This PFI: AIR Technology Translation project focuses on developing a smart implant that will offer physicians the ability to monitor progression of fracture healing in real time. Approximately 15 million bone fractures occur each year in the United States, of which an estimated 10-20% result in delayed or no healing (non-union) under normal conditions. If the bone fractures occur in complex trauma cases or in patients that are elderly or sick, this percentage rises to almost 50%. Based on a conservative estimate, over $24 billion in additional medical care is required to treat these patients with poor healing. An underlying problem with treating fracture patients is that there are currently no standardized methods for accurately measuring healing. Physicians make decisions about treatment based on subjective physical examinations, patient's pain, and radiographic techniques (X-rays) that can only detect bone formation late in the healing process. Consequently, physicians typically wait 6-9 months to diagnose non-unions, at which point patients require reoperation. There exists a need for a quantitative, reliable method to monitor fracture healing and particularly to distinguish between the phases of early stage healing. This project will incorporate sensors into standard fracture plates that are used to surgically stabilize broken bones. The sensors will take electrical measurements related to the biology of the fracture and wirelessly transmit them to external monitors. Accurate monitoring of fracture healing using these smart fracture plates will inform clinical decisions of when to begin weight-bearing and enable earlier intervention of high-risk fractures, which together both improve patient quality of life and offer a substantial cost savings to the healthcare system.
This project involves developing the electronic components to validate smart implant technology that quantifies tissue composition in the fracture callus based on electrical impedance spectroscopy (EIS). Proof-of-concept studies have been completed in ex vivo and murine models of fracture repair; this project will scale the EIS technology into the rabbit model. Scaling-up to this larger pre-clinical model allows the project to address technology gaps related to development of the sensor and wireless detection system, while working with commercially available Orthopaedic implants. A key feature that will make the technology competitive is a custom algorithm designed to analyze and characterize electronic signatures to distinguish the various stages of fracture healing. Current competitors are focused on mechanical measurements. However, electrical measurements could provide a more sensitive tool to detect early changes, as the load bearing to load sharing transition (detected by strain gauges) occurs after hard callus begins to form only in the last stage of fracture healing.
The collaborative research leadership team is composed of two orthopaedic research faculty, electrical engineering faculty, an orthopaedic surgeon and university senior licensing officer, now seeking to translate the technology to a larger preclinical animal model suitable in size for wireless smart implant development and cost-effective enough to evaluate using an appropriate sample size. Trainees involved in this project will receive innovation, entrepreneurship, and technology translation experiences through technical development, execution of pre-clinical trials and exposure to commercialization strategy.
