MECHANICS STILL MATTERS: AN ENGINEERING PERSPECTIVE ON FRACTURE HEALING

作者
Hannah L. Dailey
出处
期刊: 卷期号:107-B (SUPP_8): 41-41
标识
DOI:10.1302/1358-992x.2025.8.041
摘要

Fracture healing is a mechanoregulated process that gradually restores the mechanical integrity of an injured bone. This talk with present a historical perspective on engineering contributions to the modern understanding of mechanoregulation in fracture healing and a current assessment of challenges and opportunities where engineers can contribute to basic and clinical sciences. Starting from the seminal work of Prof. Stephan Perren in the 1970s, half a century of translational research has defined a nuanced connection between the engineering design of fracture fixation implants and healing outcomes. Decades of engineering iterations on external fixators, plates, and intramedullary nails have been tested in large animal models and clinical studies to reveal guiding principles for fracture fixation. These studies collectively explain how mechanical strain generated through interfragmentary motion is both a driver and limiter of the secondary healing response. Yet, challenges persist with clinical translation of new technologies that suggest opportunities for engineers to contribute novel tools for clinical outcomes assessment and device evaluation. Emerging technologies in this space include image-based mechanical biomarkers, wearable technologies, and mobile device data. Beyond implant design, the analytical toolkit of engineering mechanics presents new opportunities to enrich the study of mechanobiology. Virtual mechanical testing can provide spatial insights into the 3D strain environment around a healing fracture – data that cannot be measured any other way. To achieve this, current engineering challenges include real-time data acquisition to monitor activity and the need for improved approaches for image analysis and data mining. Looking to the future, prediction of and early intervention for fracture nonunion remains a major unsolved clinical problem. Addressing this need will require the development of digital twins that combine imaging data, loading data, and next-generation predictive mechanoregulation models to identify and treat nonunions as early as possible.

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