In Vivo Knee Motion and ACL Biomechanics During Dynamic Activities

摘要：超过50%的患者在前交叉韧带术后10年出现了骨性关节炎的放射学证据。 重建。然而，前交叉韧带重建术后早发性骨性关节炎的病因尚不清楚。而当 以前的工作已经证明了重建后关节运动的变化，目前还不清楚这些变化是如何发生的 运动与软骨对活体载荷的局部力学反应的变化有关。此信息可能 对于理解骨性关节炎的发病至关重要，因为软骨的机械反应会影响软骨 动态平衡。与这一机制相一致，我们的试点数据表明，测量到的软骨应变高的区域 在前交叉韧带损伤和重建的患者中，软骨厚度容易减少，这是一个特征 办公自动化的特点。重要的是，这些退行性改变早在重建后18个月就观察到了。 因此，在这个建议中，我们的总体假设是部位特定的机械反应的变化 前交叉韧带损伤和重建后软骨对负荷的变化是长期软骨的预测因素 退化。具体地说，我们假设在经历高应变的软骨区域 负荷过大，早期退变将通过成分改变和软骨厚度减少来反映。因此，我们 将在四个时间点测量局部软骨应变、成分和厚度：前交叉韧带损伤后 术后3个月、1年、2年。在每个时间点， 在活体期间，将使用高速双平面摄影和mr成像来测量局部软骨应变。 正在装车。为了评估软骨退变，我们将使用mri来测量特定部位的成分变化。 (使用T1RHO和T2松弛时间)和软骨厚度。此外，我们的分析将解释相关的 生物学变量，如年龄、性别和体重指数，以及临床因素，如移植物的放置特点和 半月板受伤。除了机械因素外，关节炎症和润滑等生物因素 也可能在前交叉韧带重建后软骨退变中起作用。因此，滑液和血清将 被收集来测量炎症介质和代谢生物标志物。使用这些数据，我们将开发一个 结合力学和生物学的前交叉韧带重建后软骨退变预测模型 因素，以及其他人口统计学和临床特征，以预测软骨健康下降。 此外，这一全面的数据集将被用于开发临床表型，以识别那些高 前交叉韧带重建后软骨退化的风险。重要的是，这些表型的发育将 使靶向治疗方法侧重于外科手术、药物靶点和非 预防软骨退化的药物干预措施，如物理治疗或减肥。 因此，我们的发现将阐明改变在软骨局部力学反应中的作用。 前交叉韧带重建术后退行性变及提高对高危患者的识别和治疗 软骨退变。

Abstract: Radiographic evidence of OA is present in more than 50% of patients 10 years after ACL reconstruction. However, the etiology of early onset OA after ACL reconstruction is not well understood. While previous work has demonstrated changes in joint motion following reconstruction, it is unclear how these altered motions relate to changes in the local mechanical response of cartilage to in vivo loading. This information may be critical to understanding the onset of OA, as the mechanical response of cartilage affects cartilage homeostasis. In line with this mechanism, our pilot data indicates that regions of high cartilage strain measured in patients with ACL injury and reconstruction are susceptible to decreased cartilage thickness, a characteristic feature of OA. Importantly, these degenerative changes are observed as early as 18 months post-reconstruction. Therefore, in this proposal our overall hypothesis is that site-specific changes in the mechanical response of cartilage to loading following ACL injury and reconstruction are predictive of long-term cartilage degeneration. Specifically, we hypothesize that in regions of cartilage experiencing elevated strain during loading, early degeneration will be reflected by altered composition and decreased cartilage thickness. Thus, we will measure localized cartilage strain, composition, and thickness at four time-points: after ACL injury but prior to reconstruction, as well as at 3 months, 1 year, and 2 years after surgery. At each time point, a combination of high-speed biplanar radiography and MR imaging will be used to measure local cartilage strains during in vivo loading. To assess cartilage degeneration, we will use MRI to measure site-specific changes in composition (using T1rho and T2 relaxation times) and cartilage thickness. Additionally, our analyses will account for relevant biological variables such as age, sex, and BMI, and clinical factors such as graft placement characteristics and meniscus injuries. In addition to mechanical factors, biological factors such as joint inflammation and lubrication may also play a role in cartilage degeneration after ACL reconstruction. Therefore, synovial fluid and serum will be collected to measure inflammatory mediators and metabolic biomarkers. Using this data, we will develop a predictive model of cartilage degeneration after ACL reconstruction that utilizes both mechanical and biological factors, as well as other demographic and clinical characteristics, to predict declines in cartilage health. Furthermore, this comprehensive dataset will be used to develop clinical phenotypes to identify those at high risk for cartilage degradation after ACL reconstruction. Importantly, the development of these phenotypes will enable targeted treatment approaches focusing on surgical procedures, pharmaceutical targets, and non- pharmacological interventions such as physical therapy or weight loss in preventing cartilage degeneration. Therefore, our findings will both elucidate the role of alterations in the local mechanical response of cartilage on degeneration after ACL reconstruction and improve the identification and treatment of patients at high risk for cartilage degeneration.