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Rapid microscopic fractional anisotropy imaging via an optimized linear regression formulation.
N J J Arezza1, D H Y Tse2, C A Baron1
1Centre for Functional and Metabolic Mapping (CFMM), Robarts Research Institute, University of Western Ontario, London, Canada; Department of Medical Biophysics, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada.
Magnetic Resonance Imaging
|May 4, 2021
Summary
We developed a faster diffusion MRI method to measure microscopic fractional anisotropy (μFA) in the brain. This technique enables rapid, whole-brain μFA imaging, crucial for understanding brain health and disease.
Area of Science:
- Neuroimaging
- Biophysics
- Medical Physics
Background:
- Water diffusion anisotropy in the brain changes with disease, trauma, and development.
- Microscopic fractional anisotropy (μFA) quantifies diffusion anisotropy independently of fiber orientation.
- Current μFA estimation methods face challenges in clinical scan times and full brain coverage.
Purpose of the Study:
- To present an optimized spherical tensor encoding (STE) technique for rapid, direct estimation of μFA.
- To evaluate the performance and reliability of the direct regression approach for μFA imaging.
- To demonstrate the potential for clinically viable, whole-brain μFA acquisition.
Main Methods:
- Utilized a 2nd order cumulant expansion of diffusion MRI (dMRI) signal with direct linear regression.
- Optimized dMRI parameters including maximum b-value and STE/LTE acquisition ratio.
- Compared direct regression methods against the established gamma model in healthy volunteers on a 3T system.
Main Results:
- The optimized STE technique requires fewer signals and can be computed rapidly.
- Direct regression approaches showed strong linear correlations (ρ = 0.97, 0.90) with the gamma model.
- All tested μFA measurements demonstrated good test-retest reliability (ρ ≥ 0.79).
Conclusions:
- The optimized direct regression approach enables rapid, nearly full brain μFA imaging within minutes.
- This technique offers a significant advantage in scan time for clinical applications.
- The method provides a reliable and efficient way to assess brain microstructure.
Keywords:
Diffusion weighted imagingMicroscopic anisotropyMicroscopic fractional anisotropyMicrostructureNeuroimaging
