Application of the digital volume correlation technique for the measurement of displacement and strain fields in bone: A literature review

Digital volume correlation (DVC) provides experimental measurements of displacements and strains throughout the interior of porous materials such as trabecular bone. It can provide full-field continuum- and tissue-level measurements, desirable for validation of finite element models, by comparing image volumes from subsequent mu CT scans of a sample in unloaded and loaded states. Since the first application of DVC for measurement of strain in bone tissue, subsequent reports of its application to trabecular bone cores up to whole bones have appeared within the literature. An optimal set of procedures capable of precise and accurate measurements of strain, however, still remains unclear, and a systematic review focussing explicitly on the increasing number of DVC algorithms applied to bone or structurally similar materials is currently unavailable. This review investigates the effects of individual parameters reported within individual studies, allowing to make recommendations for suggesting algorithms capable of achieving high accuracy and precision in displacement and strain measurements. These recommendations suggest use of subsets that are sufficiently large to encompass unique datasets (e.g. subsets of 500 gm edge length when applied to human trabecular bone cores, such as cores 10 mm in height and 5 mm in diameter, scanned at 15 mu m voxel size), a shape function that uses full affine transformations (translation, rotation, normal strain and shear strain), the robust normalized cross-correlation coefficient objective function, and high-order interpolation schemes. As these employ computationally burdensome algorithms, researchers need to determine whether they have the necessary computational resources or time to adopt such strategies. As each algorithm is suitable for parallel programming however, the adoption of high precision techniques may become more prevalent in the future. (C) 2014 Elsevier Ltd. All rights reserved.