Department of Electrical and Computer Engineering, National University of Singapore, Block E4, Level 8, Room 25, 4 Engineering Drive 3, Singapore 117583.
Acad Radiol. 2012 Oct;19(10):1273-82. doi: 10.1016/j.acra.2012.05.017.
A reliable and cost-effective method for osteoporosis screening is important in addressing the increase in osteoporotic fractures due to aging populations. Diagnostic computed tomographic (dCT) images may contain densitometric information useful for osteoporosis screening. The aim of this study was to investigate the relationship between areal bone mineral density (aBMD) and volumetric information on dCT imaging and its suitability for building an osteopenia screening system. The goal of this system is to estimate aBMD and predict bone disease condition on the basis of dCT images of the lumbar spine.
Dual-energy x-ray absorptiometry (DXA) aBMD and computed tomographic (CT) images were obtained from 44 male patients (mean age, 60 years). An aBMD from CT images (aBMD(CT)) was computed from the CT volume using established relationships of Hounsfield units to bone density and used to estimate DXA-derived aBMD (aBMD(DxA)). Estimated aBMD(CT) was then applied to diagnose osteopenia of the lumbar spine using statistical methods.
For the estimation of aBMD(DxA) from aBMD(CT), the proposed approach yielded a high correlation factor of r = 0.852, with a root mean square error of 0.0884 g/cm(2). The correlation was strongest when every slice in the dCT volume and both trabecular and cortical bone components were used. The classifier achieved an overall classification accuracy of 80.1% and an area under the receiver-operating characteristic curve of 0.894.
This clinical study demonstrates that aBMD(DxA) can be determined from routine CT data. Estimated aBMD(DxA) can be extended to form a dCT imaging-based opportunistic screening system for the detection and management of osteopenia.
由于人口老龄化，骨质疏松性骨折的发生率不断增加，因此，寻找一种可靠且经济有效的骨质疏松症筛查方法非常重要。诊断用计算机断层扫描（dCT）图像可能包含有助于骨质疏松症筛查的密度计量学信息。本研究旨在探讨基于 CT 图像的面积骨密度（aBMD）和容积信息之间的关系，及其是否适合构建骨质疏松症筛查系统。该系统的目标是基于腰椎 CT 图像估计 aBMD，并预测骨疾病状况。
从 44 名男性患者（平均年龄 60 岁）中获得双能 X 线吸收法（DXA）aBMD 和 CT 图像。通过建立 Hounsfield 单位与骨密度之间的关系，从 CT 容积中计算出 CT 图像的 aBMD（aBMD(CT)），并用于估计 DXA 衍生的 aBMD（aBMD(DxA)）。然后，应用估计的 aBMD(CT)通过统计方法诊断腰椎骨质疏松症。
对于从 aBMD(CT)估计 aBMD(DxA)，所提出的方法得到了 r = 0.852 的高相关系数，均方根误差为 0.0884 g/cm(2)。当使用 CT 容积中的每一层以及骨小梁和皮质骨成分时，相关性最强。分类器的总体分类准确率为 80.1%，受试者工作特征曲线下的面积为 0.894。
本临床研究表明，可以从常规 CT 数据中确定 aBMD(DxA)。估计的 aBMD(DxA)可以扩展为基于 dCT 成像的机会性筛查系统，用于检测和管理骨质疏松症。
