Osteoporosis Clinical Research Program, University of Wisconsin-Madison, WI 53705, USA.
J Clin Densitom. 2013 Apr-Jun;16(2):154-9. doi: 10.1016/j.jocd.2012.02.007. Epub 2012 Jun 1.
This report identifies a radius dual-energy X-ray absorptiometry (DXA) confounder and technical approach to avoid this inaccuracy. Initially, a precision study revealed substantial differences (p<0.001) in radius bone mineral density (BMD) least significant change ranging from 0.038 to 0.073g/cm(2) between 3 technologists that each performed assessments in 30 men and 30 women. Subsequently, visual examination of all 360 forearm DXA images, including bone, soft tissue, neutral, and air point-typing was performed. Errors in automated "soft tissue" identification were observed; compared with the manufacturer's ideal depiction, suboptimal soft tissue point-typing was present in 30/360 scans (8.3%) involving 27 individuals. These point-typing deviations appeared to result from inclusion of forearm positioner slots at the scan field edges or clothing covering the forearm. Twenty-four individuals had a paired scan appropriately point-typed, thus allowing evaluation of the effect on BMD measurement. In those with incorrect point-typing associated with positioner slots, the mean one-third radius BMD was ∼7% higher. In conclusion, positioner slots at the edges of the distal scan field can lead to automated soft tissue identification inaccuracies and consequent erroneous one-third radius BMD measurement. DXA technologists should avoid slot inclusion in forearm scans and evaluate point-typing as part of routine analysis.
本报告确定了桡骨双能 X 射线吸收法 (DXA) 的混杂因素和避免这种不准确性的技术方法。最初,一项精度研究显示,在 3 名技术人员对 30 名男性和 30 名女性进行评估时,桡骨骨密度 (BMD) 最小有意义变化的差异很大(p<0.001),范围为 0.038 至 0.073g/cm(2)。随后,对所有 360 个前臂 DXA 图像进行了目视检查,包括骨、软组织、中立和空气点类型。观察到自动“软组织”识别中的错误;与制造商的理想描述相比,30/360 次扫描(8.3%)中存在次优的软组织点类型,涉及 27 人。这些点类型偏差似乎是由于在扫描场边缘包含前臂定位器槽或前臂覆盖衣物所致。24 人有配对扫描得到了适当的点类型,从而可以评估对 BMD 测量的影响。在那些与定位器槽相关的错误点类型的人中,三分之一桡骨 BMD 平均高出约 7%。总之,远端扫描场边缘的定位器槽会导致自动软组织识别不准确,从而导致错误的三分之一桡骨 BMD 测量。DXA 技术人员应避免在前臂扫描中包含槽,并将点类型评估作为常规分析的一部分。