Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA 24060, USA.
Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA 24060, USA.
Acta Biomater. 2020 Apr 15;107:204-217. doi: 10.1016/j.actbio.2020.02.034. Epub 2020 Feb 25.
The mineralized skeletons of echinoderms are characterized by their complex, open-cell porous microstructure (also known as stereom), which exhibits vast variations in pore sizes, branch morphology, and three-dimensional (3D) organization patterns among different species. Quantitative description and analysis of these cellular structures in 3D are needed in order to understand their mechanical properties and underlying design strategies. In this paper series, we present a framework for analyzing such structures based on high-resolution 3D tomography data and utilize this framework to investigate the structural designs of stereom by using the spines from the sea urchin Heterocentrotus mamillatus as a model system. The first paper here reports the proposed cellular network analysis framework, which consists of five major steps: synchrotron-based tomography and hierarchical convolutional neural network-based reconstruction, machine learning-based segmentation, cellular network registration, feature extraction, and data representation and analysis. This framework enables the characterization of the porous stereom structures at the individual node and branch level (10 µm), the local cellular level (100 µm), and the global network level (~1 mm). We define and quantify multiple structural descriptors at each level, such as node connectivity, branch length and orientation, branch profile, ring structure, etc., which allows us to investigate the cellular network construction of H. mamillatus spines quantitatively. The methodology reported here could be tailored to analyze other natural or engineering open-cell porous materials for a comprehensive multiscale network representation and mechanical analysis. STATEMENT OF SIGNIFICANCE: The mechanical robustness of the biomineralized porous structures in sea urchin spines has long been recognized. However, quantitative cellular network representation and analysis of this class of natural cellular solids are still limited in the literature. This constrains our capability to fully understand the mechanical properties and design strategies in sea urchin spines and other similar echinoderms' porous skeletal structures. Combining high-resolution tomography and computer vision-based analysis, this work presents a multiscale 3D network analysis framework, which allows for extraction, registration, and quantification of sea urchin spines' complex porous structure from the individual branch and node level to the global network level. This 3D structural analysis is relevant to a diversity of research fields, such as biomineralization, skeletal biology, biomimetics, material science, etc.
棘皮动物的矿化骨骼以其复杂的、开孔多孔的微观结构（也称为立体结构）为特征，不同物种之间的孔径大小、分支形态和三维（3D）组织模式存在巨大差异。为了了解其力学性能和潜在设计策略，需要对这些细胞结构进行 3D 的定量描述和分析。在本论文系列中，我们提出了一种基于高分辨率 3D 断层扫描数据的分析此类结构的框架，并利用该框架，以海胆 H. mamillatus 的棘刺作为模型系统，研究立体结构的设计。本文首先介绍了所提出的细胞网络分析框架，该框架由五个主要步骤组成：基于同步加速器的断层扫描和基于分层卷积神经网络的重建、基于机器学习的分割、细胞网络注册、特征提取以及数据表示和分析。该框架能够在个体节点和分支水平（10μm）、局部细胞水平（100μm）和整体网络水平（~1mm）上对多孔立体结构进行特征描述。我们在每个水平上定义和量化了多个结构描述符，例如节点连通性、分支长度和方向、分支轮廓、环结构等，这使得我们能够定量研究 H. mamillatus 棘刺的细胞网络结构。这里报道的方法可以针对其他天然或工程开孔多孔材料进行定制，以进行全面的多尺度网络表示和力学分析。
海胆棘刺的生物矿化多孔结构的力学稳健性早已得到认可。然而，此类天然多孔固体的定量细胞网络表示和分析在文献中仍然有限。这限制了我们全面理解海胆棘刺和其他类似棘皮动物多孔骨骼结构的力学性能和设计策略的能力。本工作结合高分辨率断层扫描和基于计算机视觉的分析，提出了一种多尺度 3D 网络分析框架，允许从单个分支和节点水平到全局网络水平，提取、注册和量化海胆棘刺复杂多孔结构。这种 3D 结构分析与生物矿化、骨骼生物学、仿生学、材料科学等多个研究领域相关。
