基于数据的双足肌腱膜重建及其纤维分布的连续力学模拟。

IF 2.7 3区 医学 Q2 BIOPHYSICS
A. Ranjan, O. Avci, O. Röhrle
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引用次数: 0

摘要

用于确定骨骼肌纤维取向场的扩散张量成像示踪法的替代方法包括拉普拉斯流模拟。这种方法需要在肌腱和/或沿内侧腱膜处的通量边界条件(BCs),这可以显著影响所得拉普拉斯流的梯度。在此,我们提出了一种基于求解三维稳态热方程的新方法来确定双矢状肌,特别是股直肌中的纤维结构。此外,我们提出了一种半自动算法,该算法提供了前腱膜的几何表示,该算法与基于热的纤维场一起,特别适合于有限元(FE)模拟。半自动化重建的腱膜显示出良好的相关性与人工分割,产生骰子系数(DSC)为0.83。基于元模型的方法得到的通量平均角偏差为14。25°±10。36°,纤维距肌肉纵轴的倾斜度为0。44°±4。48°。比较同一股直肌几何形状的机械输出,两种不同的纤维结构表明,最重要的影响因素是相对纤维倾角。与未变形状态下的标准差(0。44°±4。48°),低负荷被动拉伸时纤维相对倾斜度的标准偏差,例如在最大负荷的30%时,有显著的减少(0。49°±2。24°)。同样,在最大等距收缩时,纤维在10%初始预拉伸时的相对倾角为0。19°±1。23、表示与未变形的外形相比,标准差有所下降(0。44°±4。48°)。目前的研究表明,尽管纤维取向和相对纤维倾斜度最初存在偏差,但基于热通量的纤维取向不仅在股骨直肌宏观分析中表现出与基于dti的纤维束状成像相当的结果,而且还导致均匀的拉伸场和改进的数值收敛。所提出的方法可以应用于确定其他双肌或多肌的内部腱膜,从而实现肌肉骨骼系统的高效计算机计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-informed reconstruction of a bipennate muscle’s aponeurosis and its fibre distribution for performing continuum-mechanical simulations

Alternatives to Diffusion-Tensor-Imaging tractography methods for determining fibre orientation fields in skeletal muscle include Laplacian flow simulations. Such methods require flux boundary conditions (BCs) at the tendons and/or along the inner aponeuroses, which can significantly influence the gradients of the resulting Laplacian flow. Herein, we propose a novel method based on solving the 3D steady-state thermal heat equations to determine the fibre architecture in a bi-pennate muscle, specifically the m. rectus femoris. Additionally, we propose a semi-automated algorithm that provides the geometrical representation of the anterior aponeurosis, which, along with the thermal-based fibre field, is particularly well suited for Finite Element (FE) simulations. The semi-automated reconstruction of the aponeurosis shows a good correlation with manual segmentation, yielding a dice coefficient (DSC) of 0.83. The metamodel-based approach resulted in fluxes with a mean angular deviation of \(14.25^\circ \,\pm \,10.36^\circ\) and a fibre inclination from the muscle’s longitudinal axis of \(0.44^\circ \,\pm \,4.48^\circ\). Comparing the mechanical output of the same m. rectus femoris muscle geometry informed by the two respective fibre architectures showed that the most significant contributing factor was the relative fibre inclination. Compared to the standard deviation in the undeformed configuration (\(0.44^\circ \,\pm \,4.48^\circ\)), the standard deviation of relative fibre inclination during passive stretching at low applied loads, for instance, at \(30\%\) of the maximum applied load, showed a significant decrease (\(0.49^\circ \,\pm \,2.24^\circ\)). Similarly, at maximum isometric contraction, the relative fibre inclinations at \(10\%\) initial fibre pre-stretch are \(0.19^\circ \,\pm \,1.23^\circ\), indicating a drop in standard deviation from the undeformed configuration (\(0.44^\circ \,\pm \,4.48^\circ\)). The current study demonstrates that despite the initial deviations in fibre orientations and relative fibre inclinations, thermal flux-based fibre orientations not only exhibit comparable results to DTI-based fibre tractography for the macroscopic analysis of the m. rectus femoris but also result in homogeneous stretch fields and improved numerical convergence. The proposed methods may be applied to determine inner aponeuroses of other bi- or multi-pennate muscles, enabling efficient in-silico computations of the musculoskeletal system.

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来源期刊
Biomechanics and Modeling in Mechanobiology
Biomechanics and Modeling in Mechanobiology 工程技术-工程:生物医学
CiteScore
7.10
自引率
8.60%
发文量
119
审稿时长
6 months
期刊介绍: Mechanics regulates biological processes at the molecular, cellular, tissue, organ, and organism levels. A goal of this journal is to promote basic and applied research that integrates the expanding knowledge-bases in the allied fields of biomechanics and mechanobiology. Approaches may be experimental, theoretical, or computational; they may address phenomena at the nano, micro, or macrolevels. Of particular interest are investigations that (1) quantify the mechanical environment in which cells and matrix function in health, disease, or injury, (2) identify and quantify mechanosensitive responses and their mechanisms, (3) detail inter-relations between mechanics and biological processes such as growth, remodeling, adaptation, and repair, and (4) report discoveries that advance therapeutic and diagnostic procedures. Especially encouraged are analytical and computational models based on solid mechanics, fluid mechanics, or thermomechanics, and their interactions; also encouraged are reports of new experimental methods that expand measurement capabilities and new mathematical methods that facilitate analysis.
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