Revolutionizing Bone Healing: A New Project to Predict Healing and Reduce Complications
Imagine a world where broken bones heal faster and with fewer complications. A groundbreaking project is taking a significant step towards this vision, aiming to predict bone healing and reduce the devastating impact of fractures on patients’ lives.
Every year, approximately 10 million Americans experience a broken bone, and the consequences can be severe. Delayed healing affects a quarter of patients with lower leg fractures, while one in 10 patients faces a nonunion, a condition requiring major surgery to heal. These complications not only cause physical pain but also take a significant toll on patients’ mental and financial well-being.
The challenge lies in understanding the complex interplay of mechanical and biological factors that influence bone healing. Mechanical factors, such as the rigidity of implants and the distance between bone ends, have been studied extensively. However, the biological factors, including cellular, molecular, and systemic processes, are less understood and harder to control.
Hannah Dailey, a researcher and associate professor at Lehigh University, is leading a team that has recently received funding for an international collaboration with Switzerland’s AO Research Institute Davos (ARI). This collaboration brings them closer to identifying the critical point of intervention in bone healing.
The four-year project, supported by the U.S. National Science Foundation and the Swiss National Science Foundation, focuses on creating computational models to predict bone healing over time. Dailey explains, ‘If you and I broke our legs in exactly the same place, in exactly the same way, we would not have identical healing responses due to our different biologies.’ This highlights the need to account for individual biological differences in the healing process.
To achieve this, the team will utilize a comprehensive library of imaging data provided by ARI, a leading institute for orthopedic research. This data tracks fracture healing in sheep, a process that closely mimics human healing. By analyzing these images taken over many months, the team can measure the healing progress and use the data to refine their predictive models.
The project’s innovative approach involves integrating the model into ARI’s online training platform, OSapp. As a premier organization for surgeon education, ARI supports interactive simulations accessible to professionals worldwide. These modules cover various topics, including instrumentation, implant manipulation, and patient recovery options.
Dailey emphasizes the potential of the model to assist surgeons in visualizing how mechanical factors can influence biological responses. She states, ‘Surgeons can control mechanics, such as implant usage and patient rehabilitation instructions. Our model will help them understand how these mechanics impact the healing process.’
The long-term goal is to develop patient-specific simulations that predict individual bone healing based on biology and implant type. This could revolutionize the way surgeons approach healing, enabling them to make better and earlier decisions about interventions, such as additional surgeries or bone stimulators.
This project holds immense promise for improving patient outcomes and reducing the burden of fracture complications. With its potential to predict and optimize healing, it brings us one step closer to a future where broken bones are no longer a cause for concern.