OBJECTIVE: Bone Strain Index (BSI) is a new DXA-based bone index that represents the finite element analysis of the bone deformation under load. The current study aimed to assess whether the BSI is associated with 3D microarchitecture and the mechanical behavior of human lumbar vertebrae.
METHODS: Lumbar vertebrae (L3) were harvested fresh from 31 human donors. The anteroposterior BMC (g) and aBMD (g/cm2) of the vertebral body were measured using DXA, and then the BSI was automatically derived. The trabecular bone volume (Tb.BV/TV), trabecular thickness (Tb.Th), degree of anisotropy (DA), and structure model index (SMI) were measured using µCT with a 35-µm isotropic voxel size. Quasi-static uniaxial compressive testing was performed on L3 vertebral bodies under displacement control to assess failure load and stiffness.
RESULTS: The BSI was significantly correlated with failure load and stiffness (r = -0.60 and -0.59; p < 0.0001), aBMD and BMC (r = -0.93 and -0.86; p < 0.0001); Tb.BV/TV and SMI (r = -0.58 and 0.51; p = 0.001 and 0.004 respectively). After adjustment for aBMD, the association between BSI and stiffness, BSI and SMI remained significant (r = -0.51; p = 0.004 and r = -0.39; p = 0.03 respectively, partial correlations) and the relation between BSI and failure load was close to significance (r = -0.35; p = 0.06).
CONCLUSIONS: The BSI was significantly correlated with the microarchitecture and mechanical behavior of L3 vertebrae, and these associations remained statistically significant regardless of aBMD.
目的:骨应变指数(BSI)是一种新的基于DXA的骨指数,它代表了载荷下骨变形的有限元分析。目前的研究旨在评估BSI是否与3D微结构和人体腰椎的力学行为相关。
方法:腰椎(L3)从31个人供体新鲜收获。使用DXA测量椎体的前后BMC(g)和aBMD(g/cm2),然后自动导出BSI。骨小梁体积(Tb。BV/TV),小梁厚度(Tb.Th),各向异性程度(DA),和结构模型指数(SMI)使用具有35µm各向同性体素大小的µCT测量。在位移控制下对L3椎体进行准静态单轴压缩测试,以评估破坏载荷和刚度。
结果:BSI与破坏载荷和刚度显着相关(r=-0.60和-0.59;p<0.0001),aBMD和BMC(r=-0.93和-0.86;p<0.0001);Tb。BV/TV和SMI(r=-0.58和0.51;p分别=0.001和0.004)。调整aBMD后,BSI和刚度之间的关联,BSI和SMI仍然显著(r=-0.51;p=0.004和r=-0.39;p=0.03,部分相关),BSI与失效载荷之间的关系接近显着性(r=-0.35;p=0.06)。
结论:BSI与L3椎骨的微结构和力学行为显著相关,无论aBMD如何,这些关联仍具有统计学意义.