Wireless, Self-Powered Sensors for Continuous and Long-term Monitoring of Spinal Fusion Process

项目总结 要获得更好的手术结果和涉及腰椎融合的研究需要可靠的 融合度的测定。目前的成像技术不适合准确和可靠地 确定不同程度的脊柱融合。这些治疗方法费用昂贵，并使患者面临显著的 辐射。此外，几乎所有以前开发的植入式遥测系统都包括车载 用于传感、计算、存储和无线的能量存储设备(电池和超级电容器) 沟通。电池在生物医学植入物中的使用是不合适的，因为它们的寿命有限， 大小和化学风险。其余的脊柱植入物使用射频识别(RFID)技术 或其他感应方法来询问传感器，它在组织内面临严重的限制。类似于 成像技术，目前的脊柱植入物在给定的时刻和现在评估融合状况 只是进行测量的“当时的快照”。 在这项研究中，我们建议研究一种无线、自供电的压电式浮动门的可行性。 (PFG)传感器，可通过连续记录机械使用情况来监控脊柱融合进度 在融合的整个时间过程中脊柱固定装置的性能。所提出的传感器的独特性是 手术完全由脊柱的微动提供动力，不需要植入任何 电池或任何外部电源。传感器收集的数据将使用便携式 超声波扫描仪，产生的输出将是时间演变曲线，它将与 脊髓功能单位(FSU)僵硬的变化。这些演变曲线将使临床医生能够区分 在骨性愈合的情况下，评估有效的融合期，并为更准确的种植制定时间表 在几种类型的脊柱融合术中取出。 我们这项研究的第一个目标将是设计一种完全集成的脊柱融合植入物 监控和无线数据检索功能。研究活动将涉及设计和原型制作 硅中的超声波能量采集和遥测电路，并随后验证了 使用身体模型制作的模块。挑战将是实现高能效的 遥测电路模块给出了超声波扫描仪可以传递给 一个毫米级传感器。我们的第二个目标将是台式测试，以评估PFG的性能 传感器和超声遥测接口在腰椎后路融合术中的应用 人类身体的脊椎。在身体脊柱上进行测试之前，将使用一种 椎体切除模型。在这项研究成功完成后，我们将展示急性体外培养 监测脊柱融合过程中潜在的临床相关动力学。如此强大的工具将会 支持设计下一代智能固定设备-具有自我监控功能的设备。

PROJECT SUMMARY Achieving better surgical outcomes and research studies involving lumbar spinal fusion requires reliable determination and degree of fusion. Current imaging technologies are not suitable to accurately and reliably determine different degrees of spinal fusion. These modalities are costly and expose the patient to significant radiation. In addition, nearly all of the previously developed implantable telemetry systems comprise on-board energy storage devices (batteries and super-capacitors) for sensing, computation, storage, and wireless communication. The use of batteries in biomedical implants is not suitable due to their limited life time, large size, and chemical risks. The rest of these spinal implants use radio-frequency identification (RFID) technology or other inductive methods to interrogate the sensor, which faces severe limitations inside the tissue. Similar to the imaging techniques, the current spinal implants evaluate the fusion condition at a given instant and present only a “snapshot at the time” where the measurements are taken. In this research study, we propose to investigate the feasibility of a wireless, self-powered piezo-floating-gate (PFG) sensor capable of monitoring the spinal fusion progress by continuously recording the mechanical usage of the spinal fixation device during the entire time course of fusion. The uniqueness of the proposed sensor is that the operation is completely self-powered by the micro-motion of the spine without the need for any implanted batteries or any external powering. Data collected by the sensor will be wirelessly retrieved using a portable ultrasound-scanner and the resulting output will be time-evolution curves, which will be correlated with the changes of functional spinal unit (FSU) stiffness. These evolution curves would enable clinicians to differentiate between conditions of osseous union, assess the effective fusion period, and schedule for more accurate implant removal in several types of spinal fusion procedures. Our first objective for this research will be to design a fully integrated spinal fusion implant with self-powered monitoring and wireless data retrieval capabilities. The research activity will involve designing and prototyping the ultrasonic energy harvesting and telemetry circuits in silicon and subsequently validating the functionality of the fabricated modules using a cadaver model. The challenge will be to achieve high energy efficiency of the telemetry circuit modules given the limited amount of energy that can be delivered by the ultrasound scanner to a millimeter-scale sensor. Our second objective will be bench-top testing to evaluate the performance of the PFG sensor and the ultrasonic telemetry interface for the monitoring of simulated posterior lumbar spinal fusion in human cadaver spines. Prior to testing on cadaver spines, the PFG spinal implants will be tested using a corpectomy model. Upon successful completion of this study, we will have demonstrated acute in-vitro monitoring of clinically relevant dynamics underlying the process of spinal fusion. Such a powerful tool would enable design of the next-generation, smart fixation-devices with self-monitoring capabilities.