Abstract:
Abusive head trauma (AHT), previously termed shaken baby syndrome (SBS), refers to head injuries inflicted on young infants by their caregivers. Although violent shaking has been implicated, there is currently a paucity of scientific evidence around the causes of these injuries. The objective of this thesis is to use finite element models to predict the deformation of soft tissues in the human infant head under prescribed shaking motion, and to examine whether these deformations are sufficient to cause injury. Phantom and human studies were investigated to validate the FE modelling framework used to create the infant model. Cube phantoms were constructed to mimic the brain, cerebrospinal fluid (CSF) and the fontanelle of an infant. These phantoms were subject to linear and rotational shaking experiments, during which the pressures were measured and used to validate a computational model. To investigate the relative motion between the brain and the skull due to a shake, rotational motions experiments were conducted on cylindrical phantoms. The deformations measured were then used to verify the assumptions and parameter settings of cylindrical FE models. The computational techniques were then validated against measured adult in vivo brain deformations where the head was experiencing rotational motions. The infant model was constructed with a fluid structure interaction modelling framework, for the first time contained all of, the anterior fontanelle, the optic nerves, the brain stem, the falx cerebri, the tentorium cerebellum, a realistic shaking input and modelled the effects of neck bending. The bridging veins were predicted to stretch enough for them to rupture, indicating that subdural haematomas would occur. The predicted forces on the optic nerves may help with future research when the injury thresholds for retinal haematomas are identified. The von Mises stresses on the brain predicted by the model indicated that it did not meet the threshold (for adult humans) required for severe traumatic brain injury. This thesis, provides a predictive tool to determine the 3D dynamic deformation of an infant’s brain subjected to realistic shaking motions.