Musculoskeletal Quantitative Imaging Research Group, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94158, USA.
Bone. 2010 Sep;47(3):519-28. doi: 10.1016/j.bone.2010.05.034. Epub 2010 May 31.
Quantitative cortical microarchitectural end points are important for understanding structure-function relations in the context of fracture risk and therapeutic efficacy. This technique study details new image-processing methods to automatically segment and directly quantify cortical density, geometry, and microarchitecture from HR-pQCT images of the distal radius and tibia. An automated segmentation technique was developed to identify the periosteal and endosteal margins of the distal radius and tibia and detect intracortical pore space morphologically consistent with Haversian canals. The reproducibility of direct quantitative cortical bone indices based on this method was assessed in a pooled data set of 56 subjects with two repeat acquisitions for each site. The in vivo precision error was characterized using root mean square coefficient of variation (RMSCV%) from which the least significant change (LSC) was calculated. Bland-Altman plots were used to characterize bias in the precision estimates. The reproducibility of cortical density and cross-sectional area measures was high (RMSCV <1% and <1.5%, respectively) with good agreement between young and elder medians. The LSC for cortical porosity (Ct.Po) was somewhat smaller in the radius (0.58%) compared with the distal tibia (0.84%) and significantly different between young and elder medians in the distal tibia (LSC: 0.75% vs. 0.92%, p<0.001). The LSC for pore diameter and distribution (Po.Dm and Po.Dm.SD) ranged between 15 and 23 microm. Bland-Altman analysis revealed moderate bias for integral measures of area and volume but not for density or microarchitecture. This study indicates that HR-pQCT measures of cortical bone density and architecture can be measured in vivo with high reproducibility and limited bias across a biologically relevant range of values. The results of this study provide informative data for the design of future clinical studies of bone quality.
定量皮质微结构终点对于理解骨折风险和治疗效果背景下的结构-功能关系非常重要。本技术研究详细介绍了新的图像处理方法,可从 HR-pQCT 桡骨和胫骨远端图像中自动分割并直接定量皮质密度、几何形状和微结构。开发了一种自动分割技术,以识别桡骨和胫骨的骨膜和骨髓腔边缘,并通过形态上与哈弗系统一致的方式检测皮质内孔空间。在一个由 56 名受试者组成的汇总数据集上,对基于该方法的直接定量皮质骨指数的可重复性进行了评估,每个部位均进行了两次重复采集。使用均方根变异系数(RMSCV%)来表征体内精度误差,从中计算出最小有意义变化(LSC)。Bland-Altman 图用于描述精度估计的偏差。皮质密度和横截面积测量的重复性很高(RMSCV<1%和<1.5%),年轻和老年中位数之间具有良好的一致性。桡骨的皮质孔隙率(Ct.Po)的 LSC 略小于胫骨(分别为 0.58%和 0.84%),并且在胫骨远端年轻和老年中位数之间存在显著差异(LSC:0.75%比 0.92%,p<0.001)。孔直径和分布(Po.Dm 和 Po.Dm.SD)的 LSC 范围在 15 到 23 微米之间。Bland-Altman 分析表明,面积和体积的整体测量值存在中度偏差,但密度或微结构不存在偏差。本研究表明,HR-pQCT 皮质骨密度和结构的测量值可以在体内以高重复性和有限的偏差在具有生物学意义的范围内进行测量。本研究的结果为骨质量的未来临床研究提供了有价值的数据。