Image Analysis Software as a Strategy to Improve the Radiographic Determination of Fracture Healing

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Abstract

Objectives:

To develop and validate an unbiased, accurate, convenient, and inexpensive means of determining when an osseous defect has healed and recovered sufficient strength to allow weight bearing.

Methods:

A novel image processing software algorithm was created to analyze the radiographic images and produce a metric designed to reflect the bone strength. We used a rat femoral segmental defect model that provides a range of healing responses from complete union to nonunion. Femora were examined by x-ray, micro–computed tomography and mechanical testing. Accurate simulated radiographic images at different incident x-ray beam angles were produced from the micro–computed tomography data files.

Results:

The software-generated metric (SC) showed high levels of correlation with both the mechanical strength (τMech) and the polar moment of inertia (pMOI), with the mechanical testing data having the highest association. The optimization analysis yielded optimal oblique angles θB of 125 degrees for τMech and 50 degrees for pMOI. The Pearson R2 values for the optimized model were 0.71 and 0.64 for τMech and pMOI, respectively. Further validation using true radiographs also demonstrated that the metric was accurate and that the simulations were realistic.

Conclusions:

The preliminary findings suggest a very promising methodology to assess bone fracture healing using conventional radiography. With radiographs acquired at appropriate incident angles, it proved possible to accurately calculate the degree of healing and the mechanical strength of the bone. Further research is necessary to refine this approach and determine whether it translates to the human clinical setting.

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