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The 3D-based scaling index algorithm to optimize structure analysis of trabecular bone in postmenopausal women with and without osteoporotic spine fractures

机译:基于3D的缩放指标算法,以优化骨质疏松脊柱骨折的绝经后妇女小梁骨结构分析

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The scaling index method (SIM) is a recently proposed non-linear technique to extract texture measures for the quantitative characterisation of the trabecular bone structure in high resolution magnetic resonance imaging (HR-MRI). The three-dimensional tomographic images are interpreted as a point distribution in a state space where each point (voxel) is defined by its x, y, z coordinates and the grey value. The SIM estimates local scaling properties to describe the nonlinear morphological features in this four-dimensional point distribution. Thus, it can be used for differentiating between cluster-, rod-, sheet-like and unstructured (background) image components, which makes it suitable for quantifying the microstructure of human cancellous bone. The SIM was applied to high resolution magnetic resonance images of the distal radius in patients with and without osteoporotic spine fractures in order to quantify the deterioration of bone structure. Using the receiver operator characteristic (ROC) analysis the diagnostic performance of this texture measure in differentiating patients with and without fractures was compared with bone mineral density (BMD). The SIM demonstrated the best area under the curve (AUC) value for discriminating the two groups. The reliability of our new texture measure and the validity of our results were assessed by applying bootstrapping resampling methods. The results of this study show that trabecular structure measures derived from HR-MRI of the radius in a clinical setting using a recently proposed algorithm based on a local 3D scaling index method can significantly improve the diagnostic performance in differentiating postmenopausal women with and without osteoporotic spine fractures.
机译:缩放指数方​​法(SIM)是最近提出的非线性技术,以提取高分辨率磁共振成像(HR-MRI)中的纹理表征的纹理措施。三维断层图像被解释为在每个点(Voxel)由其x,y,z坐标和灰度值定义的状态空间中的点分布。 SIM估计本地缩放属性以描述该四维点分布中的非线性形态特征。因此,它可以用于区分聚类,杆,片状和非结构化(背景)图像组分,这使得适合于量化人松质骨的微观结构。在患有骨质疏松脊柱骨折的患者的远端半径的高分辨率磁共振图像中应用了SIM,以量化骨结构的恶化。使用接收器操作员特征(ROC)分析,将这种纹理测量诊断性能与骨密度(BMD)进行比较。 SIM在曲线(AUC)值下的最佳区域展示了用于区分两组的曲线值。通过应用自动启动重采样方法评估我们新的纹理测量的可靠性和我们的结果的有效性。本研究的结果表明,使用基于本地3D缩放指数法的最近提出的算法在临床环境中衍生自半径的HR-MRI的小梁结构措施,可以显着提高鉴定绝经后妇女的诊断性能,无骨质疏松症骨折。

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