Microstructure-Informed Myelin Mapping (MIMM) from Gradient Echo MRI using Stochastic Matching Pursuit

Area of Science:

• Neuroimaging
• Biophysics
• Medical Physics

Background:

• Accurate quantification of white matter myelin volume fraction (MVF) is crucial for understanding neurodegenerative diseases like Multiple Sclerosis (MS).
• Existing methods for myelin quantification often lack noninvasiveness or precision, hindering longitudinal studies.
• Developing advanced Magnetic Resonance Imaging (MRI) techniques is essential for improved diagnostic and monitoring capabilities.

Approach:

• A novel noninvasive MRI method, Microstructure-Informed Myelin Mapping (MIMM), was developed to quantify MVF.
• MIMM utilizes a multi gradient echo sequence (mGRE) and a detailed biophysical model incorporating myelin and iron susceptibility effects.
• A dictionary of simulated MR signals and susceptibility values was created and matched to measured MRI data for voxel-wise quantification.

Key Points:

• MIMM models myelin as an anisotropic susceptibility source and iron as an isotropic source, capturing microstructural details.
• Three MIMM variations were tested, considering different approaches to fiber orientation, including DTI-informed and atlas-based methods.
• All MIMM variations demonstrated significant linear correlation with T2-relaxometry (p < 0.0001), with orientation-informed versions showing reduced overestimation in white matter tracts.

Conclusions:

• MIMM provides a robust method for quantifying MVF and iron distribution noninvasively.
• Orientation-informed MIMM versions improve accuracy in major white matter tracts by accounting for fiber orientation.
• The acquired myelin and iron maps hold significant potential for longitudinal monitoring of neurodegenerative diseases.