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Cluster Analysis of Finite Element Analysis and Bone Microarchitectural Parameters Identifies Phenotypes with High Fracture Risk

机译:有限元分析和骨微结构参数的聚类分析确定了高骨折风险的表型

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摘要

High-resolution peripheral quantitative computed tomography (HRpQCT) is increasingly used for exploring associations between bone microarchitectural and finite element analysis (FEA) parameters and fracture. We hypothesised that combining bone microarchitectural parameters, geometry, BMD and FEA estimates of bone strength from HRpQCT may improve discrimination of fragility fractures. The analysis sample comprised of 359 participants (aged 72–81 years) from the Hertfordshire Cohort Study. Fracture history was determined by self-report and vertebral fracture assessment. Participants underwent HRpQCT scans of the distal radius and DXA scans of the proximal femur and lateral spine. Poisson regression with robust variance estimation was used to derive relative risks for the relationship between individual bone microarchitectural and FEA parameters and previous fracture. Cluster analysis of these parameters was then performed to identify phenotypes associated with fracture prevalence. Receiver operating characteristic analysis suggested that bone microarchitectural parameters improved fracture discrimination compared to aBMD alone, whereas further inclusion of FEA parameters resulted in minimal improvements. Cluster analysis (k-means) identified four clusters. The first had lower Young modulus, cortical thickness, cortical volumetric density and Von Mises stresses compared to the wider sample; fracture rates were only significantly greater among women (relative risk [95%CI] compared to lowest risk cluster: 2.55 [1.28, 5.07], p = 0.008). The second cluster in women had greater trabecular separation, lower trabecular volumetric density and lower trabecular load with an increase in fracture rate compared to lowest risk cluster (1.93 [0.98, 3.78], p = 0.057). These findings may help inform intervention strategies for the prevention and management of osteoporosis.Electronic supplementary materialThe online version of this article (10.1007/s00223-019-00564-7) contains supplementary material, which is available to authorized users.
机译:高分辨率外围定量计算机断层扫描(HRpQCT)越来越多地用于探索骨微结构和有限元分析(FEA)参数与骨折之间的关联。我们假设结合HRpQCT的骨微结构参数,几何形状,BMD和FEA对骨强度的估计可能会改善脆性骨折的辨别力。分析样本包括来自赫特福德郡队列研究的359名参与者(年龄在72-81岁之间)。通过自我报告和椎骨骨折评估来确定骨折史。参与者进行了radius骨远端的HRpQCT扫描和股骨近端和外侧脊柱的DXA扫描。使用具有稳健方差估计的Poisson回归来得出各个骨骼微结构和FEA参数与先前骨折之间关系的相对风险。然后对这些参数进行聚类分析,以鉴定与骨折患病率相关的表型。接收器工作特性分析表明,与单独使用aBMD相比,骨微体系结构参数改善了骨折鉴别度,而进一步包含FEA参数导致的改善却很小。聚类分析(k均值)确定了四个聚类。与较宽的样品相比,第一个样品的杨氏模量,皮质厚度,皮质体积密度和冯·米塞斯应力较低。女性的骨折发生率仅显着更高(相对危险度[95%CI],最低危险度组:2.55 [1.28,5.07],p = 0.008)。与最低风险组(1.93 [0.98,3.78],p = 0.057)相比,女性的第二组具有更大的小梁间距,更低的小梁体积密度和更低的小梁负荷,并且骨折率增加。这些发现可能有助于为预防和管理骨质疏松症提供干预策略。电子补充材料本文的在线版本(10.1007 / s00223-019-00564-7)包含补充材料,授权用户可以使用。

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