Computational simulation of the intervertebral disc

The intervertebral disc is a complex structure unlike any other in the human body. The capability to withstand high loads and deformations in six degrees of freedom is facilitated by the unique soft tissue structures. However, the mechanical behaviour of these tissues is not well understood.

The aim of this project was to investigate methods of deriving structural information about the tissues of the intervertebral disc for application in computational simulation, with particular focus on the mechanical function of the annulus fibrosis and how the behaviour of this tissue is governed by its substructures.

Magnetic resonance imaging techniques were assessed for potential to inform specimen specific models of the disc. Imaging sequences were developed and validated to image in vitro disc samples in unloaded and compressed states. These images captured the lamellar structure of the annulus in three dimensions to a level of detail not previously published.

The image data facilitated the development of a novel method of specimen specific model construction, as well as providing experimental deformation data, against which the models were directly validated.

Sensitivity analyses on both generalised and specimen specific models illustrated the influence of interlamellar interaction representation on the gross mechanics of the disc models. The models were adapted to illustrate the effects of tissue degeneration and intervention on disc mechanics

Interlamellar interactions and tissue level mechanics were further investigated by developing specimen specific models of disc tissue samples based on microscopy data. Novel methods were developed to implement qualitative histological data into finite element analyses of annulus tissue samples. Interlamellar interactions were shown to provide a strong bond between lamellae.

The parameters and variables involved in the mechanical system of the disc pose major challenges for experimental investigation. This study has successfully laid the ground work to negotiate these challenges using a computational approach