首页> 外文会议>Image Processing pt.1; Progress in Biomedical Optics and Imaging; vol.7 no.30 >Quantifying Changes in the Bone Microarchitecture using Minkowski-Functionals and Scaling Vectors: a Comparative Study
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Quantifying Changes in the Bone Microarchitecture using Minkowski-Functionals and Scaling Vectors: a Comparative Study

机译:使用Minkowski函数和缩放向量量化骨微体系结构的变化:一项比较研究

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Osteoporosis is a metabolic bone disease leading to de-mineralization and increased risk of fracture. The two major factors that determine the biomechanical competence of bone are the degree of mineralization and the micro-architectural integrity. Today, modern imaging modalities exist that allow to depict structural details of trabecular bone tissue. Recently, non-linear techniques in 2D and 3D based on the scaling vector method (SVM) and the Minkowski functionals (MF) have been introduced, which show excellent performance in predicting bone strength and fracture risk. However, little is known about the performance of the various parameters with respect to monitoring structural changes due to progression of osteoporosis or as a result of medical treatment. We test and compare the two methodologies using realistic two-dimensional simulations of bone structures, which model the effect of osteoblasts and osteoclasts on the local change of relative bone density. The partial differential equations involved in the model are solved numerically using cellular automata (CA). Different realizations with slightly varying control parameters are considered. Our results show that even small changes in the trabecular structures, which are induced by variation of a control parameter of the system, become discernible by applying both the MF and the locally adapted scaling vector method. The results obtained with SVM are superior to those obtained with the Minkowski functionals. An additive combination of both measures drastically increases the sensitivity to slight changes in bone structures. These findings may be especially important for monitoring the treatment of patients, where the early recognition of (drug-induced) changes in the trabecular structure is crucial.
机译:骨质疏松症是一种代谢性骨病,导致脱矿质和骨折风险增加。决定骨骼生物力学能力的两个主要因素是矿化程度和微结构完整性。如今,现代的影像学方法可以描绘小梁骨组织的结构细节。最近,基于缩放矢量方法(SVM)和Minkowski功能(MF)的2D和3D非线性技术已被引入,它们在预测骨强度和骨折风险方面表现出出色的性能。然而,关于监测由于骨质疏松症的进展或药物治疗引起的结构变化的各种参数的性能知之甚少。我们使用逼真的骨骼结构二维模拟测试和比较这两种方法,该模型模拟了成骨细胞和破骨细胞对相对骨密度的局部变化的影响。使用元胞自动机(CA)对模型中涉及的偏微分方程进行数值求解。考虑具有稍微变化的控制参数的不同实现。我们的结果表明,通过应用MF和局部适应的缩放矢量方法,即使是由系统控制参数的变化引起的小梁结构上的微小变化,也变得可识别。用SVM获得的结果优于用Minkowski功能获得的结果。两种措施的加和组合极大地提高了对骨骼结构轻微变化的敏感性。这些发现对于监测患者的治疗可能尤其重要,因为在这种情况下,早期识别(药物引起的)小梁结构变化至关重要。

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