Department of Mechanical Engineering & Mechanics, P.C. Rossin College of Engineering and Applied Science, Lehigh University, Bethlehem, PA, USA.
Department of Mechanical Science and Engineering, Grainger College of Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Curr Osteoporos Rep. 2023 Jun;21(3):266-277. doi: 10.1007/s11914-023-00784-9. Epub 2023 Apr 20.
The purpose of this review is to summarize insights gained by finite element (FE) model-based mechanical biomarkers of bone for in vivo assessment of bone development and adaptation, fracture risk, and fracture healing.
Muscle-driven FE models have been used to establish correlations between prenatal strains and morphological development. Postnatal ontogenetic studies have identified potential origins of bone fracture risk and quantified the mechanical environment during stereotypical locomotion and in response to increased loading. FE-based virtual mechanical tests have been used to assess fracture healing with higher fidelity than the current clinical standard; here, virtual torsion test data was a better predictor of torsional rigidity than morphometric measures or radiographic scores. Virtual mechanical biomarkers of strength have also been used to deepen the insights from both preclinical and clinical studies with predictions of strength of union at different stages of healing and reliable predictions of time to healing. Image-based FE models allow for noninvasive measurement of mechanical biomarkers in bone and have emerged as powerful tools for translational research on bone. More work to develop nonirradiating imaging techniques and validate models of bone during particularly dynamic phases (e.g., during growth and the callus region during fracture healing) will allow for continued progress in our understanding of how bone responds along the lifespan.
本文旨在总结基于有限元(FE)模型的骨力学生物标志物在活体评估骨发育和适应、骨折风险和骨折愈合方面的研究进展。
肌肉驱动的 FE 模型已被用于建立产前应变与形态发育之间的相关性。出生后发育研究确定了骨骨折风险的潜在起源,并量化了典型运动期间和增加负荷时的力学环境。基于 FE 的虚拟力学测试已被用于评估骨折愈合,其逼真度高于当前的临床标准;在这里,虚拟扭转试验数据比形态计量学测量或影像学评分更能预测扭转刚度。基于虚拟的强度力学生物标志物也被用于深入了解临床前和临床研究,预测愈合不同阶段的愈合强度,并可靠预测愈合时间。基于图像的 FE 模型允许对骨的力学生物标志物进行非侵入性测量,并已成为骨转化研究的有力工具。进一步开发非辐射成像技术和验证骨骼在特定动态阶段(例如,生长过程中和骨折愈合过程中的骨痂区域)的模型,将有助于我们持续了解骨骼在整个生命周期中的反应方式。