Three-dimensional computation of fibre orientation, diameter and branching in segmented image stacks of fibrous networks
Three-dimensional computation of fibre orientation, diameter and branching in segmented image stacks of fibrous networks
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DOI：
10.1098/rsif.2020.0371
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发表时间：
2020-08-26
影响因子：
3.9
通讯作者：
Lake, Spencer P.
中科院分区：
文献类型：
--
作者：
Eekhoff, Jeremy D.;Lake, Spencer P.
细胞外基质的纤维形貌决定了局部力学特性和细胞行为，包括迁移和基因表达。虽然纤维网络的量化特性提供了有价值的数据，可以在广泛的生物医学学科中使用，但大多数可用的技术仅限于二维，因此不能完全捕获三维（3D）组织的结构。目前可用的3D技术具有有限的准确性和适用性，许多仅限于特定的成像模式。为了满足这一需求，我们开发了一种新的纤维分析算法，能够在具有不同纤维种群的图像堆栈中以体素为基础确定纤维方向、纤维直径和纤维分支。该技术的准确性在计算机生成的幻影图像堆栈上得到了证明，该图像堆栈跨越了一系列特征和复杂性，以及牛肌腱和真皮弹性纤维的双光子显微镜图像堆栈。此外，我们提出了一种轴向球面方差的测量方法，它可以用来定义纤维在三维方向分布中的对齐程度。该方法提供了一种有用的工具来量化具有可区分纤维或类纤维结构的图像堆栈的方向分布和方差。
Fibre topography of the extracellular matrix governs local mechanical properties and cellular behaviour including migration and gene expression. While quantifying properties of the fibrous network provides valuable data that could be used across a breadth of biomedical disciplines, most available techniques are limited to two dimensions and, therefore, do not fully capture the architecture of three-dimensional (3D) tissue. The currently available 3D techniques have limited accuracy and applicability and many are restricted to a specific imaging modality. To address this need, we developed a novel fibre analysis algorithm capable of determining fibre orientation, fibre diameter and fibre branching on a voxel-wise basis in image stacks with distinct fibre populations. The accuracy of the technique is demonstrated on computer-generated phantom image stacks spanning a range of features and complexities, as well as on two-photon microscopy image stacks of elastic fibres in bovine tendon and dermis. Additionally, we propose a measure of axial spherical variance which can be used to define the degree of fibre alignment in a distribution of 3D orientations. This method provides a useful tool to quantify orientation distributions and variance on image stacks with distinguishable fibres or fibre-like structures.