Non-exponential relaxation models of signal decay in magnetic resonance imaging

Diffusion-weighted magnetic resonance imaging (dMRI) describes the architecture of biological tissues by using gradient pulse sequences to provide image contrast based on the hindered and restricted diffusion of water. Changes in the direction, duration and delay between the applied gradient pulses reveal patterns characteristic of diseases in the heart and brain. Numerous approaches have been used to describe the decay of the dMRI signal intensity attenuation. Recently, a varying diffusion coefficient (VDC) model was proposed that assumes the apparent diffusion coefficient is not a constant, but a decreasing function of the diffusion-sensitizing gradient factor ( b-value). Here we analyze data from a dMRI experiment performed on the bovine optic nerve using VDC models of anomalous and ultraslow diffusion. The results show that VDC models capture and characterize the multi exponential features of the signal attenuation, and that for diffusion along and across the optic nerve that the ultraslow diffusion model gives the best fit to the experimental data. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

This article discusses the application of diffusion-weighted magnetic resonance imaging in describing the structure of biological tissues, as well as the analysis and fitting of experimental data using the VDC model. The experimental results show that the VDC model can effectively capture the characteristics of signal attenuation, and the ultraslow diffusion model provides the best fit for diffusion in the optic nerve.