小梁骨磁共振成像的拓扑分析

Topological analysis of trabecular bone MR images.

作者信息

Gomberg B R, Saha P K, Song H K, Hwang S N, Wehrli F W

机构信息

Department of Bioengineering, University of Pennsylvania, Philadelphia 19104, USA.

出版信息

IEEE Trans Med Imaging. 2000 Mar;19(3):166-74. doi: 10.1109/42.845175.

DOI:10.1109/42.845175

PMID:10875701

Abstract

Recently, imaging techniques have become available which permit nondestructive analysis of the three-dimensional (3-D) architecture of trabecular bone (TB), which forms a network of interconnected plates and rods. Most osteoporotic fractures occur at locations rich in TB, which has spurred the search for architectural parameters as determinants of bone strength. In this paper, we present a new approach to quantitative characterization of the 3-D microarchitecture of TB, based on digital topology. The method classifies each voxel of the 3-D structure based on the connectivity information of neighboring voxels. Following conversion of the 3-D digital image to a skeletonized surface representation containing only one-dimensional (1-D) and two-dimensional (2-D) structures, each voxel is classified as a curve, surface, or junction. The method has been validated by means of synthesized images and has subsequently been applied to TB images from the human wrist. The topological parameters were found to predict Young's modulus (YM) for uniaxial loading, specifically, the surface-to-curve ratio was found to be the single strongest predictor of YM (r2 = 0.69). Finally, the method has been applied to TB images from a group of patients showing very large variations in topological parameters that parallel much smaller changes in bone volume fraction (BVF).

摘要

最近，成像技术已可用于对小梁骨（TB）的三维（3-D）结构进行无损分析，小梁骨形成了一个由相互连接的板和杆组成的网络。大多数骨质疏松性骨折发生在富含小梁骨的部位，这促使人们寻找作为骨强度决定因素的结构参数。在本文中，我们提出了一种基于数字拓扑的小梁骨三维微观结构定量表征新方法。该方法根据相邻体素的连通性信息对三维结构的每个体素进行分类。在将三维数字图像转换为仅包含一维（1-D）和二维（2-D）结构的骨架化表面表示后，每个体素被分类为曲线、表面或节点。该方法已通过合成图像进行了验证，随后被应用于来自人类手腕的小梁骨图像。发现拓扑参数可预测单轴加载下的杨氏模量（YM），具体而言，发现表面与曲线的比率是杨氏模量的最强单一预测因子（r2 = 0.69）。最后，该方法已应用于一组患者的小梁骨图像，这些患者的拓扑参数变化很大，而骨体积分数（BVF）的变化要小得多。