Non-invasive assessment of bone strength

骨骼是一种极具适应性的组织，可以在疾病或受伤后迅速重塑。骨的三维(3D)微结构是理解骨力学的关键，而计算机断层扫描(CT)的进步，加上定制的有限元(FE)分析方法，使得分析骨重建信号如何通过复杂的结构分布成为可能。自2002年以来，我的实验室在高效和准确的计算建模方面取得了重大进展。这带来了巨大的机会，通过整合技术和开发新的计算方法来促进我们对骨适应机制的理解。继续我的研究计划的长期目标，下一阶段将利用新的纵向数据集来建立各种情况下骨骼适应的基本机制。它将时间序列图像数据的分析与有限元建模相结合，直接将骨骼的生物适应与其机械和生理功能联系起来。新的方向还包括开发多模式成像方法，将磁共振成像(MRI)和CT相结合，以便可以探索关键生物组织，特别是软骨和骨的功能相互作用。*我的下一阶段研究计划有三个主要目标。首先，建立一个骨骼适应的机制模型，该模型获取了以下受试者的实验纵向数据：(I)暴露在微重力环境中六个月(国际空间站宇航员)，(Ii)通过我们的基于人群的研究代表正常衰老，以及(Iii)正在接受实验疗法以增强他们的骨骼强度。将患者特有的FE模型与测量到的局部骨微结构变化相结合，为了解骨适应的机制提供了独特的基础。第二，推进高通量图像处理，其战略是允许分析代表多年数据集的大量3D图像数据。个体之间骨骼适应的自然变异性很大，需要高通量方法来最大限度地增加连续观察的数量。第三个目标是建立以高分辨率集成硬组织和软组织测量的方法，以便能够开发代表集成关节生物力学模型的综合有限元模型来研究组织相互作用。*总体而言，本研究计划使用先进的成像和高性能有限元建模来建立组织适应的机制模型，并将其应用于通过我的实验室最近的几项研究获得的丰富的大型数据集。这一方法为理解骨适应的机制提供了重要的生物医学工程贡献。

Bone is a remarkably adaptive tissue that can rapidly remodel as a result of disease or injury. The three-dimensional (3D) microstructure of bone is key to understanding bone mechanics, and advancements of computed tomography (CT), coupled with customized finite element (FE) analysis methods, permit the analysis of how bone remodeling signals are distributed through the complex structure. Since 2002, my lab has made significant strides towards efficient and accurate computational modeling. This leads to enormous opportunities to advance our understandings of the mechanisms of bone adaptation through integration of technologies and the development of new computational approaches. Continuing with the long-term objective of my research program, this next phase will utilize novel longitudinal datasets to establish the fundamental mechanisms of bone adaptation under a variety of scenarios. It will couple analysis of time-series image data with FE modeling to directly link biological adaptations of bone to its mechanical and physiological functions. New directions also include developing multi-modal imaging approaches that integrate magnetic resonance imaging (MRI) and CT so that the functional interaction of key biological tissues, specifically cartilage and bone, can be explored. ******There are three main objectives of the next phase of my research program. First, establish a mechanistic model of bone adaptation that takes experimental longitudinal data of subjects who have (i) been exposed to microgravity for periods of six months (International Space Station astronauts), (ii) represent normal aging through our population-based study, and (iii) are undergoing experimental therapies to augment their bone strength. Coupling patient-specific FE models with measured local changes to bone microarchitecture provides a unique basis to learn about the mechanisms of bone adaptation. Second, advance high-throughput image processing, with the strategy to allow analysis of large volumes of 3D image data representing multi-year datasets. The natural variability of bone adaptation among individuals is large, and necessitates high-throughput approaches to maximum the number of serial observations. The third objective establishes methods to integrate hard and soft tissue measurements at high resolution so that comprehensive FE models can be developed that represent integrated biomechanical models of joints to study the tissue interactions. ******Overall, this research program uses advanced imaging and high-performance FE modeling to establish mechanistic models of tissue adaptation, and applies it to large, rich datasets that have been acquired through several recent studies in my lab. This approach provides an important biomedical engineering contribution toward understanding mechanisms of bone adaptation.