Department of Biomedical Engineering, Brown University, Providence, RI 02912, United States.
Department of Orthopedics, Alpert Medical School of Brown University and Rhode Island Hospital, Providence, RI 02912, United States.
J Biomech. 2019 Jul 19;92:120-125. doi: 10.1016/j.jbiomech.2019.05.040. Epub 2019 May 29.
Accurately assessing the dynamic kinematics of the skeletal wrist could advance our understanding of the normal and pathological wrist. Biplane videoradiography (BVR) has allowed investigators to study dynamic activities in the knee, hip, and shoulder joint; however, currently, BVR has not been utilized for the wrist joint because of the challenges associated with imaging multiple overlapping bones. Therefore, our aim was to develop a BVR procedure and to quantify its accuracy for evaluation of wrist kinematics. BVR was performed on six cadaveric forearms for one neutral static and six dynamic tasks, including flexion-extension, radial-ulnar deviation, circumduction, pronation, supination, and hammering. Optical motion capture (OMC) served as the gold standard for assessing accuracy. We propose a feedforward tracking methodology, which uses a combined model of metacarpals (second and third) for initialization of the third metacarpal (MC3). BVR-calculated kinematic parameters were found to be consistent with the OMC-calculated parameters, and the BVR/OMC agreement had submillimeter and sub-degree biases in tracking individual bones as well as the overall joint's rotation and translation. All dynamic tasks (except pronation task) showed a limit of agreement within 1.5° for overall rotation, and within 1.3 mm for overall translations. Pronation task had a 2.1° and 1.4 mm limit of agreement for rotation and translation measurement. The poorest precision was achieved in calculating the pronation-supination angle, and radial-ulnar and volar-dorsal translational components, although they were sub-degree and submillimeter. The methodology described herein may assist those interested in examining the complexities of skeletal wrist function during dynamic tasks.
准确评估腕骨的动态运动学可以增进我们对正常和病理腕关节的理解。双平面影像（BVR）允许研究人员研究膝关节、髋关节和肩关节的动态活动；然而，由于与成像多个重叠骨骼相关的挑战，目前 BVR 尚未用于腕关节。因此，我们的目的是开发 BVR 程序并量化其评估腕关节运动学的准确性。BVR 对六个尸体前臂进行了一次中立静态和六次动态任务，包括屈伸、桡偏-尺偏、回旋、旋前、旋后和叩击。光学运动捕捉（OMC）作为评估准确性的金标准。我们提出了一种前馈跟踪方法，该方法使用第二和第三掌骨的组合模型来初始化第三掌骨（MC3）。BVR 计算的运动学参数与 OMC 计算的参数一致，BVR/OMC 协议在跟踪单个骨骼以及整个关节的旋转和平移方面具有亚毫米和亚度的偏差。所有动态任务（除旋前任务外）的整体旋转角度的协议范围均在 1.5°以内，整体平移角度的协议范围均在 1.3 mm 以内。旋前任务的旋转和平移测量的协议范围为 2.1°和 1.4 mm。计算旋前-旋后角度、桡偏-尺偏和掌侧-背侧平移分量的精度最差，尽管它们的偏差在亚度和亚毫米范围内。本文描述的方法可以帮助那些有兴趣研究动态任务中骨骼腕关节功能复杂性的人。
