Engineering Center for Orthopaedic Research Excellence (E-CORE), Departments of Bioengineering and Orthopaedic Surgery, University of Toledo, Toledo, OH, USA.
Motion Analysis and Integrative Neurophysiology Lab, Department of Exercise and Rehabilitation Sciences, College of Health and Human Services, University of Toledo, Toledo, Ohio, USA.
Am J Sports Med. 2023 Jul;51(8):2098-2109. doi: 10.1177/03635465231174899. Epub 2023 Jun 1.
BACKGROUND: Previous studies have examined the effect of whole body (WB) parameters on anterior cruciate ligament (ACL) strain and loads, as well as knee joint kinetics and kinematics. However, articular cartilage damage occurs in relation to ACL failure, and the effect of WB parameters on ACL strain and articular cartilage biomechanics during dynamic tasks is unclear. PURPOSES: (1) To investigate the effect of WB parameters on ACL strain, as well as articular cartilage stress and contact force, during a single-leg cross drop (SLCD) and single-leg drop (SLD). (2) To identify WB parameters predictive of high ACL strain during these tasks. STUDY DESIGN: Descriptive laboratory study. METHODS: Three-dimensional motion analysis data from 14 physically active men and women were recorded during an SLCD and SLD. OpenSim was used to obtain their kinematics, kinetics, and muscle forces for the WB model. Using these data in kinetically driven finite element simulations of the knee joint produced outputs of ACL strains and articular cartilage stresses and contact forces. Spearman correlation coefficients were used to assess relationships between WB parameters and ACL strain and cartilage biomechanics. Moreover, receiver operating characteristic curve analyses and multivariate binary logistic regressions were used to find the WB parameters that could discriminate high from low ACL strain trials. RESULTS: Correlations showed that more lumbar rotation away from the stance limb at peak ACL strain had the strongest overall association (ρ = 0.877) with peak ACL strain. Higher knee anterior shear force (ρ = 0.895) and lower gluteus maximus muscle force (ρ = 0.89) at peak ACL strain demonstrated the strongest associations with peak articular cartilage stress or contact force in ≥1 of the analyzed tasks. The regression model that used muscle forces to predict high ACL strain trials during the dominant limb SLD yielded the highest accuracy (93.5%), sensitivity (0.881), and specificity (0.952) among all regression models. CONCLUSION: WB parameters that were most consistently associated with and predictive of high ACL strain and poor articular cartilage biomechanics during the SLCD and SLD tasks included greater knee abduction angle at initial contact and higher anterior shear force at peak ACL strain, as well as lower gracilis, gluteus maximus, and medial gastrocnemius muscle forces. CLINICAL RELEVANCE: Knowledge of which landing postures create a high risk for ACL or cartilage injury may help reduce injuries in athletes by avoiding those postures and practicing the tasks with reduced high-risk motions, as well as by strengthening the muscles that protect the knee during single-leg landings.
背景：先前的研究已经检验了全身（WB）参数对前交叉韧带（ACL）应变和负荷以及膝关节运动学和运动学的影响。然而，在 ACL 失效的情况下会发生关节软骨损伤，并且在动态任务中，WB 参数对 ACL 应变和关节软骨生物力学的影响尚不清楚。
目的：（1）研究在单腿交叉下降（SLCD）和单腿下降（SLD）过程中，WB 参数对 ACL 应变以及关节软骨的应力和接触力的影响。（2）确定在这些任务中预测 ACL 高应变的 WB 参数。
研究设计：描述性实验室研究。
方法：对 14 名身体活跃的男性和女性在进行 SLCD 和 SLD 时的三维运动分析数据进行了记录。OpenSim 用于获得其 WB 模型的运动学、动力学和肌肉力量。使用这些数据对膝关节进行运动学驱动的有限元模拟，得出 ACL 应变和关节软骨应力和接触力的输出。使用 Spearman 相关系数评估 WB 参数与 ACL 应变和软骨生物力学之间的关系。此外，还使用接收者操作特征曲线分析和多元二项逻辑回归来确定可以区分高 ACL 应变试验和低 ACL 应变试验的 WB 参数。
结果：相关性表明，在 ACL 应变峰值时，腰椎向支撑腿的旋转距离越大，与 ACL 应变峰值的总体关联最强（ρ=0.877）。在 ACL 应变峰值时，膝关节前向剪切力越高（ρ=0.895）和臀大肌肌肉力越低（ρ=0.89）与分析任务中至少 1 项任务的关节软骨最大应力或接触力的关联最强。在主导肢体 SLD 中，使用肌肉力量预测高 ACL 应变试验的回归模型在所有回归模型中表现出最高的准确性（93.5%）、敏感性（0.881）和特异性（0.952）。
结论：在 SLCD 和 SLD 任务中，与 ACL 高应变和关节软骨生物力学最一致相关并具有预测性的 WB 参数包括初始接触时更大的膝关节外展角度和 ACL 应变峰值时更高的前向剪切力，以及较低的骼腰肌、臀大肌和内侧腓肠肌肌肉力量。
临床相关性：了解哪些着陆姿势会增加 ACL 或软骨受伤的风险，可能有助于通过避免这些姿势并练习降低高风险运动的任务，以及通过加强单腿着陆时保护膝盖的肌肉，来减少运动员受伤。
BMC Musculoskelet Disord. 2024-4-23
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