Analysis of ADC model robustness in diffusion-weighted MRI

A variety of parametric models based on the Apparent Diffusion Coefficient (ADC) have been proposed to describe signal decay in the interpretation of diffusion weighted Magnetic Resonance Imaging data. In this work, we investigate the robustness of several of these models, including the exponential model, bi-exponential model and the recently proposed gamma distribution model, using a Crámer-Rao lower bound analysis. It is demonstrated that the parameters of all models are susceptible to significant estimation errors at the current gradient strengths of clinical scanners. To complement the theoretical analysis, the robustness of the models is compared through application to experimental ovine optic nerve and rat brain MRI data. Our results indicate that gamma distribution model fits experimental data better than the commonly employed bi-exponential model.