Determining skeletal muscle architecture with Laplacian simulations: a comparison with diffusion tensor imaging
Determining skeletal muscle architecture with Laplacian simulations: a comparison with diffusion tensor imaging
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DOI：
10.1007/s10237-017-0923-5
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发表时间：
2017-12-01
影响因子：
3.5
通讯作者：
Fernandez, Justin W.
中科院分区：
文献类型：
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作者：
Handsfield, Geoffrey G.;Bolsterlee, Bart;Fernandez, Justin W.
骨骼肌结构的确定对于准确地模拟肌肉行为非常重要。目前用于确定3D肌肉结构的方法可能昂贵且耗时，使得它们无法在临床或建模应用中应用。拉普拉斯流动模拟等计算方法可以根据肌肉形状和腱膜位置来估计肌束的方向。然而，这种方法的准确性尚不清楚，因为它还没有对照肌肉结构确定的其他标准进行验证。在这项研究中，比较了拉普拉斯入路和扩散张量成像在8块成人腓肠肌内侧的肌肉结构。将数据集细分为训练集和验证集，并使用计算流体力学软件进行拉普拉斯模拟。在训练集中，肌肉几何形状、腱膜位置和几何流动导引的输入结果在方法之间有很好的一致性。将该方法应用于验证集，在羽状角(平均差异)或束长(平均差异0.9 mm)方面没有显著差异。因此，拉普拉斯模拟在预测健康志愿者的腓肠肌结构方面是有效的，使用的是成像衍生的肌肉形状和腱膜位置。这种方法可以作为一种工具，用于确定骨骼肌的结构，并作为其他方法的补充。
Determination of skeletal muscle architecture is important for accurately modeling muscle behavior. Current methods for 3D muscle architecture determination can be costly and time-consuming, making them prohibitive for clinical or modeling applications. Computational approaches such as Laplacian flow simulations can estimate muscle fascicle orientation based on muscle shape and aponeurosis location. The accuracy of this approach is unknown, however, since it has not been validated against other standards for muscle architecture determination. In this study, muscle architectures from the Laplacian approach were compared to those determined from diffusion tensor imaging in eight adult medial gastrocnemius muscles. The datasets were subdivided into training and validation sets, and computational fluid dynamics software was used to conduct Laplacian simulations. In training sets, inputs of muscle geometry, aponeurosis location, and geometric flow guides resulted in good agreement between methods. Application of the method to validation sets showed no significant differences in pennation angle (mean difference or fascicle length (mean difference 0.9 mm). Laplacian simulation was thus effective at predicting gastrocnemius muscle architectures in healthy volunteers using imaging-derived muscle shape and aponeurosis locations. This method may serve as a tool for determining muscle architecture in silico and as a complement to other approaches.