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Abusive head trauma (AHT) is a potentially fatal result of child abuse but the mechanisms of injury are controversial. To address the hypothesis that shaking alone is sufficient to elicit the injuries observed, effective computational and experimental models are necessary. This paper investigates the use of a coupled rigid-body computational modelling framework to reproduce in vivo shaking kinematics in AHT. A sagittal plane OpenSim computational model of a lamb was developed and used to interpret biomechanical data from in vivo shaking experiments. The acceleration of the head during shaking was used to provide in vivo validation of the associated computational model. Results of this study demonstrated that peak accelerations occurred when the head impacted the torso and produced acceleration magnitudes exceeding 200ms(-)(2). The computational model demonstrated good agreement with the experimental measurements and was shown to be able to reproduce the high accelerations that occur during impact. The biomechanical results obtained with the computational model demonstrate the utility of using a coupled rigid-body modelling framework to describe infant head kinematics in AHT.

Fetal head geometry plays an important role in the mechanics of childbirth during the second stage labour. Large heads have been shown to be associated with difficult and prolonged childbirth. However, the relationship between the fetal head geometry and childbirth mechanics has not been quantitatively analysed. To address this, our study used finite element (FE) modelling techniques and biomechanical simulations to analyse the contribution of fetal head shape and size on the mechanics of childbirth. X-ray computed tomography (CT) images from 26 newborn infants (less than 9 days old) without skull abnormalities were used to construct individual-specific FE models of the fetal skull. Simulations of childbirth were conducted using each model of the skull and a customised pelvic floor model based on magnetic resonance imaging (MRI) of a healthy nulliparous woman. The force required for delivery, the maximum principal stresses, and the maximum principal stretch ratios at the left and right pelvic floor muscle-pubic bone interfaces were quantified. Partial least squares regression (PLSR) models for predicting these mechanical indices were constructed using: (i) either the FE geometries of the fetal heads or the biometrical parameters (biparietal diameters and fetal head circumferences) as inputs; and (ii) either a linear or a quadratic function for the inner relation. The predictabilities of the mechanical indices using the PLSR models were quantified using a leave-one-out analysis. Quantitative associations were found between the geometric parameters of the fetal head and the indices of childbirth mechanics. When using the full FE geometries as inputs, the PLSR model using a linear inner relation gave better predictability than the model using a quadratic inner relation. This could be attributed to the quadratic inner relation correlating response to the noise in point-to-point correspondence. When using the biometrical parameters of the skull as inputs, the PLSR model using a quadratic inner relation gave the best overall predictability. Such a model could be implemented in a clinical setting as a predictive model for childbirth planning and as an educational tool for clinical training.

Mammography is currently the most widely used screening and diagnostic tool for breast cancer. Because X-ray images are 2D projections of a 3D object, it is not trivial to localise features identified in mammogram pairs within the breast volume. Furthermore, mammograms represent highly deformed configurations of the breast under compression, thus the tumour localisation process relies on the clinician's experience. Biomechanical models of the breast undergoing mammographic compressions have been developed to overcome this limitation. In this study, we present the development of a modelling framework that implements Coulomb's frictional law with a finite element analysis using a C(1)-continuous Hermite mesh. We compared two methods of this contact mechanics implementation: the penalty method, and the augmented Lagrangian method, the latter of which is more accurate but computationally more expensive compared to the former. Simulation results were compared with experimental data from a soft silicon gel phantom in order to evaluate the modelling accuracy of each method. Both methods resulted in surface-deformation root-mean-square errors of less than 2mm, whilst the maximum internal marker prediction error was less than 3mm when simulating two mammographic-like compressions. Simulation results were confirmed using the augmented Lagrangian method, which provided similar accuracy. We conclude that contact mechanics on soft elastic materials using the penalty method with an appropriate choice of the penalty parameters provides sufficient accuracy (with contact constraints suitably enforced), and may thus be useful for tracking breast tumours between clinical images.