Analysis of the Predictive Efficiency of Lumbar Vertebral Body Quantification (VBQ) and CT Hounsfield Units (HUs) for Bone Density: Age and Gender Differences

腰椎椎体定量(VBQ)和CT亨氏单位(HU)对骨密度预测效能的分析:年龄和性别差异

阅读:1

Abstract

Study DesignRetrospective Cohort Study.ObjectiveThis study examines the consistency of Vertebral Bone Quality (VBQ) and Computed Tomography Hounsfield Units (CT HUs) with Dual-energy X-ray absorptiometry (DXA) as a reference standard, evaluating the diagnostic performance of these 2 imaging techniques across different age groups and genders. Particular attention is given to the applicability of VBQ in different age and gender cohorts.MethodsWe included 972 eligible patients, from which 569 patients were randomly selected and included in the analysis according to the inclusion criteria. These patients underwent lumbar Magnetic Resonance Imaging (MRI), lumbar CT, and DXA within 3 months of hospital admission. The study assessed the correlation and diagnostic efficacy of these techniques in measuring lumbar and femoral neck bone mineral density (BMD).ResultsIt showed good correlation between VBQ and CT HUs with DXA in individuals under 70 years of age. However, in the population over 70 years, the correlation of VBQ with DXA significantly decreased (lumbar BMD pr = -.145 P > .05; femoral neck BMD r = -.097 P > .05), whereas CT HUs maintained high diagnostic performance. The ROC curve analysis indicated that the AUC for differentiating osteoporosis (based on lumbar spine BMD) by VBQ was .545 in males over 70 and .487 in females over 70. However, CT HUs demonstrated diagnostic performance across all groups.ConclusionVBQ is effective in assessing osteoporosis in patients under 70 but shows decreased efficacy in those over 70. When using VBQ to predict osteoporosis in patients on opportunistic grounds, it is still necessary to incorporate additional reference indicators, such as CT HUs.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。