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一种基于定制图像的分析工具,用于从多光子显微镜量化人体主动脉壁中弹性蛋白和胶原的微观结构。

A custom image-based analysis tool for quantifying elastin and collagen micro-architecture in the wall of the human aorta from multi-photon microscopy.

机构信息

Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States.

Center for Vascular Remodeling and Regeneration, University of Pittsburgh, Pittsburgh, PA, United States.

出版信息

J Biomech. 2014 Mar 21;47(5):935-943. doi: 10.1016/j.jbiomech.2014.01.027. Epub 2014 Jan 20.

DOI:10.1016/j.jbiomech.2014.01.027
PMID:24524988
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4036225/
Abstract

The aorta possesses a micro-architecture that imparts and supports a high degree of compliance and mechanical strength. Alteration of the quantity and/or arrangement of the main load-bearing components of this micro-architecture--the elastin and collagen fibers--leads to mechanical, and hence functional, changes associated with aortic disease and aging. Therefore, in the future, the ability to rigorously characterize the wall fiber micro-architecture could provide insight into the complicated mechanisms of aortic wall remodeling in aging and disease. Elastin and collagen fibers can be observed using state-of-the-art multi-photon microscopy. Image-analysis algorithms have been effective at characterizing fibrous constructs using various microscopy modalities. The objective of this study was to develop a custom MATLAB-language automated image-based analysis tool to describe multiple parameters of elastin and collagen micro-architecture in human soft fibrous tissue samples using multi-photon microscopy images. Human aortic tissue samples were used to develop the code. The tool smooths, cleans and equalizes fiber intensities in the image before segmenting the fibers into a binary image. The binary image is cleaned and thinned to a fiber skeleton representation of the image. The developed software analyzes the fiber skeleton to obtain intersections, fiber orientation, concentration, porosity, diameter distribution, segment length and tortuosity. In the future, the developed custom image-based analysis tool can be used to describe the micro-architecture of aortic wall samples in a variety of conditions. While this work targeted the aorta, the software has the potential to describe the architecture of other fibrous materials, tube-like networks and connective tissues.

摘要

主动脉具有赋予并支撑高度顺应性和机械强度的微观结构。这种微观结构的主要承载成分——弹性蛋白和胶原纤维的数量和/或排列的改变,导致与主动脉疾病和衰老相关的机械和功能变化。因此,在未来,严格描述壁纤维微观结构的能力可以深入了解衰老和疾病中主动脉壁重塑的复杂机制。使用最先进的多光子显微镜可以观察到弹性蛋白和胶原纤维。图像分析算法在使用各种显微镜模式对纤维结构进行特征描述方面非常有效。本研究的目的是开发一个定制的 MATLAB 语言自动基于图像的分析工具,使用多光子显微镜图像描述人软纤维组织样本中弹性蛋白和胶原微观结构的多个参数。使用人主动脉组织样本开发了该代码。该工具在将纤维分割成二进制图像之前,对图像进行平滑、清理和纤维强度均衡处理。二进制图像经过清理和细化,得到图像的纤维骨架表示。开发的软件分析纤维骨架,以获得交点、纤维方向、浓度、孔隙率、直径分布、片段长度和扭曲度。在未来,开发的定制基于图像的分析工具可以用于描述各种条件下的主动脉壁样本的微观结构。虽然这项工作针对的是主动脉,但该软件有可能描述其他纤维材料、管状网络和结缔组织的结构。