Morgan Elise F, Mason Zachary D, Chien Karen B, Pfeiffer Anthony J, Barnes George L, Einhorn Thomas A, Gerstenfeld Louis C
Orthopaedic and Developmental Biomechanics Laboratory, Department of Mechanical Engineering, Boston University, Boston, MA 02215, USA.
Bone. 2009 Feb;44(2):335-44. doi: 10.1016/j.bone.2008.10.039. Epub 2008 Oct 25.
Non-invasive characterization of fracture callus structure and composition may facilitate development of surrogate measures of the regain of mechanical function. As such, quantitative computed tomography- (CT-) based analyses of fracture calluses could enable more reliable clinical assessments of bone healing. Although previous studies have used CT to quantify and predict fracture healing, it is unclear which of the many CT-derived metrics of callus structure and composition are the most predictive of callus mechanical properties. The goal of this study was to identify the changes in fracture callus structure and composition that occur over time and that are most closely related to the regain of mechanical function. Micro-computed tomography (microCT) imaging and torsion testing were performed on murine fracture calluses (n=188) at multiple post-fracture timepoints and under different experimental conditions that alter fracture healing. Total callus volume (TV), mineralized callus volume (BV), callus mineralized volume fraction (BV/TV), bone mineral content (BMC), tissue mineral density (TMD), standard deviation of mineral density (sigma(TMD)), effective polar moment of inertia (J(eff)), torsional strength, and torsional rigidity were quantified. Multivariate statistical analyses, including multivariate analysis of variance, principal components analysis, and stepwise regression were used to identify differences in callus structure and composition among experimental groups and to determine which of the microCT outcome measures were the strongest predictors of mechanical properties. Although calluses varied greatly in the absolute and relative amounts of mineralized tissue (BV, BMC, and BV/TV), differences among timepoints were most strongly associated with changes in tissue mineral density. Torsional strength and rigidity were dependent on mineral density as well as the amount of mineralized tissue: TMD, BV, and sigma(TMD) explained 62% of the variation in torsional strength (p<0.001); and TMD, BMC, BV/TV, and sigma(TMD) explained 70% of the variation in torsional rigidity (p<0.001). These results indicate that fracture callus mechanical properties can be predicted by several microCT-derived measures of callus structure and composition. These findings form the basis for developing non-invasive assessments of fracture healing and for identifying biological and biomechanical mechanisms that lead to impaired or enhanced healing.
对骨折骨痂结构和成分进行非侵入性表征可能有助于开发机械功能恢复的替代指标。因此，基于定量计算机断层扫描（CT）的骨折骨痂分析能够实现更可靠的骨愈合临床评估。尽管先前的研究已使用CT来量化和预测骨折愈合，但尚不清楚众多源自CT的骨痂结构和成分指标中哪些对骨痂力学性能的预测性最强。本研究的目的是确定骨折骨痂结构和成分随时间发生的变化，以及与机械功能恢复最密切相关的变化。在多个骨折后时间点，对小鼠骨折骨痂（n = 188）进行了微型计算机断层扫描（microCT）成像和扭转测试，并在不同实验条件下进行，这些条件会改变骨折愈合情况。对总骨痂体积（TV）、矿化骨痂体积（BV）、骨痂矿化体积分数（BV/TV）、骨矿物质含量（BMC）、组织矿物质密度（TMD）、矿物质密度标准差（sigma(TMD)）、有效极惯性矩（J(eff)）、抗扭强度和扭转刚度进行了量化。使用多变量统计分析，包括方差分析、主成分分析和逐步回归，以确定实验组之间骨痂结构和成分的差异，并确定哪些microCT结果指标是力学性能的最强预测因子。尽管骨痂矿化组织的绝对和相对量（BV、BMC和BV/TV）差异很大，但时间点之间的差异与组织矿物质密度的变化最为密切相关。抗扭强度和刚度取决于矿物质密度以及矿化组织的量：TMD、BV和sigma(TMD)解释了抗扭强度变化的62%（p < 0.001）；TMD、BMC、BV/TV和sigma(TMD)解释了扭转刚度变化的70%（p < 0.001）。这些结果表明，骨折骨痂力学性能可通过几种源自microCT的骨痂结构和成分测量指标进行预测。这些发现为开发骨折愈合的非侵入性评估以及识别导致愈合受损或增强的生物学和生物力学机制奠定了基础。
