Department of Bioengineering

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    Leveraging Rehabilitation and Implantable Strain Sensors to Improve Bone Healing After Traumatic Femur Fractures
    (University of Oregon, 2025-02-24) Williams, Kylie; Guldberg, Robert
    The primary objective of this thesis was to quantify patient-specific loading and rehabilitation parameters to elucidate how specific rehabilitation conditions impact bone healing after traumatic bone injuries. Our overall hypothesis was that parameters of mechanical loading and exercise will impact bone healing. To test this hypothesis, we utilized three rehabilitation platforms that enabled investigation of distinct rehabilitation parameters. These platforms including (1) a rodent running wheel with engineered resistance brakes or on/off brakes to enable running of different intensities or durations, respectively, (2) a treadwheel with an adapted on/off brake as a scalable platform, and (3) altered treadmill with speeds conducive to rodent needs. These platforms allowed for the investigate of distinct rehabilitation platforms and their relationship to bone healing. We also used implantable wireless strain sensors that enabled real-time non-invasive monitoring of mechanical cues as a function of time, rehabilitation conditions, and healing status. In collaboration with University of Utah, we used these sensors and in vivo microCT scans to develop subject-specific finite element models to quantify niche mechanical cues during different rehabilitation conditions. We discovered that higher intensity rehabilitation, relative to rehabilitation of lower intensity, increased early-stage strain magnitudes and significantly improved bone healing, with explant femurs matching intact strength. Beyond loading magnitude, we also discovered the importance of both long term and short term on bone healing. Nonlinear multivariate analyses revealed that rehabilitation must balance activity and rest to improve bone healing, where rehabilitation with longer running distance and shorter daily rest periods resulted in 100% union after 3 mm bone injuries. These results further found that the necessary balance of rehabilitation and rest depends on subject-specific factors such as injury size since the same rehabilitation conditions resulted in only 20% union after a 2 mm bone injury but 100% nonunion after a 3 mm bone injury. Using previous studies to inform a rehabilitation regimen predicted to improve bone healing, we also found the importance of short-term rest between exercise loading bouts. Rehabilitation that involved steady-state running for 12 minutes significantly hindered bridging and bone formation compared to rehabilitation that involved intermittent rest periods between one minute running bouts. Systemic myeloid-derived cell types, previously predicted to impair bone healing, were also downregulated for rehabilitation with short-term rest periods. These results highlight rehabilitation with data-informed levels of intensity, activity, and both short and long term rest as a therapeutic to modulate early mechanical loading and the immune response to enhance bone repair.This work facilitated a deeper understanding of how specific rehabilitation parameters regulate mechanical cues and bone repair and validated an implantable sensor platform to further investigate mechanobiology. This thesis aids in the development of subject-specific rehabilitation with the novel insight into the importance of rest on bone healing. Our results challenge the fields focus on optimizing the loading magnitude to improve bone repair. In addition, this thesis provides foundational support for the commercialization of implantable sensor technologies to track implant mechanics as a noninvasive feedback of healing status and to inform personalized clinical decisions. This dissertation includes content from several published articles including Nash* et al. (2022) Connective Tissue Research; Nash* et al. (2022) Physiology in Health and Disease, Springer; Williams and Harrer et al. (2024) NPJ Regenerative Medicine; and Williams et al. (submitted 2024) Science Advances. *Publication under maiden name: Kylie Nash