Bone fractures often heal by forming a soft external bridge called a callus, which gradually hardens over time and restores the structural stiffness of the bone. In clinical studies focused on bone healing, healing progress is usually tracked using subjective assessments such as pain and mobility scores, qualitative observations of callus on X-rays, and incidence of complications such as implant fatigue failure. This data can be highly variable, leading to study designs that require very large multi-center trials with thousands of cases to detect differences between groups.

Accordingly, the purpose of this thesis is to propose a new technique for assessing bone healing using virtual mechano-structural analysis of computed tomography (CT) scan data. In this work, CT scans from 19 fractured human tibiae (shinbones) at 12 weeks after surgery were segmented and prepared for finite element analysis (FEA). Boundary conditions were applied to the models to simulate a torsion test that is commonly used to assess the structural integrity of long bones in animal models of fracture healing. The output of each model was the virtual torsional rigidity (VTR) of the healing zone, normalized to the torsional rigidity of that same patient’s virtually reconstructed tibia. This provided a structural measure to track the percentage of healing each patient had undergone. Callus morphometric measurements were also collected from the CT scans.

Results from this study showed that morphometric data such as callus volume and density had weak non-significant correlations to a patient’s healing. However, VTR had a strong correlation of R2 = 0.699 (p < 0.0001) with the reconstructed VTR. Furthermore, more than 75% of patients achieved a normalized VTR (torsional rigidity relative to uninjured bone) of 75% or above. This finding suggests that a new clinically relevant guideline – the “75/75” rule – may be useful for benchmarking expectations for normal healing. Under this rule, surgeons should expect 75% of tibial fracture patients to achieve at least 75% of their own intact rigidity at 12 weeks post-op.

In summary, this study is the first-ever application of image-based structural analysis to clinical (human) CT scan data for assessment of bone healing. The methods proposed may provide the foundation for a new paradigm of robust and statistically powerful clinical research in orthopaedic trauma.