Trauma and Orthopaedic Research Unit, The Australian National University, Canberra, Australian Capital Territory, Australia.
Faculty of Health, University of Canberra, Canberra, Australian Capital Territory, Australia.
J Orthop Res. 2020 Oct;38(10):2250-2261. doi: 10.1002/jor.24622. Epub 2020 Feb 10.
Tibiofemoral shape influences knee kinematics but little is known about the effect of shape on deep knee flexion kinematics. The aim of this study was to examine the association between tibiofemoral joint shape and kinematics during deep kneeling in patients with and without osteoarthritis (OA). Sixty-one healthy participants and 58 patients with end-stage knee OA received a computed tomography (CT) of their knee. Participants completed full flexion kneeling while being imaged using single-plane fluoroscopy. Six-degree-of-freedom kinematics were measured by registering a three-dimensional (3D)-static CT onto 2D-dynamic fluoroscopic images. Statistical shape modeling and bivariate functional principal component analysis (bfPCA) were used to describe variability in knee shape and kinematics, respectively. Random-forest-regression models were created to test the ability of shape to predict kinematics controlling for body mass index, sex, and group. The first seven modes of the shape model up to three modes of the bfPCAs captured more than 90% of the variation. The ability of the random forest models to predict kinematics from shape was low, with no more than 50% of the variation being explained in any model. Furthermore, prediction errors were high, ranging between 24.2% and 29.4% of the data. Variations in the bony morphology of the tibiofemoral joint were weakly associated with the kinematics of deep knee flexion. The models only explained a small amount of variation in the data with high error rates indicating that additional predictors need to be identified. These results contribute to the clinical understanding of knee kinematics and potentially the expectations placed on high-flexion total knee replacement design.
胫骨股骨形状会影响膝关节运动学，但对于形状对深度屈膝运动学的影响知之甚少。本研究旨在检查健康受试者和膝骨关节炎（OA）患者在深度屈膝过程中胫骨股骨关节形状与运动学之间的关联。61 名健康参与者和 58 名终末期膝骨关节炎患者接受了膝关节计算机断层扫描（CT）。参与者在接受单平面透视成像的同时完成全屈膝深度屈膝。通过将三维（3D）静态 CT 注册到 2D 动态透视图像上来测量 6 自由度运动学。统计形状建模和双变量功能主成分分析（bfPCA）分别用于描述膝关节形状和运动学的可变性。随机森林回归模型用于创建测试形状预测运动学的能力，同时控制体重指数、性别和组。形状模型的前七个模式和 bfPCAs 的前三个模式捕获了超过 90%的变化。随机森林模型从形状预测运动学的能力较低，任何模型都不能解释超过 50%的变化。此外，预测误差较高，介于数据的 24.2%和 29.4%之间。胫骨股骨关节的骨骼形态变化与深度屈膝的运动学呈弱相关。这些模型仅解释了数据中很小一部分的变化，且误差率较高，表明需要确定其他预测因素。这些结果有助于临床了解膝关节运动学，并且可能有助于对高屈曲全膝关节置换设计的期望。
