NUTRIM, Department of Human Movement Sciences, Maastricht University Medical Centre, The Netherlands.
BMC Musculoskelet Disord. 2011 Nov 10;12:256. doi: 10.1186/1471-2474-12-256.
Currently, custom foot and ankle orthosis prescription and design tend to be based on traditional techniques, which can result in devices which vary greatly between clinicians and repeat prescription. The use of computational models of the foot may give further insight in the biomechanical effects of these devices and allow a more standardised approach to be taken to their design, however due to the complexity of the foot the models must be highly detailed and dynamic.
METHODS/DESIGN: Functional and anatomical datasets will be collected in a multicentre study from 10 healthy participants and 15 patients requiring orthotic devices. The patient group will include individuals with metarsalgia, flexible flat foot and drop foot.Each participant will undergo a clinical foot function assessment, 3D surface scans of the foot under different loading conditions, and detailed gait analysis including kinematic, kinetic, muscle activity and plantar pressure measurements in both barefoot and shod conditions. Following this each participant will undergo computed tomography (CT) imaging of their foot and ankle under a range of loads and positions while plantar pressures are recorded. A further subgroup of participants will undergo magnetic resonance imaging (MRI) of the foot and ankle.Imaging data will be segmented to derive the geometry of the bones and the orientation of the joint axes. Insertion points of muscles and ligaments will be determined from the MRI and CT-scans and soft tissue material properties computed from the loaded CT data in combination with the plantar pressure measurements. Gait analysis data will be used to drive the models and in combination with the 3D surface scans for scaling purposes. Predicted plantar pressures and muscle activation patterns predicted from the models will be compared to determine the validity of the models.
This protocol will lead to the generation of unique datasets which will be used to develop linked inverse dynamic and forward dynamic biomechanical foot models. These models may be beneficial in predicting the effect of and thus improving the efficacy of orthotic devices for the foot and ankle.
目前，定制足踝矫形器的处方和设计往往基于传统技术，这可能导致临床医生之间以及重复处方的设备差异很大。使用足部计算模型可以进一步了解这些设备的生物力学效应，并允许对其设计采用更标准化的方法，但是由于足部的复杂性，模型必须非常详细和动态。
方法/设计：将从 10 名健康参与者和 15 名需要矫形器的患者中进行一项多中心研究，以收集功能和解剖数据集。患者组将包括患有跖骨痛、柔性平足和垂足的个体。每位参与者将接受临床足部功能评估、不同加载条件下的足部 3D 表面扫描以及详细的步态分析，包括在赤脚和穿鞋条件下的运动学、动力学、肌肉活动和足底压力测量。在此之后，每位参与者将在记录足底压力的情况下接受足部和踝关节的一系列加载和位置的计算机断层扫描 (CT) 成像。参与者的一个亚组将接受足部和踝关节的磁共振成像 (MRI)。将对成像数据进行分割，以得出骨骼的几何形状和关节轴的方向。将从 MRI 和 CT 扫描确定肌肉和韧带的插入点，并从加载的 CT 数据结合足底压力测量值计算软组织材料特性。步态分析数据将用于驱动模型，并与 3D 表面扫描结合用于缩放。将比较从模型预测的足底压力和肌肉激活模式，以确定模型的有效性。
该方案将生成独特的数据集，这些数据集将用于开发链接的逆动力学和前向动力学生物力学足部模型。这些模型可能有助于预测矫形器对足部和踝关节的效果，从而提高其疗效。
