Department of Orthopedic Surgery, Rush University Medical Center, Chicago, IL, USA.
Department of Research, Cleveland Clinic Akron General, Akron, OH, USA.
J Biomech. 2019 May 9;88:164-172. doi: 10.1016/j.jbiomech.2019.03.032. Epub 2019 Mar 28.
Quantifying the complex loads at the patellofemoral joint (PFJ) is vital to understanding the development of PFJ pain and osteoarthritis. Discrete element analysis (DEA) is a computationally efficient method to estimate cartilage contact stresses with potential application at the PFJ to better understand PFJ mechanics. The current study validated a DEA modeling framework driven by PFJ kinematics to predict experimentally-measured PFJ contact stress distributions. Two cadaveric knee specimens underwent quadriceps muscle [215 N] and joint compression [350 N] forces at ten discrete knee positions representing PFJ positions during early gait while measured PFJ kinematics were used to drive specimen-specific DEA models. DEA-computed contact stress and area were compared to experimentally-measured data. There was good agreement between computed and measured mean and peak stress across the specimens and positions (r = 0.63-0.85). DEA-computed mean stress was within an average of 12% (range: 1-47%) of the experimentally-measured mean stress while DEA-computed peak stress was within an average of 22% (range: 1-40%). Stress magnitudes were within the ranges measured (0.17-1.26 MPa computationally vs 0.12-1.13 MPa experimentally). DEA-computed areas overestimated measured areas (average error = 60%; range: 4-117%) with magnitudes ranging from 139 to 307 mm computationally vs 74-194 mm experimentally. DEA estimates of the ratio of lateral to medial patellofemoral stress distribution predicted the experimental data well (mean error = 15%) with minimal measurement bias. These results indicate that kinematically-driven DEA models can provide good estimates of relative changes in PFJ contact stress.
量化髌股关节 (PFJ) 的复杂负荷对于了解 PFJ 疼痛和骨关节炎的发展至关重要。离散元分析 (DEA) 是一种计算效率高的方法,可用于估计软骨接触应力,并有可能应用于 PFJ 以更好地了解 PFJ 力学。本研究验证了一种由 PFJ 运动学驱动的 DEA 建模框架,以预测实验测量的 PFJ 接触应力分布。两个尸体膝关节标本在十个离散膝关节位置接受股四头肌 [215 N] 和关节压缩 [350 N] 力,这些位置代表了早期步态中的 PFJ 位置,同时使用测量的 PFJ 运动学来驱动特定于标本的 DEA 模型。将 DEA 计算的接触应力和面积与实验测量的数据进行比较。在标本和位置上,计算得到的平均和峰值应力与实验测量数据之间存在很好的一致性 (r=0.63-0.85)。DEA 计算得到的平均应力与实验测量得到的平均应力平均相差 12%(范围:1-47%),而 DEA 计算得到的峰值应力与实验测量得到的平均应力平均相差 22%(范围:1-40%)。测量得到的应力值在测量得到的范围内 (0.17-1.26 MPa 计算值与 0.12-1.13 MPa 实验值)。DEA 计算得到的面积比实验测量得到的面积高估了 (平均误差为 60%;范围:4-117%),计算值范围为 139-307mm2,实验值范围为 74-194mm2。DEA 估计的外侧与内侧髌股压力分布比很好地预测了实验数据(平均误差为 15%),测量偏差最小。这些结果表明,运动学驱动的 DEA 模型可以很好地估计 PFJ 接触应力的相对变化。