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In large animal studies, the mechanical reintegration of the bone fragments is measured using postmortem physical testing, but these assessments can only be performed once, after sacrifice. Image‐based virtual mechanical testing is an attractive alternative because it could be used to monitor healing longitudinally. However, the procedures and software required to perform finite element analysis (FEA) on subject‐specific models for virtual mechanical testing can be time consuming and costly. Accordingly, the goal of this study was to determine whether a simpler image‐based geometric measure—the torsion constant, sometimes known as polar moment of inertia—can be reliably used as a surrogate measure of bone healing in large animals. To achieve this, postmortem biomechanical testing and microCT scans were analyzed for a total of 33 operated and 20 intact ovine tibiae. An image‐processing procedure to compute the attenuation‐weighted torsion constant from the microCT scans was developed in MATLAB and this code has been made freely available. Linear regression analysis was performed between the postmortem biomechanical data, the results of virtual mechanical testing using FEA, and the torsion constants measured from the scans. The results showed that virtual mechanical testing is the most reliable surrogate measure of postmortem torsional rigidity, having strong correlations and high absolute agreement. However, when FEA is not practical, the torsion constant is a viable alternative surrogate measure that is moderately correlated with postmortem torsional rigidity and can be readily calculated. 

Bone healing has been traditionally described as a four-phase process: inflammatory response, soft callus formation, hard callus development, and remodeling. The remodeling phase has been largely neglected in most numerical mechanoregulation models of fracture repair in favor of capturing early healing using a pre-defined callus domain. However, in vivo evidence suggests that remodeling occurs concurrently with repair and causes changes in cortical bone adjacent to callus that are typically neglected in numerical models of bone healing. The objective of this study was to use image processing techniques to quantify this early-stage remodeling in ovine osteotomies. To accomplish this, we developed a numerical method for radiodensity profilometry with optimization-based curve fitting to mathematically model the bone density gradients in the radial direction across the cortical wall and callus. After assessing data from 26 sheep, we defined a dimensionless density fitting function that revealed significant remodeling occurring in the cortical wall adjacent to callus during early healing, a 23% average reduction in density compared to intact. This fitting function is robust for modeling radial density gradients in both intact bone and fracture repair scenarios and can capture a wide variety of the healing responses. The fitting function can also be scaled easily for comparison to numerical model predictions and may be useful for validating future mechanoregulatory models of coupled fracture repair and remodeling.