Multidimensional diffusion MRI with spectrally modulated gradients reveals unprecedented microstructural detail

Area of Science:

• Biomedical Engineering
• Materials Science
• Medical Imaging

Background:

• Characterizing porous media is crucial for biomedical and industrial applications.
• Diffusion magnetic resonance imaging (dMRI) non-invasively probes microstructural features.
• Conventional dMRI struggles to differentiate complex microstructures due to limited encoding.

Purpose of the Study:

• To develop an advanced diffusion encoding framework for enhanced microstructural characterization.
• To overcome the limitations of conventional dMRI in distinguishing heterogeneous materials.
• To introduce a novel method for assessing time-dependent diffusion in anisotropic structures.

Main Methods:

• Proposed an augmented multidimensional diffusion encoding (MDE) framework.
• Utilized spectral analysis of MDE waveforms for time-dependent diffusion assessment.
• Generated contrasts by signal subtraction from three measurement types.

Main Results:

• Demonstrated the ability to differentiate microstructural features like cell size and shape.
• Validated the approach through analytical calculations, simulations, and proof-of-concept experiments.
• Observed distinct contrasts in post-mortem brain tissues, highlighting potential in biological studies.

Conclusions:

• The MDE framework provides a novel dimension for assessing microscopic anisotropy.
• Simultaneous assessment of restriction size and shape enhances porous material characterization.
• This technique holds significant potential for materials science, biological tissue research, and diagnostics.