Quantitative 3D analysis of the canal network in cortical bone by micro-computed tomography.
Quantitative 3D analysis of the canal network in cortical bone by micro-computed tomography.
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DOI：
10.1002/ar.b.10024
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发表时间：
2003-09-01
影响因子：
--
通讯作者：
Hallgrimsson, B.
中科院分区：
文献类型：
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作者：
Cooper, D. M. L.;Turinsky, A. L.;Hallgrimsson, B.
皮质骨被一个相互连接的多孔管道网络穿透，这些管道促进了神经血管结构在整个皮质的分布。这个网络是大脑皮层微结构的一个组成部分，因此，随着大脑皮层的重塑，它在整个生命过程中都会经历不断的变化。到目前为止，由于方法上的障碍，对包括神经管网络在内的皮质微结构的研究在很大程度上局限于二维(2D)领域。由于扫描分辨率的不断提高，微型计算机断层扫描(MUCT)是第一种能够分辨皮质管的非破坏性成像技术。就像它在骨小梁上的应用一样，MUCT提供了一种有效的方法来量化根管网络的3D结构的各个方面。我们在这里的目的是通过提供例子，讨论可以获得的一些参数，并将这些参数与研究应用相联系，来介绍MUCT在这一应用中的使用。虽然为小梁微结构分析开发的几个参数适用于皮质孔隙度的分析，但用于估计连通性的算法不适用。我们改进了现有的基于骨架化的算法来完成这项任务。我们相信，对根管网络的尺寸和结构进行三维分析将为骨生物学的许多方面提供新的信息。例如，与管子的大小、间距和体积有关的参数对于研究骨的机械特性可能特别有用。可替换地，描述运河网络的3D架构的参数，例如运河之间的连通性，可以提供评估累积重建相关改变的手段。
Cortical bone is perforated by an interconnected network of porous canals that facilitate the distribution of neurovascular structures throughout the cortex. This network is an integral component of cortical microstructure and, therefore, undergoes continual change throughout life as the cortex is remodeled. To date, the investigation of cortical microstructure, including the canal network, has largely been limited to the two-dimensional (2D) realm due to methodological hurdles. Thanks to continuing improvements in scan resolution, micro-computed tomography (muCT) is the first nondestructive imaging technology capable of resolving cortical canals. Like its application to trabecular bone, muCT provides an efficient means of quantifying aspects of 3D architecture of the canal network. Our aim here is to introduce the use of muCT for this application by providing examples, discussing some of the parameters that can be acquired, and relating these to research applications. Although several parameters developed for the analysis of trabecular microstructure are suitable for the analysis of cortical porosity, the algorithm used to estimate connectivity is not. We adapt existing algorithms based on skeletonization for this task. We believe that 3D analysis of the dimensions and architecture of the canal network will provide novel information relevant to many aspects of bone biology. For example, parameters related to the size, spacing, and volume of the canals may be particularly useful for investigation of the mechanical properties of bone. Alternatively, parameters describing the 3D architecture of the canal network, such as connectivity between the canals, may provide a means of evaluating cumulative remodeling related change.