Meng Qingen, Fisher John, Wilcox Ruth
Institute of Medical and Biological Engineering, School of Mechanical Engineering, University of Leeds, Leeds, UK.
R Soc Open Sci. 2017 Aug 9;4(8):170670. doi: 10.1098/rsos.170670. eCollection 2017 Aug.
The geometry of the articular components of the knee is an important factor in predicting joint mechanics in computational models. There are a number of uncertainties in the definition of the geometry of cartilage and meniscus, and evaluating the effects of these uncertainties is fundamental to understanding the level of reliability of the models. In this study, the sensitivity of knee mechanics to geometric uncertainties was investigated by comparing polynomial-based and image-based knee models and varying the size of meniscus. The results suggested that the geometric uncertainties in cartilage and meniscus resulting from the resolution of MRI and the accuracy of segmentation caused considerable effects on the predicted knee mechanics. Moreover, even if the mathematical geometric descriptors can be very close to the imaged-based articular surfaces, the detailed contact pressure distribution produced by the mathematical geometric descriptors was not the same as that of the image-based model. However, the trends predicted by the models based on mathematical geometric descriptors were similar to those of the imaged-based models.
膝关节关节部件的几何形状是预测计算模型中关节力学的一个重要因素。软骨和半月板几何形状的定义存在诸多不确定性，评估这些不确定性的影响对于理解模型的可靠程度至关重要。在本研究中，通过比较基于多项式和基于图像的膝关节模型并改变半月板大小，研究了膝关节力学对几何不确定性的敏感性。结果表明，由MRI分辨率和分割精度导致的软骨和半月板几何不确定性对预测的膝关节力学有相当大的影响。此外，即使数学几何描述符可能与基于图像的关节表面非常接近，但数学几何描述符产生的详细接触压力分布与基于图像的模型并不相同。然而，基于数学几何描述符的模型预测趋势与基于图像的模型相似。
