MR Imaging and Osteoporosis: Fractal Lacunarity Analysis of Trabecular Bone
MR Imaging and Osteoporosis: Fractal Lacunarity Analysis of Trabecular Bone
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DOI：
10.1109/titb.2006.872078
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发表时间：
2006-07
影响因子：
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通讯作者：
A. Zaia;Roberta Eleonori;P. Maponi;R. Rossi;R. Murri
中科院分区：
文献类型：
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作者：
A. Zaia;Roberta Eleonori;P. Maponi;R. Rossi;R. Murri
我们开发了一种磁共振（MR）图像分析方法，能够提供对骨微结构变化敏感的参数，以及骨质疏松症的发生和进展。该方法已建成考虑到许多解剖和生理结构的分形特性。分形空隙度分析已被用来确定相关参数，以区分三种类型的骨小梁结构（健康的年轻人，健康的围绝经期，和腰椎病患者）从腰椎MR图像。特别是，我们建议近似的空隙度函数的双曲线模型函数，取决于三个系数，α，β和γ，并计算这些系数作为最小二乘问题的解决方案。该系数三元组提供了更好地表示所考虑的图像中的像素的质量密度的变化的模型函数。初步的临床应用结果表明，β系数可作为评价骨小梁结构的标准，并可作为骨质疏松症早期诊断的参数指标
We develop a method of magnetic resonance (MR) image analysis able to provide parameter(s) sensitive to bone microarchitecture changes in aging, and to osteoporosis onset and progression. The method has been built taking into account fractal properties of many anatomic and physiologic structures. Fractal lacunarity analysis has been used to determine relevant parameter(s) to differentiate among three types of trabecular bone structure (healthy young, healthy perimenopausal, and osteoporotic patients) from lumbar vertebra MR images. In particular, we propose to approximate the lacunarity function by a hyperbola model function that depends on three coefficients, alpha,beta, and gamma, and to compute these coefficients as the solution of a least squares problem. This triplet of coefficients provides a model function that better represents the variation of mass density of pixels in the image considered. Clinical application of this preliminary version of our method suggests that one of the three coefficients, beta, may represent a standard for the evaluation of trabecular bone architecture and a potentially useful parametric index for the early diagnosis of osteoporosis