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Multi-compartment diffusion-relaxation MR signal representation in the spherical 3D-SHORE basis
Fabian Bogusz1, Tomasz Pieciak2
1AGH University of Krakow, Kraków, Poland.
Computers in Biology and Medicine
|September 7, 2025
Summary
This study introduces Multi-Compartment SHORE (MC-SHORE), a novel method for analyzing diffusion-relaxation magnetic resonance (MR) signals. MC-SHORE accurately models complex tissue microstructures, improving upon existing techniques for better tissue characterization.
Area of Science:
- Magnetic Resonance Imaging (MRI)
- Biophysical Modeling
- Neuroimaging
Background:
- Multi-parametric diffusion-relaxation MRI requires efficient signal modeling.
- Current continuum modeling approaches face challenges with dictionary size and parameter estimation.
- Accurate modeling is crucial for understanding tissue microstructure beyond mono-exponential decay.
Purpose of the Study:
- To present a novel Multi-Compartment SHORE (MC-SHORE) representation for diffusion-relaxation MR signals.
- To enable accurate signal approximation from scattered acquisitions using sparse priors.
- To estimate microstructural measures and separate intra-/extra-axonal and free water signals.
Main Methods:
- Developed MC-SHORE, a multi-compartment signal representation based on Simple Harmonic Oscillator-based Reconstruction and Estimation.
- Applied L1 norm for sparsity constraint to estimate signal contributions.
- Validated the method using in silico and in vivo diffusion-relaxation MR data.
Main Results:
- MC-SHORE accurately approximates diffusion-relaxation MR signals, outperforming single-compartment non-Gaussian and multi-compartment mono-exponential methods.
- The technique maintains a low dictionary size, facilitating efficient estimation.
- Successfully estimated microstructural measures like return-to-the-origin probability and orientation distribution function.
Conclusions:
- MC-SHORE offers a robust framework for analyzing complex diffusion-relaxation MR data.
- The method effectively separates intra-/extra-axonal and free water contributions, reducing partial volume effects.
- MC-SHORE advances the capability for detailed in vivo tissue microstructure characterization.
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