Regenerative Bioscience Center, Rhodes Center for ADS, University of Georgia , Athens, GA, USA.
Department of Kinesiology, University of Georgia , Athens, GA, USA.
Connect Tissue Res. 2021 Jan;62(1):4-14. doi: 10.1080/03008207.2020.1828381. Epub 2020 Oct 7.
Imaging-based metrics for analysis of biological tissues are powerful tools that can extract information such as shape, size, periodicity, and many other features to assess the requested qualities of a tissue. Muscular and osseous tissues consist of periodic structures that are directly related to their function, and so analysis of these patterns likely reflects tissue health and regeneration. A method for assessment of periodic structures is by analyzing them in the spatial frequency domain using the Fourier transform. In this paper, we present two filters which we developed in the spatial frequency domain for the purpose of analyzing musculoskeletal structures. These filters provide information about 1) the angular orientation of the tissues and 2) their periodicity. We explore periodic structural patterns in the mitochondrial network of skeletal muscles that are reflective of muscle metabolism and myogenesis; and patterns of collagen fibers in the bone that are reflective of the organization and health of bone extracellular matrix. We present an analysis of mouse skeletal muscle in healthy and injured muscles. We used a transgenic mouse that ubiquitously expresses fluorescent protein in their mitochondria and performed 2-photon microscopy to image the structures. To acquire the collagen structure of the bone we used non-linear SHG microscopy of mouse flat bone. We analyze and compare juvenile versus adult mice, which have different structural patterns. Our results indicate that these metrics can quantify musculoskeletal tissues during development and regeneration.
基于成像的生物组织分析指标是一种强大的工具，可以提取形状、大小、周期性和许多其他特征等信息，以评估组织的所需质量。肌肉和骨骼组织由与它们的功能直接相关的周期性结构组成，因此分析这些模式可能反映了组织的健康和再生。评估周期性结构的一种方法是通过在空间频域中使用傅里叶变换对其进行分析。在本文中，我们提出了两种滤波器，我们在空间频域中开发了这两种滤波器，用于分析肌肉骨骼结构。这些滤波器提供了有关以下两个方面的信息：1）组织的角度取向；2）其周期性。我们探索了骨骼肌中线粒体网络中反映肌肉代谢和肌发生的周期性结构模式；以及反映骨细胞外基质组织和健康的骨胶原纤维模式。我们对健康和受伤肌肉中的小鼠骨骼肌进行了分析。我们使用了一种在其线粒体中普遍表达荧光蛋白的转基因小鼠，并进行了双光子显微镜成像来观察这些结构。为了获取骨胶原结构，我们使用了小鼠扁平骨的非线性 SHG 显微镜。我们分析和比较了具有不同结构模式的幼年和成年小鼠。我们的结果表明，这些指标可以在发育和再生过程中定量分析肌肉骨骼组织。
