Experimental and virtual testing of bone-implant systems equipped with the AO Fracture Monitor with regard to interfragmentary movement.

Introduction: The management of fractured bones is a key domain within orthopedic trauma surgery, with the prevention of delayed healing and non-unions forming a core challenge. This study evaluates the efficacy of the AO Fracture Monitor in conjunction with biomechanical simulations to better understand the local mechanics of fracture gaps, which is crucial for comprehending mechanotransduction, a key factor in bone healing. Through a series of experiments and corresponding simulations, the study tests four hypotheses to determine the relationship between physical measurements and the predictive power of biomechanical models. Methods: Employing the AO Fracture Monitor and Digital Image Correlation techniques, the study demonstrates a significant correlation between the surface strain of implants and interfragmentary movements. This provides a foundation for utilizing one-dimensional AO Fracture Monitor measurements to predict three-dimensional fracture behavior, thereby linking mechanical loading with fracture gap dynamics. Moreover, the research establishes that finite element simulations of bone-implant systems can be effectively validated using experimental data, underpinning the accuracy of simulations in replicating physical behaviors. Results and Discussion: The findings endorse the combined use of monitoring technologies and simulations to infer the local mechanical conditions at the fracture site, offering a potential leap in personalized therapy for bone healing. Clinically, this approach can enhance treatment outcomes by refining the assessment precision in trauma trials, fostering the early detection of healing disturbances, and guiding improvements in future implant design. Ultimately, this study paves the way for more sophisticated patient monitoring and tailored interventions, promising to elevate the standard of care in orthopedic trauma surgery.

Simulation-based prediction of bone healing and treatment recommendations for lower leg fractures: Effects of motion, weight-bearing and fibular mechanics.

Despite recent experimental and clinical progress in the treatment of tibial and fibular fractures, in clinical practice rates of delayed bone healing and non-union remain high. The aim of this study was to simulate and compare different mechanical conditions after lower leg fractures to assess the effects of postoperative motion, weight-bearing restrictions and fibular mechanics on the strain distribution and the clinical course. Based on the computed tomography (CT) data set of a real clinical case with a distal diaphyseal tibial fracture, a proximal and a distal fibular fracture, finite element simulations were run. Early postoperative motion data, recorded via an inertial measuring unit system and pressure insoles were recorded and processed to study strain. The simulations were used to compute interfragmentary strain and the von Mises stress distribution of the intramedullary nail for different treatments of the fibula, as well as several walking velocities (1.0 km/h; 1.5 km/h; 2.0 km/h) and levels of weight-bearing restriction. The simulation of the real treatment was compared to the clinical course. The results show that a high postoperative walking speed was associated with higher loads in the fracture zone. In addition, a larger number of areas in the fracture gap with forces that exceeded beneficial mechanical properties longer was observed. Moreover, the simulations showed that surgical treatment of the distal fibular fracture had an impact on the healing course, whereas the proximal fibular fracture barely mattered. Weight-bearing restrictions were beneficial in reducing excessive mechanical conditions, while it is known that it is difficult for patients to adhere to partial weight-bearing recommendations. In conclusion, it is likely that motion, weight bearing and fibular mechanics influence the biomechanical milieu in the fracture gap. Simulations may improve decisions on the choice and location of surgical implants, as well as give recommendations for loading in the postoperative course of the individual patient.

Concepts and clinical aspects of active implants for the treatment of bone fractures.

Nonunion is a complication of long bone fractures that leads to disability, morbidity and high costs. Early detection is difficult and treatment through external stimulation and revision surgery is often a lengthy process. Therefore, alternative diagnostic and therapeutic options are currently being explored, including the use of external and internal sensors. Apart from monitoring fracture stiffness and displacement directly at the fracture site, it would be desirable if an implant could also vary its stiffness and apply an intervention to promote healing, if needed. This could be achieved either by a predetermined protocol, by remote control, or even by processing data and triggering the intervention itself (self-regulated 'intelligent' or 'smart' implant). So-called active or smart materials like shape memory alloys (SMA) have opened up opportunities to build active implants. For example, implants could stimulate fracture healing by active shortening and lengthening via SMA actuator wires; by emitting pulses, waves, or electromagnetic fields. However, it remains undefined which modes of application, forces, frequencies, force directions, time durations and periods, or other stimuli such implants should ideally deliver for the best result. The present paper reviews the literature on active implants and interventions for nonunion, discusses possible mechanisms of active implants and points out where further research and development are needed to build an active implant that applies the most ideal intervention. STATEMENT OF SIGNIFICANCE: Early detection of delays during fracture healing and timely intervention are difficult due to limitations of the current diagnostic strategies. New diagnostic options are under evaluation, including the use of external and internal sensors. In addition, it would be desirable if an implant could actively facilitate healing ('Intelligent' or 'smart' implant). Implants could stimulate fracture healing via active shortening and lengthening; by emitting pulses, waves, or electromagnetic fields. No such implants exist to date, but new composite materials and alloys have opened up opportunities to build such active implants, and several groups across the globe are currently working on their development. The present paper is the first review on this topic to date.

Individualized Determination of the Mechanical Fracture Environment After Tibial Exchange Nailing-A Simulation-Based Feasibility Study.

Non-union rate after tibial fractures remains high. Apart from largely uncontrollable biologic, injury, and patient-specific factors, the mechanical fracture environment is a key determinant of healing. Our aim was to establish a patient-specific simulation workflow to determine the mechanical fracture environment and allow for an estimation of its healing potential. In a referred patient with failed nail-osteosynthesis after tibial-shaft fracture exchange nailing was performed. Post-operative CT-scans were used to construct a three-dimensional model of the treatment situation in an image processing and computer-aided design system. Resulting forces, computed in a simulation-driven workflow based on patient monitoring and motion capturing were used to simulate the mechanical fracture environment before and after exchange nailing. Implant stresses for the initial and revision situation, as well as interfragmentary movement, resulting hydrostatic, and octahedral shear strain were calculated and compared to the clinical course. The simulation model was able to adequately predict hardware stresses in the initial situation where mechanical implant failure occurred. Furthermore, hydrostatic and octahedral shear strain of the revision situation were calculated to be within published healing boundaries-accordingly the fracture healed uneventfully. Our workflow is able to determine the mechanical environment of a fracture fixation, calculate implant stresses, interfragmentary movement, and the resulting strain. Critical mechanical boundary conditions for fracture healing can be determined in relation to individual loading parameters. Based on this individualized treatment recommendations during the early post-operative phase in lower leg fractures are possible in order to prevent implant failure and non-union development.