Comparative finite-element analysis: a single computational modelling method can estimate the mechanical properties of porcine and human vertebrae

Significant advances in the functional analysis of musculoskeletal systems require the development of modelling techniques with improved focus, accuracy and validity. This need is particularly visible in the fields, such as palaeontology, where unobservable parameters may lie at the heart of the most interesting research questions, and where models and simulations may provide some of the most innovative solutions. Here, we report on the development of a computational modelling method to generate estimates of the mechanical properties of vertebral bone across two living species, using elderly human and juvenile porcine specimens as cases with very different levels of bone volume fraction and mineralization. This study is presented in two parts; part I presents the computational model development and validation, and part II the virtual loading regime and results. This work paves the way for the future estimation of mechanical properties in fossil mammalian bone.

Development of specimen-specific finite element models of human vertebrae for the analysis of vertebroplasty

The aim of this study was to determine the accuracy of specimen-specific finite element models of untreated and cement-augmented vertebrae by direct comparison with experimental results. Eleven single cadaveric vertebrae were imaged using micro computed tomography (mCT) and tested to failure in axial compression in the laboratory. Four of the specimens were first augmented with PMMA cement to simulate a prophylactic vertebroplasty. Specimen-specific finite element models were then generated using semi-automated methods. An initial set of three untreated models was used to determine the optimum conversion factors from the image data to the bone material properties. Using these factors, the predicted stiffness and strength were determined for the remaining specimens (four untreated, four augmented). The model predictions were compared with the corresponding experimental data. Good agreement was found with the non-augmented specimens in terms of stiffness (root-mean-square (r.m.s.) error 12.9 per cent) and strength (r.m.s. error 14.4 per cent). With the augmented specimens, the models consistently overestimated both stiffness and strength (r.m.s. errors 65 and 68 per cent). The results indicate that this method has the potential to provide accurate predictions of vertebral behaviour prior to augmentation. However, modelling the augmented bone with bulk material properties is inadequate, and more detailed modelling of the cement region is required to capture the bone—cement interactions if the models are to be used to predict the behaviour following vertebroplasty.