Computational biomechanical modelling of external fixation of fractures to predict bone healing

The treatment of bone fractures commonly uses ring external fixation frames (REFFs) to permit early mobility through using minimal invasive surgery. REFFs can be fitted in various configurations, and the patient-specific configuration ultimately influences the rate at which the fractured bone will heal. There is a clinical need for a computational (aka in silico) tool that enables a consultant to predict the time span in which a fractured bone will heal for a given REFF configuration and considering patient-specific data.

Computational modelling offers techniques to simulate bone healing, although these techniques need to consider the numerous patient-specific factors that affect the biomechanics at the fracture site. This project will work with consultants from both the Hull University Teaching Hospital and Leeds Teaching Hospitals Trust to identify these patient-specific factors, and then use an experimental-computational framework to simulate bone healing in the event of a fractured bone.

This project will develop new engineering methods to simulate and predict bone healing in cases of fractures treated with a REFF, accounting for the natural population variation in fracture mechanics. The objectives of the project are: Build computational models of REFFs and validate them against experimental testing data of the same frames;

Use clinical data to establish the range of variation in fracture mechanics that are present within a population (e.g. frame configuration, fracture type, rate of movement post-fracture, alteration to gait post-fracture etc);

Develop novel computational models to predict bone healing that considers this natural population variation in fracture mechanics;

Compare the accuracy of computational modelling predictions to clinical datasets of fracture healing, and determine how accuracy varies when modelling the extremes of the natural population variation in fracture mechanics.