Keywords: White Matter, Quantitative Imaging, myelin water imaging, multicomponent analysis, multiple sclerosis, quantitative MRI, qMRI, white matter
Motivation: Multicomponent T2 (mcT2) analysis is the go-to tool for mapping myelin in vivo. Resolving T2 spectra, however, is highly challenging due to substantial ambiguity in the multidimensional space of microstructural configurations.
Goal(s): Accurate and reproducible myelin water imaging.
Approach: A spatially-global data-driven mcT2 analysis was employed, relying on the identification of tissue-specific mcT2 configurations prior to performing voxel-wise analysis. A new scheme was developed for correcting transmit field (B1+) inhomogeneities.
Results: Successful application of the data-driven technique is demonstrated on numerical phantom, healthy volunteers, and for identifying pathology in normal-appearing tissue of subjects with multiple sclerosis.
Impact: The data-driven approach constitutes a new paradigm for multi-component T2 fitting, yielding unprecedented accuracy and high robustness. Application on MS patients’ data highlights the potential of data-driven MWF values as a biomarker for pathology in normal appearing tissue.
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