Tornetta Rockwood Adults 9781975137298 FINAL VERSION

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SECTION ONE • General Principles

controlled interfragmentary motion. 221 Some important facts about numerical simulation are as follows: • FEA results are only approximations that must be validated by physical tests that exactly replicate the FEA model. • After successful validation, FEA is a powerful tool that can be used to explore a wide parameter space to systematically optimize implant performance in a timely and cost-effective manner. • Combining FEA with numerical simulation of fracture heal- ing can support the development of implants that maximize fixation durability and support bone healing. The goal of this chapter was to provide a basic understanding of biomechanics and engineering principles. This is essential to allow appropriate evaluation of biomechanical studies and to integrate the information into clinical studies. Improper or selective use of test methods or outcome parameters can bias results to favor one implant over another. In contrast, a prop- erly designed study that replicates a clinically relevant failure mode or implant performance enables systematic optimization of orthopedic implants and interventions in a timely and cost-effective manner. By reducing the number of uncontrolled vari- ables compared to clinical studies, biomechanical studies have a higher sensitivity to detect performance differences between interventions. As such, biomechanical research provides a time and cost-effective complementary strategy to analyze implant performance before a clinical study is designed. Understanding the mechanisms of fractures and the energy required to cause specific fracture types allows the surgeon to understand the “character” of the fracture. Targeting a specific healing mode allows the surgeon to design a fixation construct that allows healing along an expected course with or without callus. Understanding the basic mechanics of the general types of fixation constructs allows the application of the principles of fixation in specific anatomic locations. Knowledge of the postop- erative loads experienced by fracture fixation constructs is vital to optimizing their application. Finally, understanding the concepts of stress risers and their effect on the risks of peri-implant frac- tures will avoid such complications arising from the improper choice of fixation methods. The surgeon must possess the ability to evaluate the quality of biomechanical studies as they apply to the clinical treatment of patients. SUMMARY

strain at specific locations (Fig. 1-42B). Comparison between these physical test results and the same parameters extracted from the FEA demonstrates the degree by which the FEA results correlate with actual test results. It must be noted that FEA results are always estimations, never exact, and can exhibit large deviations compared to physical test results. These deviations stem from the inherent limitations by which a computational model can accurately simulate model parameters, such as the geometry and material properties of bone, or the pressure and frictional properties at the implant–bone interface or fracture site. Based on the physical test results, FEA parameters can be systematically adjusted to minimize deviations and to improve the model validity. Although the development and validation of a numeri- cal model are elaborate and time-consuming, a validated FEA model has two powerful advantages over the physical test setup used for its model validation. First, FEA can provide unique results that cannot be obtained with other methods. It can cal- culate strain, stress, and deformation throughout the entire fixa- tion construct. This enables the localization of the highest stress concentration in an implant, which is invaluable for implant optimization (Fig. 1-42C). In contrast, experimental measure- ments are limited to a small number of predefined measurement locations, which are restricted to the specimen surface. Second, FEA allows for a wide range of parametric studies in a time and cost-effective manner to explore the effect of geometry, material properties, or boundary conditions. In the intramedullary nail example, FEA can be employed to explore how outcome mea- surements are affected by different types of hip fractures, by different lag screw diameters, or by different locking bolt con- figurations. As such, FEA is an invaluable tool for exploration and optimization of implants and fixation techniques. Numerical simulation of bone healing can be considered an outgrowth of the rapidly advancing field of FEA. For prediction of bone healing, computational models are used in conjunc- tion with bio-regulatory and mechano-regulation algorithms to predict the influence of mechanical stimuli on the tissue dif- ferentiation process during bone healing. Over the last decade, computational models of fracture healing have progressed from static, linear elastic models to dynamic poroelastic analyses, accounting for callus growth and several biologic factors includ- ing growth factors, cells, and vascularization. 101 By combining FEA with numerical simulation of bone heal- ing, biomechanical research holds the key to develop the next generation of fracture fixation implants that deliver durable fixation as well as reliable promotion of fracture healing by

Annotated References

Reference

Annotation

Augat P, Simon U, Liedert A, et al. Mechanics and mechano-biology of fracture healing in normal and osteoporotic bone. Osteoporos Int. 2005;16:S36–S43. Bottlang M, Tsai S, Bliven EK, et al. Dynamic stabilization of simple fractures with active plates delivers stronger healing than conventional compression plating. J Orthop Trauma. 2017;31(2):71–77.

Review of mechanical factors affecting fracture healing in osteoporotic and normal bone.

In vivo study demonstrating that a simple transverse fracture heals faster and stronger when stabilized with an axially elastic plate than with a compression plate

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