将该方法的评估扩展到临床试验中获取的数据集。
在一项评估商业导航系统的临床试验中,作为三个介入放射学程序的一部分,共获得了 9 个 CBCT 数据集。使用评估的定位方法,直接从投影图像在容积坐标系中定位基准标记。使用两个质量度量来评估定位:基准标记注册误差用于量化精度,基准标记定位误差用于量化准确性。本研究中使用的基准标记是嵌入导航系统使用的定制注册体模中的 6 毫米球体。
在所有情况下,所提出的方法都能够定位嵌入注册体模中的所有五个基准标记。该方法的平均(标准差)基准标记注册误差为 0.29(0.13)mm。与直接容积定位相比,平均(标准差)定位差异为 0.82(0.34)mm。
基于当前使用临床病例数据的评估,作者得出结论,该定位方法在胸腹部介入中足够准确,可以简化当前的工作流程,并由于减少了重复 CBCT 扫描而减少了患者的累积辐射。