Fiber orientation-dependent white matter contrast in gradient echo MRI

Micro-compartment specific T2* relaxation in the brain

MRI at high field can be sensitized to the magnetic properties of tissues, which introduces a signal dependence on the orientation of white matter (WM) fiber bundles relative to the magnetic field. In addition, study of the NMR relaxation properties of this signal has indicated contributions from compartmentalized water environments inside and outside the myelin sheath that may be separable. Here we further investigated the effects of water compartmentalization on the MRI signal with the goal of extracting compartment-specific information. By comparing MRI measurements of human and marmoset brain at 7T with magnetic field modeling, we show that: (1) water between the myelin lipid bilayers, in the axonal, and in the interstitial space each experience characteristic magnetic field effects that depend on fiber orientation (2) these field effects result in characteristic relaxation properties and frequency shifts for these compartments; and (3) compartmental contributions may be separated by multi-component fitting of the MRI signal relaxation (i.e. decay) curve. We further show the potential application of these findings to the direct mapping of myelin content and assessment of WM fiber integrity with high field MRI.

Detecting microstructural properties of white matter based on compartmentalization of magnetic susceptibility

The microscopic structure of neuronal tissue is crucial to brain function, with axon diameter, axonal density and myelination directly influencing signal conduction in the white matter. There is increasing evidence that these microstructural properties alter signal in magnetic resonance imaging (MRI) driven by magnetic susceptibility of different compartments (e.g., myelin sheaths and iron-laden cells). To explain these observations, we have developed a multi-compartmental geometric model of whitematter microstructure. Using a single set of literature parameters, this forward model predicts experimentally observed orientation dependence and temporal evolution of the MRI signal. Where previous models have aimed to explain only the orientation dependence of signal phase, the proposed approach encapsulates the full repertoire of signal behavior. The frequency distribution underlying signal behavior is predicted to be a rich source of microstructural information with relevance to neuronal pathology.