Vokes Tamara J, Pham Ann, Wilkie Joel, Kocherginsky Masha, Ma Siu-Ling, Chinander Michael, Karrison Theodore, Bris Octavia, Giger Maryellen L
Department of Medicine, University of Chicago, Chicago, IL 60637, USA.
J Clin Densitom. 2008 Apr-Jun;11(2):211-20. doi: 10.1016/j.jocd.2007.10.004. Epub 2007 Dec 26.
Radiographic texture analysis (RTA) is a computerized analysis of the spatial pattern of radiographic images used as a way of evaluating bone structure. We have shown that RTA performed on high-resolution heel images obtained using a portable densitometer differentiates subjects with and without osteoporotic fractures. In the present study, short-term precision of RTA was examined on densitometric heel images obtained from 33 subjects scanned 8 times each, with 3 observers placing a region of interest (ROI) 3 times on each image. The long-term precision was examined on images obtained from 10 subjects 3 times on each of 3 days separated by 1 week, with 2 observers placing an ROI on each image. The RTA features examined included the root mean square (RMS) variation, a measure of the contrast between the light and dark areas of the image, the first moment of the power spectrum, a measure of the spatial frequency of the trabecular pattern, and Minkowski fractal (MINK), a measure of roughness/smoothness of the trabecular pattern. The precision of the RTA features expressed as coefficient of variation ranged between the lowest of 0.5-0.7% for MINK and the highest of 14-16% for RMS. The short- and long-term precision was similar, and was not significantly influenced by repositioning and rescanning, or by ROI placement by the same or different observers. Significant sources of variability of RTA were the between-subject differences and differences between regions of the heel, but not differences due to repositioning, rescanning in the same position, or ROI placement by the same or different observers. We conclude that technical aspects of image acquisition and processing are adequate to allow further development of RTA of the densitometric images for clinical application as a method for noninvasive assessment of bone structure.
放射图像纹理分析（RTA）是一种对放射图像的空间模式进行计算机化分析的方法，用于评估骨骼结构。我们已经表明，对使用便携式骨密度仪获得的高分辨率足跟图像进行RTA，可以区分有无骨质疏松性骨折的受试者。在本研究中，对33名受试者的骨密度足跟图像进行了RTA短期精密度检查，每位受试者扫描8次，3名观察者在每张图像上放置感兴趣区域（ROI）3次。对10名受试者的图像进行了长期精密度检查，在相隔1周的3天里，每天对每位受试者的图像扫描3次，2名观察者在每张图像上放置ROI。所检查的RTA特征包括均方根（RMS）变化，它是图像明暗区域对比度的一种度量；功率谱的一阶矩，它是小梁模式空间频率的一种度量；以及闵可夫斯基分形（MINK），它是小梁模式粗糙度/平滑度的一种度量。以变异系数表示的RTA特征精密度在MINK的最低值0.5 - 0.7%到RMS的最高值14 - 16%之间。短期和长期精密度相似，并且不受重新定位和重新扫描的显著影响，也不受同一或不同观察者放置ROI的影响。RTA变异性的重要来源是受试者之间的差异以及足跟不同区域之间的差异，而不是由于重新定位、在同一位置重新扫描或同一或不同观察者放置ROI所导致的差异。我们得出结论，图像采集和处理的技术方面足以允许进一步开发用于临床应用的骨密度图像RTA，作为一种无创评估骨骼结构的方法。
