Digital volume correlation for the characterization of musculoskeletal tissues: Current challenges and future developments

Abstract

Biological tissues are complex hierarchical materials, difficult to characterise due to the challenges associated to the separation of scale and heterogeneity of the mechanical properties at different dimensional levels.The Digital Volume Correlation approach is the only image-based experimental approach that can accurately measure internal strain field within biological tissues under complex loading scenarios. In this minireview examples of DVC applications to study the deformation of musculoskeletal tissues at different dimensional scales are reported, highlighting the potential and challenges of this relatively new technique.The manuscript aims at reporting the wide breath of DVC applications in the past 2 decades and discuss future perspective for this unique technique, including fast analysis, applications on soft tissues, high precision approaches, and clinical applications.

Biomechanical evaluation of different strain judging criteria on the prediction precision of cortical bone fracture simulation under compression

“…Based on these, the innovation of this paper was to further improve the simulation accuracy of the cortical bone fracture under compression. The principal strain or equivalent strain was always selected as the criterion to judge the crack initiation and propagation in the element of the FE model ( Dall’Ara and Tozzi, 2022 ; Hambli and Allaoui, 2013 ). However, various types of strain rise differently, even under the same loading condition ( Dall’Ara et al, 2017 ).…”

Bone metastases do not affect the measurement uncertainties of a global digital volume correlation algorithm

“…Finally, the authors are aware that other sources of errors exist: such as the quality of the input images (image resolution, artefacts, SNR) and the correlation algorithm (objective and shape function, operational parameters) ( Roberts et al, 2014 ). The effect of them have already been partially investigated through a zero-strain analysis, in different bone structures ( Dall’Ara and Tozzi, 2022 ).…”

“…Local internal experimental strain measurements of whole bones can be performed by using Digital Volume Correlation (DVC) ( Dall’Ara and Tozzi, 2022 ), processing micro-Computed Tomography (microCT) images of the object in unloaded and loaded conditions. This contact-less technique provides a volumetric measurement of the displacement field and, by differentiation, of the strain fields within the imaged structure.…”

“…This contact-less technique provides a volumetric measurement of the displacement field and, by differentiation, of the strain fields within the imaged structure. DVC has already been applied to evaluate the internal displacement and strain fields in different musculoskeletal tissues ( Dall’Ara and Tozzi, 2022 ; Dall’Ara et al, 2022 ). In particular, this approach has already been used to study the biomechanics of animal ( Danesi et al, 2016 ; Palanca et al, 2016 ; Tozzi et al, 2016 ; Palanca et al, 2021b ) and human ( Hussein et al, 2012 ) vertebrae and to investigate the local strain distributions within the whole vertebral body and in specific subregions.…”

Data-driven image mechanics (D2IM): a deep learning approach to predict displacement and strain fields from undeformed X-ray tomography images - Evaluation of bone mechanics

“…Experimental techniques such as digital volume correlation (DVC) are currently considered state-of-the-art in the mechanical characterization of bone, from organ to tissue level. DVC allows for three-dimensional full-field displacement and strain measurements in the material volume by correlating grayscale features from three-dimensional images, typically obtained via high-resolution X-ray computed tomography (XCT) before and after the application of mechanical loading in a process known as in situ XCT mechanics [1]. However, traditional in situ XCT mechanics is performed in a stepwise fashion (i.e.…”