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Determining skeletal muscle architecture with Laplacian simulations: a comparison with diffusion tensor imaging

机译:用Laplacian模拟确定骨骼肌架构:与扩散张量成像的比较

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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.
机译:骨骼肌架构的测定对于准确建模肌肉行为非常重要。用于3D肌肉架构的目前的方法可能是昂贵且耗时的,使得它们抑制临床或建模应用。拉普拉斯流模拟等计算方法可以基于肌肉形状和腱膜变形位置来估计肌肉迷信取向。然而,这种方法的准确性未知,因为它尚未验证肌肉架构确定的其他标准。在这项研究中,将来自拉普拉斯方法的肌肉结构与八个成人内侧胃肠肌肌中的扩散张量成像确定的肌肉建筑进行比较。数据集被细分为培训和验证集,并且使用计算流体动力学软件进行拉普拉斯仿真。在训练套件中,肌肉几何形状,腱膜神经症位置和几何流导界的输入良好的方法之间产生了良好的一致性。该方法在验证集中的应用显示出钢结构角度没有显着差异(平均差异或绒毛差(平均差0.9mm)。因此,Laplacian模拟因此使用成像衍生的肌肉形状和腱膜肌肤形状预测健康志愿者的腓肠肌肌肉架构有效。该方法可以用作用于确定硅中的肌肉结构的工具,并作为对其他方法的补充。

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