Diffusion MRI and the Diffusion Tensor Model
Illustrations of tensors from various microstructures, highlighting the influence of the anisotropic water component (depicted as blue dots) on the resulting tensors. Each scenario includes representations of Mean Diffusivity (MD) and Fractional Anisotropy (FA). Figure adapted from Colman et al. (Colman, 2022) under the Creative Commons Attribution License.
Illustration of free water molecules (blue dots) within various microstructures, showcasing the impact of tissue damage on the resulting free water (FW) signal.
References
Colman et al., Appl. Sci., 12: 1-17, 2022;
https://www.mdpi.com/2076-3417/12/2/816
Diffusion MRI (dMRI) is an advanced imaging technique that measures water molecule diffusion in tissues, reflecting cellular structures, such as neurons, axons, and white matter tracts. In healthy brain tissue, water diffuses more freely along axons than across them, creating anisotropy. dMRI captures this directional diffusion, and disruptions to white matter, such as in neurodegenerative diseases, which reduce anisotropy and increase overall diffusion. By modeling diffusion with diffusion tensor imaging (DTI), metrics like fractional anisotropy (FA) and mean diffusivity (MD) are derived, providing insights into white matter and tissue integrity.
A complementary model, called free water assessment, separates diffusion signals into free water (extracellular fluid) and tissue-bound water. The free water fraction (FW) is estimated using a bi-tensor model to detect isotropic diffusion. FW calculations reveal gray matter changes, such as neuroinflammation, cell loss, or edema, common in disorders like frontotemporal dementia (FTD).
FTD is a diverse group of neurodegenerative disorders that cause progressive atrophy in the frontal and temporal lobes, resulting in behavioral, language, and executive dysfunction. Diffusion MRI detects white and gray matter abnormalities in FTD subtypes, enhancing our understanding of spatial and temporal differences in their microstructure. It is increasingly used in FTD clinical trials to aid in diagnosis, identify early changes, track disease progression, and assess treatment effectiveness.