Collaborative Research: Integration of Implantable MEMS Sensors and Computational Modeling to Assess Mechanical Regulation of Bone Regeneration

合作研究：集成植入式 MEMS 传感器和计算模型来评估骨再生的机械调节

• 批准号: 1362652
• 负责人: Mark Allen
• 金额: $ 13.51万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1362652&HistoricalAwards=false
• 关键词: Collaborative; Research; Integration; Implantable; MEMS

These studies will provide a detailed characterization of the bone healing mechanical environment in vivo at both the tissue level and the local cell level. Additionally, the small scale and wireless properties of sensors advanced in this study will provide a platform to enable non-invasive quantification of the local mechanical environment for a broad range of regenerative engineering and medicine applications. Ultimately, these sensors could be utilized to transform the methods, modes, and costs of tissue replacements and enable the real time assessment of such cases as graft rejection and spinal fixation. This project will also combine an educational plan with three routes for broadening participation: (1) outreach programs in micro- and nanotechnology to K-12 participants; (2) GT-ENGAGE, a program which immerses high-school students from underrepresented groups in engineering research projects; and (3) the GT-SURE undergraduate research opportunity program. Through this approach, students across age ranges from K-college will be provided both a broad and detailed immersion in the research and technology development experience. The research objective of this award is to develop a multi-scale mechanics approach to comprehensively characterize the in vivo mechanical environment within a tissue engineered construct during regeneration. Studies conducted under this award will utilize implantable wireless microelectromechanical (MEMS) sensors, biomechanical testing, and image-based finite element modeling. Tissue engineered constructs and dynamic fixation plates will be instrumented with wireless MEMS sensors; these will then be implemented in a well-established in vivo critically sized segmental bone defect model. In vivo measurements of the local strain gradients within the engineered constructs will be measured in real time during the course of regeneration to obtain a loading history. Image-based finite element models of the local mechanical strains in regenerating bone will be created and validated using the in vivo data from the implantable MEMS sensors.

这些研究将在组织水平和局部细胞水平的体内对骨骼修复机械环境的详细表征。此外，这项研究中先进的传感器的小规模和无线特性将提供一个平台，以实现无创量化当地机械环境，以进行广泛的再生工程和医学应用。最终，这些传感器可用于改变组织置换的方法，模式和成本，并能够实时评估移植排斥和脊柱固定等情况。该项目还将将一项教育计划与以扩大参与的三种途径相结合：（1）与K-12参与者的微技术和纳米技术的外展计划； （2）GT-Engage，该计划使工程研究项目中代表性不足的小组的高中生浸入了一项计划； （3）GT-Sure本科研究机会计划。通过这种方法，各个年龄段的学生范围从K-College提供了广泛而详尽的沉浸式研究和技术开发经验。该奖项的研究目标是开发一种多尺度的力学方法，以全面地表征在再生过程中组织工程结构内的体内机械环境。根据该奖项进行的研究将利用可植入的无线微电动机电（MEMS）传感器，生物力学测试和基于图像的有限元建模。组织工程结构和动态固定板将用无线MEMS传感器进行仪器；然后，这些将在良好的体内大小的分段骨缺损模型中实现。在再生过程中，将实时测量工程结构中局部应变梯度的体内测量，以获得加载史。将使用来自可植入的MEMS传感器的体内数据创建和验证局部机械菌株的基于图像的有限元模型。