Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
The Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, Maryland, USA.
Med Phys. 2022 Sep;49(9):5715-5727. doi: 10.1002/mp.15819. Epub 2022 Jul 25.
Spinal deformation during surgical intervention (caused by patient positioning and/or the correction of malalignment) confounds conventional navigation due to the assumptions of rigid transformation. Moreover, the ability to accurately quantify spinal alignment in the operating room would provide an assessment of the surgical product via metrics that correlate with clinical outcomes.
A method for deformable 3D-2D registration of preoperative CT to intraoperative long-length tomosynthesis images is reported for an accurate 3D evaluation of device placement in the presence of spinal deformation and automated evaluation of global spinal alignment (GSA).
Long-length tomosynthesis ("Long Film," LF) images were acquired using an O-arm imaging system (Medtronic, Minneapolis USA). A deformable 3D-2D patient registration was developed using multi-scale masking (proceeding from the full-length image to local subvolumes about each vertebra) to transform vertebral labels and planning information from preoperative CT to the LF images. Automatic measurement of GSA (main thoracic kyphosis [MThK] and lumbar lordosis [LL]) was obtained using a spline fit to registered labels. The "Known-Component Registration" method for device registration was adapted to the multi-scale process for 3D device localization from orthogonal LF images. The multi-scale framework was evaluated using a deformable spine phantom in which pedicle screws were inserted, and deformations were induced over a range in LL ∼25°-80°. Further validation was carried out in a cadaver study with implanted pedicle screws and a similar range of spinal deformation. The accuracy of patient and device registration was evaluated in terms of 3D translational error and target registration error, respectively, and the accuracies of automatic GSA measurements were compared to manual annotation.
Phantom studies demonstrated accurate registration via the multi-scale framework for all vertebral levels in both the neutral and deformed spine: median (interquartile range, IQR) patient registration error was 1.1 mm (0.7-1.9 mm IQR). Automatic measures of MThK and LL agreed with manual delineation within -1.1° ± 2.2° and 0.7° ± 2.0° (mean and standard deviation), respectively. Device registration error was 0.7 mm (0.4-1.0 mm IQR) at the screw tip and 0.9° (1.0°-1.5°) about the screw trajectory. Deformable 3D-2D registration significantly outperformed conventional rigid registration (p < 0.05), which exhibited device registration errors of 2.1 mm (0.8-4.1 mm) and 4.1° (1.2°-9.5°). Cadaver studies verified performance under realistic conditions, demonstrating patient registration error of 1.6 mm (0.9-2.1 mm); MThK within -4.2° ± 6.8° and LL within 1.7° ± 3.5°; and device registration error of 0.8 mm (0.5-1.9 mm) and 0.7° (0.4°-1.2°) for the multi-scale deformable method, compared to 2.5 mm (1.0-7.9 mm) and 2.3° (1.6°-8.1°) for rigid registration (p < 0.05).
The deformable 3D-2D registration framework leverages long-length intraoperative imaging to achieve accurate patient and device registration over the extended lengths of the spine (up to 64 cm) even with strong anatomical deformation. The method offers a new means for the quantitative validation of spinal correction (intraoperative GSA measurement) and the 3D verification of device placement in comparison to preoperative images and planning data.
手术干预过程中的脊柱变形(由患者体位和/或对线矫正引起)会因刚性变换的假设而使传统导航变得混乱。此外,能够在手术室中准确地量化脊柱排列,通过与临床结果相关的指标来评估手术效果,这将提供一种评估方法。
报道一种用于将术前 CT 与术中长长度断层合成图像进行可变形 3D-2D 配准的方法,以实现存在脊柱变形情况下设备放置的准确 3D 评估,并实现全局脊柱排列(GSA)的自动评估。
使用 O 臂成像系统(美国明尼苏达州美敦力公司)获取长长度断层合成(“长片”,LF)图像。使用多尺度掩模(从全长图像到每个椎骨的局部子体积进行)开发了一种可变形的 3D-2D 患者配准方法,将椎骨标签和术前 CT 规划信息转换到 LF 图像上。使用样条拟合注册标签,自动测量 GSA(主胸曲度 [MThK] 和腰椎前凸 [LL])。适用于设备注册的“已知组件注册”方法被改编为用于从正交 LF 图像进行 3D 设备定位的多尺度过程。多尺度框架通过在 LL 范围内进行变形的椎骨标本中插入椎弓根螺钉并诱导 25°-80°的变形进行了评估。在具有植入椎弓根螺钉和类似脊柱变形范围的尸体研究中进一步验证了该方法。通过 3D 平移误差和目标注册误差分别评估患者和设备注册的准确性,并比较了自动 GSA 测量的准确性与手动标注。
在中性和变形脊柱的所有椎骨水平上,通过多尺度框架进行了准确的注册:中位数(四分位距,IQR)患者注册误差为 1.1 毫米(0.7-1.9 毫米 IQR)。MThK 和 LL 的自动测量与手动勾画的偏差在-1.1°±2.2°和 0.7°±2.0°(平均值和标准差)内,分别。螺钉尖端的设备注册误差为 0.7 毫米(0.4-1.0 毫米 IQR),螺钉轨迹周围为 0.9°(1.0°-1.5°)。可变形 3D-2D 配准明显优于传统刚性配准(p<0.05),后者的设备注册误差为 2.1 毫米(0.8-4.1 毫米)和 4.1°(1.2°-9.5°)。尸体研究在实际条件下验证了性能,表明患者注册误差为 1.6 毫米(0.9-2.1 毫米);MThK 在-4.2°±6.8°和 LL 在 1.7°±3.5°;多尺度可变形方法的设备注册误差为 0.8 毫米(0.5-1.9 毫米)和 0.7°(0.4°-1.2°),而刚性注册的误差为 2.5 毫米(1.0-7.9 毫米)和 2.3°(1.6°-8.1°)(p<0.05)。
可变形 3D-2D 配准框架利用术中长长度成像,即使在强烈的解剖变形情况下,也能实现脊柱全长(最长 64 厘米)的患者和设备的准确配准。该方法为脊柱矫正的定量验证(术中 GSA 测量)和与术前图像和规划数据相比的设备放置的 3D 验证提供了一种新方法。