Application of the Minkowski functionals in 3D to high-resolution MR images of trabecular bone: prediction of the biomechanical strength by nonlinear topological measures

骨质疏松症 闵可夫斯基空间 小梁骨 计算机科学 松质骨 骨矿物 背景(考古学) 体素 人工智能 材料科学 数学 几何学 地质学 解剖 医学 古生物学 内分泌学
作者
Holger F. Boehm,Thomas M. Link,Roberto Monetti,Dirk Müeller,Ernst J. Rummeny,David C. Newitt,Sharmila Majumdar,C. Raeth
出处
期刊:Proceedings of SPIE 卷期号:5370: 172-172 被引量:14
标识
DOI:10.1117/12.532835
摘要

Multi-dimensional convex objects can be characterized with respect to shape, structure, and the connectivity of their components using a set of morphological descriptors known as the Minkowski functionals. In a 3D Euclidian space, these correspond to volume, surface area, mean integral curvature, and the Euler-Poincaré characteristic. We introduce the Minkowski functionals to medical image processing for the morphological analysis of trabecular bone tissue. In the context of osteoporosis-a metabolic disorder leading to a weakening of bone due to deterioration of micro-architecture-the structure of bone increasingly gains attention in the quantification of bone quality. The trabecular architecture of healthy cancellous bone consists of a complex 3D system of inter-connected mineralised elements whereas in osteoporosis the micro-structure is dominated by gaps and disconnections. At present, the standard parameter for diagnosis and assessment of fracture risk in osteoporosis is the bone mineral density (BMD) - a bulk measure of mineralisation irrespective of structural texture characteristics. With the development of modern imaging modalities (high resolution MRI, micro-CT) with spatial resolutions allowing to depict individual trabeculae bone micro-architecture has successfully been analysed using linear, 2- dimensional structural measures adopted from standard histo-morphometry. The preliminary results of our study demonstrate that due to the complex - i.e. the non-linear - network of trabecular bone structures non-linear measures in 3D are superior to linear ones in predicting mechanical properties of trabecular bone from structural information extracted from high resolution MR image data.

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