Medical imaging and osteoporosis: fractal's lacunarity analysis of trabecular bone in MR images

A. Zaia, Roberta Eleonori, P. Maponi, R. Rossi, R. Murri
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引用次数: 23

Abstract

The aim of this study was to develop a method of MR image analysis able to provide parameter(s) sensitive to bone microarchitecture changes in aging and 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 perimenopaused, 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 different coefficients, /spl alpha/, /spl beta/, /spl gamma/, and to compute these coefficients as the solution of a least squares problem. This term of coefficients provides the 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, namely /spl beta/, may represent a standard for an evaluation of trabecular bone architecture and a potential useful parametric index in early diagnosis of osteoporosis.
医学影像与骨质疏松:MR图像中骨小梁的分形间隙分析
本研究的目的是开发一种磁共振图像分析方法,能够提供对衰老和骨质疏松症发病和进展中骨微结构变化敏感的参数。该方法的建立考虑了许多解剖和生理结构的分形特性。分形间隙分析用于确定相关参数,以区分腰椎MR图像中三种类型的骨小梁结构(健康青年、健康绝经期和骨质疏松症患者)。特别是,我们建议用双曲线模型函数来近似空隙性函数,该函数依赖于三个不同的系数,/spl alpha/, /spl beta/, /spl gamma/,并将这些系数作为最小二乘问题的解来计算。这一项系数提供了更好地表示所考虑的图像中像素质量密度变化的模型函数。本方法初步版本的临床应用表明,三个系数中的一个,即/spl β /,可能代表一个评估小梁骨结构的标准,并可能是早期诊断骨质疏松症的有用参数指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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