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Diagnostic monitoring and prediction of bone fracture healing is critical for the detection of delayed union or non‐union and provides the requisite information as to whether therapeutic intervention or timely revision are warranted. A promising approach to monitor fracture healing is to measure the mechanical load‐sharing between the healing callus and the implanted hardware used for internal fixation. The objectives of this study were to evaluate a non‐invasive measurement system in which an antenna electromagnetically couples with the implanted hardware to sense deflections of the hardware due to an applied load and to investigate the efficacy of the system to detect changes in mechanical load‐sharing in an ex vivo fracture healing model. The measurement system was applied to ovine metatarsal bones treated with osteotomies, resulting in four different levels of bone stability which simulated various degrees of fracture healing. Computational finite element simulations supplemented these ex vivo experiments to compare the osteotomy model of fracture healing to a more clinically applicable callus stiffening model of healing. In the ex vivo experiments, the electromagnetic coupling system detected significant differences between the four simulated degrees of healing with good repeatability. Computational simulations indicated that the experimental model of fracture healing provided a good surrogate for studying healing during the early time period as the callus stiffness is increasing as well as when diagnostic monitoring of the healing process is most critical. Based upon the data reported herein, the direct electromagnetic coupling method holds strong potential for clinical assessments and predictions of fracture healing. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res

Current diagnostic modalities, such as radiographs or computed tomography, exhibit limited ability to predict the outcome of bone fracture healing. Failed fracture healing after orthopaedic surgical treatments are typically treated by secondary surgery; however, the negative correlation of time between primary and secondary surgeries with resultant health outcome and medical cost accumulation drives the need for improved diagnostic tools. This study describes the simultaneous use of multiple (n = 5) implantable flexible substrate wireless microelectromechanical (fsBioMEMS) sensors adhered to an intramedullary nail (IMN) to quantify the biomechanical environment along the length of fracture fixation hardware during simulated healing in ex vivo ovine tibiae. This study further describes the development of an antenna array for interrogation of five fsBioMEMS sensors simultaneously, and quantifies the ability of these sensors to transmit signal through overlaying soft tissues. The ex vivo data indicated significant differences associated with sensor location on the IMN (p < 0.01) and fracture state (p < 0.01). These data indicate that the fsBioMEMS sensor can serve as a tool to diagnose the current state of fracture healing, and further supports the use of the fsBioMEMS as a means to predict fracture healing due to the known existence of latency between changes in fracture site material properties and radiographic changes.

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