Finite element analysis based on in vivo HR-pQCT images of the distal radius is associated with wrist fracture in postmenopausal women
Finite element analysis based on in vivo HR-pQCT images of the distal radius is associated with wrist fracture in postmenopausal women
复制标题
DOI：
10.1359/jbmr.071108
复制
发表时间：
2008-03-01
影响因子：
6.2
通讯作者：
Delmas, Pierre D.
中科院分区：
文献类型：
--
作者：
Boutroy, Stephanie;Van Rietbergen, Bert;Delmas, Pierre D.
通过有限元分析在体内评估的 BMD、骨微结构和骨机械特性与绝经后妇女的腕部骨折相关。简介：许多骨折发生在 BMD 正常的个体中。通过有限元分析 (FEA) 评估骨机械性能可以提高对骨折高风险人群的识别。 材料和方法：我们使用 HR-pQCT 来评估 33 名有脆性腕部骨折病史的绝经后女性和来自 OFELY 队列的 33 名年龄匹配的对照组的体积骨密度、微结构和 mu FE 衍生的桡骨骨机械性能。半径面积 BMD (aBMD) 也通过 DXA 测量。通过单变量逻辑回归分析评估密度、微结构、机械参数和骨折状态之间的关联，并表示为每个 SD 变化的 OR（95% CI）。我们还进行了主成分 (PC) 分析 (PCA)，以减少参数数量并研究它们与腕部骨折的关联 (OR)。结果：面积和体积密度、皮质厚度、小梁数量以及机械参数（例如估计失效载荷、刚度以及远端和近端部位小梁骨承载的载荷比例）与腕部骨折相关 （p < 0.05）。 PCA 揭示了五个独立的成分，共同解释了骨骼特征总变异性的 86.2%。第一个 PC 包括 FE 估计的失效载荷、面积和体积 BMD 以及皮质厚度，解释了 51% 的方差，手腕骨折的 OR = 2.49（95% CI，1.32-4.72）。其余 PC 不包含任何密度参数。第二个 PC 包括小梁结构，解释了 12% 的方差，OR = 1.82（95% CI，0.94-3.52）。第三个 PC 包括皮质骨与小梁骨承载的负载比例，由 FEA 评估，解释了 9% 的方差，OR = 1.61（95% CI，0.94-2.77）。因此，皮质骨与小梁骨承载的负荷比例似乎与腕部骨折相关，与 BMD 和微结构无关（分别包含在第一和第二 PC 中）。结论：这些结果表明，通过 mu FE 评估的骨机械特性可以提供有关骨骼脆性和骨折风险的信息，而不能单独通过 BMD 或结构测量来评估，因此可能会增强腕部骨折的预测 骨折风险。
BMD, bone microarchitecture, and bone mechanical properties assessed in vivo by finite element analysis were associated with wrist fracture in postmenopausal women.Introduction: Many fractures occur in individuals with normal BMD. Assessment of bone mechanical properties by finite element analysis (FEA) may improve identification of those at high risk for fracture.Materials and Methods: We used HR-pQCT to assess volumetric bone density, microarchitecture, and mu FE-derived bone mechanical properties at the radius in 33 postmenopausal women with a prior history of fragility wrist fracture and 33 age-matched controls from the OFELY cohort. Radius areal BMD (aBMD) was also measured by DXA. Associations between density, microarchitecture, mechanical parameters and fracture status were evaluated by univariate logistic regression analysis and expressed as ORs (with 95% CIs) per SD change. We also conducted a principal components (PCs) analysis (PCA) to reduce the number of parameters and study their association (OR) with wrist fracture.Results: Areal and volumetric densities, cortical thickness, trabecular number, and mechanical parameters such as estimated failure load, stiffness, and the proportion of load carried by the trabecular bone at the distal and proximal sites were associated with wrist fracture (p < 0.05). The PCA revealed five independent components that jointly explained 86.2% of the total variability of bone characteristics. The first PC included FE-estimated failure load, areal and volumetric BMD, and cortical thickness, explaining 51% of the variance with an OR for wrist fracture = 2.49 (95% CI, 1.32-4.72). Remaining PCs did not include any density parameters. The second PC included trabecular architecture, explaining 12% of the variance, with an OR = 1.82 (95% CI, 0.94-3.52). The third PC included the proportion of the load carried by cortical versus trabecular bone, assessed by FEA, explaining 9% of the variance, and had an OR = 1.61 (95% CI, 0.94-2.77). Thus, the proportion of load carried by cortical versus trabecular bone seems to be associated with wrist fracture independently of BMD and microarchitecture (included in the first and second PC, respectively).Conclusions: These results suggest that bone mechanical properties assessed by mu FE may provide information about skeletal fragility and fracture risk not assessed by BMD or architecture measurements alone and are therefore likely to enhance the prediction of wrist fracture risk.