Abstract. Magnetic resonance imaging (MRI) is the primary method
for noninvasive investigations of the human brain in health, disease, and
development but yields data that are difficult to interpret whenever the
millimeter-scale voxels contain multiple microscopic tissue environments
with different chemical and structural properties. We propose a novel MRI
framework to quantify the microscopic heterogeneity of the living human
brain as spatially resolved five-dimensional relaxation–diffusion
distributions by augmenting a conventional diffusion-weighted imaging
sequence with signal encoding principles from multidimensional solid-state
nuclear magnetic resonance (NMR) spectroscopy, relaxation–diffusion
correlation methods from Laplace NMR of porous media, and Monte Carlo data
inversion. The high dimensionality of the distribution space allows
resolution of multiple microscopic environments within each heterogeneous
voxel as well as their individual characterization with novel statistical
measures that combine the chemical sensitivity of the relaxation rates with
the link between microstructure and the anisotropic diffusivity of tissue
water. The proposed framework is demonstrated on a healthy volunteer using
both exhaustive and clinically viable acquisition protocols.
Avian egg latebra as brain tissue water diffusion model