Institute for Biomechanics, ETH Zurich, Zurich, Switzerland.
J Bone Miner Res. 2013 Dec;28(12):2601-8. doi: 10.1002/jbmr.1996.
More accurate techniques to estimate fracture risk could help reduce the burden of fractures in postmenopausal women. Although micro-finite element (µFE) simulations allow a direct assessment of bone mechanical performance, in this first clinical study we investigated whether the additional information obtained using geometrically and materially nonlinear µFE simulations allows a better discrimination between fracture cases and controls. We used patient data and high-resolution peripheral quantitative computed tomography (HRpQCT) measurements from our previous clinical study on fracture risk, which compared 100 postmenopausal women with a distal forearm fracture to 105 controls. Analyzing these data with the nonlinear µFE simulations, the odds ratio (OR) for the factor-of-risk (yield load divided by the expected fall load) was marginally higher (1.99; 95% confidence interval [CI], 1.41-2.77) than for the factor-of-risk computed from linear µFE (1.89; 95% CI, 1.37-2.69). The yield load and the energy absorbed up to the yield point as computed from nonlinear µFE were highly correlated with the initial stiffness (R(2) = 0.97 and 0.94, respectively) and could therefore be derived from linear simulations with little loss in precision. However, yield deformation was not related to any other measurement performed and was itself a good predictor of fracture risk (OR, 1.89; 95% CI, 1.39-2.63). Moreover, a combined risk score integrating information on relative bone strength (yield load-based factor-of-risk), bone ductility (yield deformation), and the structural integrity of the bone under critical loads (cortical plastic volume) improved the separation of cases and controls by one-third (OR, 2.66; 95% CI, 1.84-4.02). We therefore conclude that nonlinear µFE simulations provide important additional information on the risk of distal forearm fractures not accessible from linear µFE nor from other techniques assessing bone microstructure, density, or mass.
更精确的骨折风险估计技术可以帮助减轻绝经后妇女的骨折负担。虽然微有限元(µFE)模拟可以直接评估骨骼的机械性能,但在这项首次临床研究中,我们研究了使用几何和材料非线性µFE 模拟获得的额外信息是否可以更好地区分骨折病例和对照组。我们使用了来自我们之前关于骨折风险的临床研究的患者数据和高分辨率外周定量计算机断层扫描(HRpQCT)测量值,该研究将 100 名患有前臂远端骨折的绝经后妇女与 105 名对照组进行了比较。使用非线性 µFE 模拟分析这些数据,危险比(OR)对于风险因素(屈服载荷除以预期跌倒载荷)略高(1.99;95%置信区间 [CI],1.41-2.77)比线性 µFE 计算的风险因素(1.89;95%CI,1.37-2.69)。从非线性 µFE 计算得出的屈服载荷和屈服点之前吸收的能量与初始刚度高度相关(R²分别为 0.97 和 0.94),因此可以从线性模拟中得出,几乎没有精度损失。然而,屈服变形与任何其他测量值都没有关系,本身就是骨折风险的良好预测指标(OR,1.89;95%CI,1.39-2.63)。此外,综合风险评分整合了相对骨强度(基于屈服载荷的风险因素)、骨延展性(屈服变形)和临界载荷下骨骼结构完整性(皮质塑性体积)的信息,将病例和对照组的分离提高了三分之一(OR,2.66;95%CI,1.84-4.02)。因此,我们得出结论,非线性 µFE 模拟提供了关于远端前臂骨折风险的重要额外信息,这些信息无法从线性 µFE 或评估骨微观结构、密度或质量的其他技术中获得。