Department of Orthopaedics and Rehabilitation, The University of Iowa, Iowa City, IA 52242-1088, USA.
Comput Math Methods Med. 2012;2012:767469. doi: 10.1155/2012/767469. Epub 2012 Oct 14.
Recent findings suggest that contact stress is a potent predictor of subsequent symptomatic osteoarthritis development in the knee. However, much larger numbers of knees (likely on the order of hundreds, if not thousands) need to be reliably analyzed to achieve the statistical power necessary to clarify this relationship. This study assessed the reliability of new semiautomated computational methods for estimating contact stress in knees from large population-based cohorts. Ten knees of subjects from the Multicenter Osteoarthritis Study were included. Bone surfaces were manually segmented from sequential 1.0 Tesla magnetic resonance imaging slices by three individuals on two nonconsecutive days. Four individuals then registered the resulting bone surfaces to corresponding bone edges on weight-bearing radiographs, using a semi-automated algorithm. Discrete element analysis methods were used to estimate contact stress distributions for each knee. Segmentation and registration reliabilities (day-to-day and interrater) for peak and mean medial and lateral tibiofemoral contact stress were assessed with Shrout-Fleiss intraclass correlation coefficients (ICCs). The segmentation and registration steps of the modeling approach were found to have excellent day-to-day (ICC 0.93-0.99) and good inter-rater reliability (0.84-0.97). This approach for estimating compartment-specific tibiofemoral contact stress appears to be sufficiently reliable for use in large population-based cohorts.
最近的研究结果表明，接触压力是膝关节随后出现症状性骨关节炎发展的一个有力预测指标。然而，需要对更多数量的膝关节（可能数以百计，甚至数以千计）进行可靠地分析，才能达到澄清这种关系所需的统计能力。本研究评估了新的半自动计算方法在从大型基于人群的队列中估计膝关节接触压力方面的可靠性。该研究纳入了来自多中心骨关节炎研究的 10 个膝关节。通过三个人在两天内的两个不连续的日子，从连续的 1.0 特斯拉磁共振成像切片中手动分割骨表面。然后，有四个人使用半自动算法将得到的骨表面注册到负重 X 光片上相应的骨边缘。离散元分析方法用于估计每个膝关节的接触压力分布。使用 Shout-Fleiss 组内相关系数（ICC）评估峰值和平均内侧和外侧胫股接触压力的分割和注册可靠性（每日和组间）。该建模方法的分割和注册步骤具有极好的每日可靠性（ICC 0.93-0.99）和良好的组间可靠性（0.84-0.97）。这种估计特定间室的胫股接触压力的方法似乎足够可靠，可以用于大型基于人群的队列。
