Modelling of diffusion-weighted MRI signals in non-neural tissue

The general aim of clinical diffusion-weighted MRI (DWI) is the inference of tissue structure properties, particularly pathology, from measurements of diffusion attenuation under conditions of varying diffusion times and b-values. Models of water diffusion in tissue have been proposed to serve this purpose. Diffusion models can be broadly split into two types, phenomenological and structural. Phenomenological models aim to provide reliable mathematical descriptions of DWI signals, but biophysical interpretation of their model parameters is limited. The recent trend is towards compartment models that are based on assumptions about tissue geometry. Compartment models have proven successful in brain imaging, where they predict the diffusion signal more accurately and provide estimates of specific neural tissue features, such as fiber orientation distribution and axon diameter. However, compartment models are generally lacking for non-neural tissue. This thesis investigates compartment models of diffusion in four types of non-neural tissue (prostate, breast, spheroids and lymph nodes).