Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland.
Adv Exp Med Biol. 2018;1093:93-103. doi: 10.1007/978-981-13-1396-7_8.
This chapter introduces a solution called "3X-knee" that can robustly derive 3D models of the lower extremity from 2D long leg standing X-ray radiographs for preoperative planning and postoperative treatment evaluation of total knee arthroplasty (TKA). There are three core components in 3X-knee technology: (1) a knee joint immobilization apparatus, (2) an X-ray image calibration phantom, and (3) a statistical shape model-based 2D-3D reconstruction algorithm. These three components are integrated in a systematic way in 3X-knee to derive 3D models of the complete lower extremity from 2D long leg standing X-ray radiographs acquired in weight-bearing position. More specifically, the knee joint immobilization apparatus will be used to rigidly fix the X-ray calibration phantom with respect to the underlying anatomy during the image acquisition. The calibration phantom then serves two purposes. For one side, the phantom will allow one to calibrate the projection parameters of any acquired X-ray image. For the other side, the phantom also allowsone to track positions of multiple X-ray images of the underlying anatomy without using any additional positional tracker, which is a prerequisite condition for the third component to compute patient-specific 3D models from 2D X-ray images and the associated statistical shape models. Validation studies conducted on both simulated X-ray images and on patients' X-ray data demonstrate the efficacy of the present solution.
本章介绍了一种名为“3X-knee”的解决方案，它可以从 2D 下肢全长站立位 X 射线图像中稳健地提取下肢的 3D 模型，用于全膝关节置换术（TKA）的术前规划和术后治疗评估。3X-knee 技术有三个核心组成部分：（1）膝关节固定装置，（2）X 射线图像校准体模，（3）基于统计形状模型的 2D-3D 重建算法。这三个组成部分在 3X-knee 中以系统的方式集成，以便从负重位采集的 2D 下肢全长站立位 X 射线图像中提取完整下肢的 3D 模型。更具体地说，膝关节固定装置将用于在图像采集过程中刚性地将 X 射线校准体模固定在基础解剖结构上。校准体模有两个用途。一方面，体模可以校准任何采集的 X 射线图像的投影参数。另一方面，体模还可以在不使用任何额外位置跟踪器的情况下跟踪基础解剖结构的多个 X 射线图像的位置，这是第三个组件从 2D X 射线图像和相关的统计形状模型计算患者特定 3D 模型的前提条件。在模拟 X 射线图像和患者 X 射线数据上进行的验证研究证明了该解决方案的有效性。
