COnstrained Reference frame diffusion TEnsor Correlation Spectroscopic (CORTECS) MRI: A practical framework for...

Area of Science:

• Neuroimaging
• Diffusion MRI
• Biophysics

Background:

• Water diffusion in cortical tissue follows specific orientations relative to the surface.
• Existing diffusion MRI methods face challenges in accurately characterizing complex diffusion patterns.

Purpose of the Study:

• To develop a practical framework for imaging non-parametric diffusion tensor distributions (DTDs).
• To constrain and efficiently reconstruct these distributions using high-resolution diffusion MRI data.

Main Methods:

• Proposed a constrained DTD (cDTD) framework utilizing a common orthonormal reference frame for microscopic diffusion tensors.
• Employed Inverse Laplace Transform methods for efficient reconstruction of cDTDs.
• Applied the framework to numerical simulations and high-resolution diffusion MRI data from a macaque monkey brain.

Main Results:

• Successfully estimated 2D cDTDs in the cortex, deriving distributions of microscopic diffusivities and anisotropies.
• Demonstrated that signal components from cDTD-derived spectra correlate highly with cortical laminar structures seen in histology.
• Showcased the framework's ability to simplify non-parametric DTD measurement in high-resolution datasets.

Conclusions:

• The developed cDTD framework offers a simplified and efficient approach to analyzing complex water diffusion in brain tissue.
• This method provides high specificity to anatomical structures, particularly cortical layers.
• The framework is applicable retrospectively to existing diffusion MRI datasets of fixed cortical tissues.