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The goal of this study was to develop an image analysis algorithm for quantifying the effects of remodelling on cortical bone during early fracture healing. An adaptive thresholding technique with boundary curvature and tortuosity control was developed to automatically identify the endocortical and pericortical boundaries in the presence of high-gradient bone mineral density (BMD) near the healing zone. The algorithm successfully detected boundaries in more than 47,000 microCT images from 12 pairs of healing ovine osteotomies and intact contralateral tibiae. Resampling techniques were used to achieve data dimensionality reduction on the segmented images, allowing characterisation of radial, circumferential, and axial distributions of cortical BMD. Local (transverse slice) and total (whole bone) remodelling scores were produced. These surrogate measures of cortical remodelling derived from BMD revealed that cortical changes were detectable throughout the region covered by callus and that the localised loss of cortical BMD was highest near the osteotomy. Total remodelling score was moderately and significantly correlated with callus volume and mineral composition (r > 0.64, p < 0.05), suggesting that the cortex may be a source of mineral needed to build callus. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

As scientific advancements continue to reshape the world, it becomes increasingly crucial to uphold ethical standards and minimize the potentially adverse impact of research activities. In this context, the implementation of the 3R principles—Replacement, Reduction, and Refinement—has emerged as a prominent framework for promoting ethical research practices in the use of animals. This article aims to explore recent advances in integrating the 3R principles into fracture healing research, highlighting their potential to enhance animal welfare, scientific validity, and societal trust. The review focuses on in vitro, in silico, ex vivo, and refined in vivo methods, which have the potential to replace, reduce, and refine animal experiments in musculoskeletal, bone, and fracture healing research. Here, we review material that was presented at the workshop "Implementing 3R Principles into Fracture Healing Research" at the 2023 Orthopedic Research Society (ORS) Annual Meeting in Dallas, Texas. [ABSTRACT FROM AUTHOR]

In image-based finite element analysis of bone, partial volume effects (PVEs) arise from image blur at tissue boundaries and as a byproduct of geometric reconstruction and meshing during model creation. In this study, we developed and validated a material assignment approach to mitigate partial volume effects. Our validation data consisted of physical torsion testing of intact tibiae from N = 20 Swiss alpine sheep. We created finite element models from micro-CT scans of these tibiae using three popular element types (10-node tetrahedral, 8-node hexahedral, and 20-node hexahedral). Without partial volume management, the models over-predicted the torsional rigidity compared to physical biomechanical tests. To address this problem, we implemented a dual-zone material model to treat elements that overlap low-density surface voxels as soft tissue rather than bone. After in situ inverse optimization, the dual-zone material model produced strong correlations and high absolute agreement between the virtual and physical tests. This suggests that with appropriate partial volume management, virtual mechanical testing can be a reliable surrogate for physical biomechanical testing. For maximum flexibility in partial volume management regardless of element type, we recommend the use of the following dual-zone material model for ovine tibiae: soft-tissue cutoff density of 665 mgHA/cm3 with a soft tissue modulus of 50 MPa (below cutoff) and a density-modulus conversion slope of 10,225 MPa-cm3/mgHA for bone (above cutoff). [ABSTRACT FROM AUTHOR]

Since the 1970s, the 2%−10% rule has been used to describe the range of interfragmentary gap closure strains that are conducive for secondary bone healing. Interpreting the available evidence for the association between strain and bone healing remains challenging because interfragmentary strain is impossible to directly measure in vivo. The question of how much strain occurs within and around the fracture gap is also difficult to resolve using bench tests with osteotomy models because these do not reflect the complexity of injury patterns seen in the clinic. To account for these challenges, we used finite element modeling to assess the three‐dimensional interfragmentary strain in a case series of naturally occurring distal femur fractures treated with lateral plating under load conditions representative of the early postoperative period. Preoperative computed tomography scans were used to construct patient‐specific finite element models and plate fixation constructs to match the operative management of each patient. The simulations showed that gap strains were within 2%−10% only for the lowest load application level, 20% static body weight (BW). Moderate loading of 60% static BW and above caused gap strains that far exceeded 10%, but in all cases, strains in the periosteal region external to the fracture line remained low. Comparing these findings with postoperative radiographs suggests that in vivo secondary healing of distal femur fractures may be robust to early gap strains much greater than 10% because formation of new bone is initiated outside the gap where strains are lower, followed by later consolidation within the gap. [ABSTRACT FROM AUTHOR]

