PubMed · 6831811
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O O Oni. 1983. Bone healing.. https://pubmed.ncbi.nlm.nih.gov/6831811/
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Based on published reports, we presumed radiographs would be unreliable as a sole measure of fracture healing. To confirm this presumption we correlated radiographic fracture healing assessments with fracture stiffness measurements. We showed 100 plain radiographs of fractures with corresponding fracture stiffness measurements to 92 observers. The radiographs were shown twice to assess intraobserver variation. Observers were divided into three groups and asked to determine whether each fracture had healed (union corresponded to a fracture stiffness greater than 15 nm/degrees). Group 1 based fracture healing on the general appearance of healing. Groups 2 and 3 assessed fracture healing based on the number of cortices bridged by callus. In Group 2, the fracture was considered healed if two or more cortices were bridged on both radiographic views and in Group 3 if three or more cortices were bridged by callus. All groups performed poorly. There was no difference in terms of correct prediction of healing between methods, although there was a trend toward more reliability with cortical callus bridging assessment. We found substantial intraobserver variability, which improved using cortical bridging methods. Observers were less reliable at predicting healing when there was a metaphyseal extension to a diaphyseal fracture.
Bone fractures heal through a complex process involving several cellular events. This healing process can serve to study factors that control tissue growth and differentiation from mesenchymal stem cells. The mechanical environment at the fracture site is one of the factors influencing the healing process and controls size and differentiation patterns in the newly formed tissue. Mathematical models can be useful to unravel the complex relation between mechanical environment and tissue formation. In this study, we present a mathematical model that predicts tissue growth and differentiation patterns from local mechanical signals. Our aim was to investigate whether mechanical stimuli, through their influence on stem cell proliferation and chondrocyte hypertrophy, predict characteristic features of callus size and geometry. We found that the model predicted several geometric features of fracture calluses. For instance, callus size was predicted to increase with increasing movement. Also, increases in size were predicted to occur through increase in callus diameter but not callus length. These features agree with experimental observations. In addition, spatial and temporal tissue differentiation patterns were in qualitative agreement with well-known experimental results. We therefore conclude that local mechanical signals can probably explain the shape and size of fracture calluses.
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