BioMEMs Sensor for Monitoring Fracture Healing

描述(由申请者提供)：美国人每年治疗近800万长骨骨折。这些骨折中约有10%无法正常愈合。许多这种骨不连或假关节是在严重或交织(高度碎裂)的情况下发生的，这种情况不能通过稳定的(膜内骨化)愈合途径进行。早期发现异常愈合将允许使用更新的更非侵入性的翻修策略，以及缓解更开放的翻修程序的技术要求。不幸的是，在骨折部位的标准放射学信息不能区分愈合途径的早期阶段，很难诊断骨折异常愈合的过程。我们已经假设，在至关重要的早期时间段的愈合可以通过监测植入的硬件机制来确定。这一假设利用了之前展示的现象，即随着愈合的进行，软组织骨痂和新形成的骨逐渐承担部分负荷，从而减轻了植入硬件的负担(和相关应变)。因此，为了解决在早期识别异常骨折愈合的迫切需求，我们开发了一种无线、感应供电(非植入式电源)、生物兼容的微型机电传感器(BioMEMS)，它能够监测植入的骨折硬件上的表面应变，并使用射频(RF)技术报告这些数据。这项开发计划寻求资金，以促进这些活动，并建立传感器的能力，以区分正常和异常骨愈合使用体外和动物模型。为了实现这些目标，我们提出了三个具体目标：1-优化传感器的结构以检测应变，2-充分表征传感器在模拟骨折和生理环境中的响应，以及3-在正常和异常骨折愈合的动物模型中实现传感器，以验证我们的指导性假设并执行严格的生物兼容性分析。总而言之，这项发展计划旨在将我们的生物微机械传感器从台式发展到活体环境。该研究计划代表了证明该设备的安全性和有效性所需的实验的合理进展。预计在该项目结束时，将获得足够的数据，以便申请在人类患者身上进行临床试验。 公共卫生相关性：美国人每年接受近800万例长骨骨折的治疗，其中约10%的骨折没有正确愈合。不幸的是，在可以采用更多非侵入性翻修策略的早期阶段，不容易诊断异常骨折愈合的过程。因此，为了解决在早期识别异常骨折愈合的迫切需要，我们开发了一种无线、感应供电(非植入式电源)和生物兼容的传感器，它能够检测骨愈合的过程并使用无线技术报告这些数据。

DESCRIPTION (provided by applicant): The American population is treated for nearly eight million long bone fractures per year. Approximately 10% of these fractures do not heal properly. Many of these non-unions or pseudoarthroses result when there is a severe or communited (highly fragmented) condition that does not proceed through a stabilized (intramembranous ossification) healing pathway. Early detection of aberrant healing would allow for newer classes of more non-invasive revision strategies to be utilized, as well as ease the technical demands of more open revision procedures. Unfortunately, the course of aberrant fracture healing is not easily diagnosed in the early time period when standard radiographic information of the fracture site is not capable of discriminating the healing pathway. We have hypothesized that healing in the critically important early time period can be determined by monitoring of the implanted hardware mechanics. This postulation leverages the previously demonstrated phenomena whereby the soft tissue callus and newly formed bone progressively assume part of the load as healing proceeds, thus reducing the burden (and associated strain) on the implanted hardware. Thus, to address the critical need of identifying aberrant fracture healing during the early time period, we have developed a wireless, inductively-powered (no implantable power source), biocompatible micro-electromechanical sensor (bioMEMS) that is capable of monitoring the surface strain on implanted bone fracture hardware and reports these data using radio frequency (RF) technology. This development proposal seeks funding to further these activities and to establish the sensor's ability to discern normal versus aberrant bone healing using in vitro and animal models. In order to achieve these goals, we propose three specific aims: 1 - to optimize the sensor's architecture for detecting strain, 2 - to fully characterize the sensor's response in a simulated fracture and physiological environments, and 3 - to implement the sensor in an animal model of normal and aberrant fracture healing to test our guiding hypothesis and perform rigorous biocompatibility analyses. In summary, this developmental proposal seeks to evolve our bioMEMs sensor from the benchtop to the in vivo environment. The research plan represents a logical progression of experiments that are required to demonstrate the safety and efficacy of the device. It is expected that at the end of this project that sufficient data will have been obtained in order to file an application for clinical trial in human patients. PUBLIC HEALTH RELEVANCE: The American population is treated for nearly eight million long bone fractures per year and approximately 10% of these fractures do not heal properly. Unfortunately, the course of aberrant fracture healing is not easily diagnosed in the early time period when more non- invasive revision strategies could be employed. Thus, to address the critical need of identifying aberrant fracture healing during the early time period, we have developed a wireless, inductively-powered (no implantable power source) and biocompatible sensor that is capable of detecting the course of bone healing and reports these data using wireless technology.