Modenese Luca, Montefiori Erica, Wang Anqi, Wesarg Stefan, Viceconti Marco, Mazzà Claudia
Department of Mechanical Engineering and INSIGNEO Institute for in silico Medicine, University of Sheffield, Sheffield, UK; Department of Civil and Environmental Engineering, Imperial College London, UK.
Department of Mechanical Engineering and INSIGNEO Institute for in silico Medicine, University of Sheffield, Sheffield, UK.
J Biomech. 2018 May 17;73:108-118. doi: 10.1016/j.jbiomech.2018.03.039. Epub 2018 Mar 30.
The generation of subject-specific musculoskeletal models of the lower limb has become a feasible task thanks to improvements in medical imaging technology and musculoskeletal modelling software. Nevertheless, clinical use of these models in paediatric applications is still limited for what concerns the estimation of muscle and joint contact forces. Aiming to improve the current state of the art, a methodology to generate highly personalized subject-specific musculoskeletal models of the lower limb based on magnetic resonance imaging (MRI) scans was codified as a step-by-step procedure and applied to data from eight juvenile individuals. The generated musculoskeletal models were used to simulate 107 gait trials using stereophotogrammetric and force platform data as input. To ensure completeness of the modelling procedure, muscles' architecture needs to be estimated. Four methods to estimate muscles' maximum isometric force and two methods to estimate musculotendon parameters (optimal fiber length and tendon slack length) were assessed and compared, in order to quantify their influence on the models' output. Reported results represent the first comprehensive subject-specific model-based characterization of juvenile gait biomechanics, including profiles of joint kinematics and kinetics, muscle forces and joint contact forces. Our findings suggest that, when musculotendon parameters were linearly scaled from a reference model and the muscle force-length-velocity relationship was accounted for in the simulations, realistic knee contact forces could be estimated and these forces were not sensitive the method used to compute muscle maximum isometric force.
由于医学成像技术和肌肉骨骼建模软件的改进，生成下肢特定个体的肌肉骨骼模型已成为一项可行的任务。然而，就肌肉和关节接触力的估计而言，这些模型在儿科应用中的临床使用仍然有限。为了改进当前的技术水平，一种基于磁共振成像（MRI）扫描生成高度个性化的下肢特定个体肌肉骨骼模型的方法被编纂为一个分步程序，并应用于来自八名青少年个体的数据。生成的肌肉骨骼模型被用于以立体摄影测量和力平台数据作为输入来模拟107次步态试验。为确保建模过程的完整性，需要估计肌肉的结构。评估并比较了四种估计肌肉最大等长力的方法和两种估计肌肉肌腱参数（最佳纤维长度和肌腱松弛长度）的方法，以量化它们对模型输出的影响。报告的结果代表了首次基于特定个体模型对青少年步态生物力学进行的全面表征，包括关节运动学和动力学、肌肉力和关节接触力的概况。我们的研究结果表明，当肌肉肌腱参数从参考模型进行线性缩放并且在模拟中考虑肌肉力-长度-速度关系时，可以估计出实际的膝关节接触力，并且这些力对用于计算肌肉最大等长力的方法不敏感。