In patient-specific finite element modeling, elementwise material assignment calculates local mechanical properties from the underlying CT data. If meshes must be transformed, for example to reconstruct broken bones, this elementwise material mapping is not possible using commercial software. Accordingly, we developed an algorithm to transform and reconstruct CT scans and fill gaps at discontinuities. Virtual mechanical testing showed that iterative reconstruction retains material heterogeneity with minimal strain artifacts and achieves whole-bone mechanics clinically equivalent (within 5%) to homogeneous models. This approach may expand the range of clinical CT scans that are viable for virtual biomechanics by allowing defect repair. [ABSTRACT FROM AUTHOR]

Bone fracture healing is a complex physiological process influenced by biomechanical and biomolecular factors. Mechanical stability is crucial for successful healing, and disruptions can lead to delayed healing or nonunion. Bone commonly heals itself through secondary fracture healing, which is governed by the mechanical strain at the fracture site. To investigate these phenomena, a validated methodology for capturing the mechanoregulatory process in specimen‐specific models of fracture healing could provide insight into the healing process. This study implemented a prognostic healing simulation framework to predict healing trajectories based on mechanical stimuli. Sixteen sheep were subjected to a 3 mm transverse tibial mid‐shaft osteotomy, stabilized with a custom plate, and equipped with displacement transducer sensors to measure interfragmentary motion over 8 weeks. Computed tomography scans were used to create specimen‐specific bone geometries for finite element analysis. Virtual mechanical testing was performed iteratively to calculate strains in the callus region, which guided tissue differentiation and consequently, healing. The predicted healing outcomes were compared to continuous in vivo sensor data, providing a unique validation data set. Healing times derived from the in vivo sensor and in silico sensor showed no significant differences, suggesting the potential for these predictive models to inform clinical assessments and improve nonunion risk evaluations. This study represents a crucial step towards establishing trustworthy computational models of bone healing and translating these to the preclinical and clinical setting, enhancing our understanding of fracture healing mechanisms.Clinical significance: Prognostic bone fracture healing simulation could assist in non‐union diagnosis and prediction. [ABSTRACT FROM AUTHOR]

Finite element analysis with models derived from computed tomography (CT) scans is potentially powerful as a translational research tool because it can achieve what animal studies and cadaver biomechanics cannot-low-risk, noninvasive, objective assessment of outcomes in living humans who have actually experienced the injury, or treatment being studied. The purpose of this study was to assess the validity of CT-based virtual mechanical testing with respect to physical biomechanical tests in a large animal model. Three different tibial osteotomy models were performed on 44 sheep. Data from 33 operated limbs and 20 intact limbs was retrospectively analyzed. Radiographic union scoring was performed on the operated limbs and physical torsional tests were performed on all limbs. Morphometric measures and finite element models were developed from CT scans and virtual torsional tests were performed to assess healing with four material assignment techniques. In correlation analysis, morphometric measures and radiographic scores were unreliable predictors of biomechanical rigidity, while the virtual torsion test results were strongly and significantly correlated with measured biomechanical test data, with high absolute agreement. Overall, the results validated the use of virtual mechanical testing as a reliable in vivo assessment of structural bone healing. This method is readily translatable to clinical evaluation for noninvasive assessment of the healing progress of fractures with minimal risk. Clinical significance: virtual mechanical testing can be used to reliably and noninvasively assess the rigidity of a healing fracture using clinical-resolution CT scans and that this measure is superior to morphometric and radiographic measures., (© 2020 Orthopaedic Research Society. Published by Wiley Periodicals LLC.)