School of Engineering and Computer Science, Hebrew University, Givat Ram Campus, Jerusalem, Israel 91904.
J Neurosurg. 2009 Dec;111(6):1201-6. doi: 10.3171/2009.3.JNS081457.
OBJECT: Surface-based registration (SBR) with facial surface scans has been proposed as an alternative for the commonly used fiducial-based registration in image-guided neurosurgery. Recent studies comparing the accuracy of SBR and fiducial-based registration have been based on a few targets located on the head surface rather than inside the brain and have yielded contradictory conclusions. Moreover, no visual feedback is provided with either method to inform the surgeon about the estimated target registration error (TRE) at various target locations. The goals in the present study were: 1) to quantify the SBR error in a clinical setup, 2) to estimate the targeting error for many target locations inside the brain, and 3) to create a map of the estimated TRE values superimposed on a patient's head image. METHODS: The authors randomly selected 12 patients (8 supine and 4 in a lateral position) who underwent neurosurgery with a commercial navigation system. Intraoperatively, scans of the patients' faces were acquired using a fast 3D surface scanner and aligned with their preoperative MR or CT head image. In the laboratory, the SBR accuracy was measured on the facial zone and estimated at various intracranial target locations. Contours related to different TREs were superimposed on the patient's head image and informed the surgeon about the expected anisotropic error distribution. RESULTS: The mean surface registration error in the face zone was 0.9 +/- 0.35 mm. The mean estimated TREs for targets located 60, 105, and 150 mm from the facial surface were 2.0, 3.2, and 4.5 mm, respectively. There was no difference in the estimated TRE between the lateral and supine positions. The entire registration procedure, including positioning of the scanner, surface data acquisition, and the registration computation usually required < 5 minutes. CONCLUSIONS: Surface-based registration accuracy is better in the face and frontal zones, and error increases as the target location lies further from the face. Visualization of the anisotropic TRE distribution may help the surgeon to make clinical decisions. The observed and estimated accuracies and the intraoperative registration time show that SBR using the fast surface scanner is practical and feasible in a clinical setup.
目的:与基于基准点的配准相比,基于表面的配准(SBR)利用面部表面扫描已被提议作为图像引导神经外科中常用的基准点配准的替代方法。最近比较 SBR 和基于基准点的配准准确性的研究基于头部表面上的几个而不是大脑内的目标,并且得出了相互矛盾的结论。此外,两种方法都没有提供视觉反馈来告知外科医生在各种目标位置的估计目标配准误差(TRE)。本研究的目的是:1)量化临床设置中的 SBR 误差,2)估计大脑内许多目标位置的靶向误差,3)创建叠加在患者头部图像上的估计 TRE 值的地图。
方法:作者随机选择了 12 名接受商业导航系统神经外科手术的患者(8 名仰卧位和 4 名侧卧位)。术中,使用快速 3D 表面扫描仪采集患者面部的扫描,并与术前 MR 或 CT 头部图像对齐。在实验室中,在面部区域测量 SBR 精度,并在各种颅内目标位置进行估计。与不同 TRE 相关的轮廓叠加在患者的头部图像上,告知外科医生预期的各向异性误差分布。
结果:面部区域的平均表面配准误差为 0.9 +/- 0.35 毫米。位于距面部表面 60、105 和 150 毫米的目标的平均估计 TRE 分别为 2.0、3.2 和 4.5 毫米。侧卧和仰卧位的估计 TRE 没有差异。整个注册过程,包括扫描仪的定位、表面数据采集和注册计算,通常需要 < 5 分钟。
结论:基于表面的配准精度在面部和额部区域更好,随着目标位置远离面部,误差增加。各向异性 TRE 分布的可视化可能有助于外科医生做出临床决策。观察到的和估计的准确性以及术中注册时间表明,使用快速表面扫描仪的 SBR 在临床环境中是实用且可行的。
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