Department of Civil and Environmental Engineering, Imperial College London, UK.
Aix-Marseille University, CNRS, ISM UMR 7287, 13009 Marseille, France.
J Biomech. 2021 Feb 12;116:110186. doi: 10.1016/j.jbiomech.2020.110186. Epub 2020 Dec 24.
The generation of personalised and patient-specific musculoskeletal models is currently a cumbersome and time-consuming task that normally requires several processing hours and trained operators. We believe that this aspect discourages the use of computational models even when appropriate data are available and personalised biomechanical analysis would be beneficial. In this paper we present a computational tool that enables the fully automatic generation of skeletal models of the lower limb from three-dimensional bone geometries, normally obtained by segmentation of medical images. This tool was evaluated against four manually created lower limb models finding remarkable agreement in the computed joint parameters, well within human operator repeatability. The coordinate systems origins were identified with maximum differences between 0.5 mm (hip joint) and 5.9 mm (subtalar joint), while the joint axes presented discrepancies between 1° (knee joint) to 11° (subtalar joint). To prove the robustness of the methodology, the models were built from four datasets including both genders, anatomies ranging from juvenile to elderly and bone geometries reconstructed from high-quality computed tomography as well as lower-quality magnetic resonance imaging scans. The entire workflow, implemented in MATLAB scripting language, executed in seconds and required no operator intervention, creating lower extremity models ready to use for kinematic and kinetic analysis or as baselines for more advanced musculoskeletal modelling approaches, of which we provide some practical examples. We auspicate that this technical advancement, together with upcoming progress in medical image segmentation techniques, will promote the use of personalised models in larger-scale studies than those hitherto undertaken.
个性化和患者特异性肌肉骨骼模型的生成目前是一项繁琐且耗时的任务，通常需要数小时的处理时间和经过培训的操作人员。我们认为，即使有合适的数据并且个性化生物力学分析将是有益的，这一方面也会阻碍计算模型的使用。在本文中，我们提出了一种计算工具，该工具能够从三维骨骼几何形状（通常通过医学图像分割获得）自动生成下肢骨骼模型。该工具针对四个手动创建的下肢模型进行了评估，发现计算出的关节参数之间存在显著的一致性，远在人类操作人员的可重复性范围内。坐标系原点的差异最大为 0.5 毫米（髋关节）至 5.9 毫米（距下关节），而关节轴之间的差异在 1°（膝关节）至 11°（距下关节）之间。为了证明该方法的稳健性，我们使用来自四个数据集的模型进行了构建，这些数据集包括男性和女性、从青少年到老年的解剖结构以及从高质量计算机断层扫描和低质量磁共振成像扫描重建的骨骼几何形状。整个工作流程在 MATLAB 脚本语言中实现，在几秒钟内执行，并且不需要操作人员干预，从而创建了可用于运动学和动力学分析的下肢模型，或者作为更高级肌肉骨骼建模方法的基线，我们提供了一些实际示例。我们希望，随着医学图像分割技术的即将取得进展，这一技术进步将促进个性化模型在比以往更大规模的研究中的使用。
