Microstructure-Informed Myelin Mapping (MIMM) from routine multi-echo gradient echo data using multiscale physics modeling of iron and myelin effects and QSM.
Academic Article
Overview
abstract
PURPOSE: Myelin quantification is used in the study of demyelination in neurodegenerative diseases. A novel noninvasive MRI method, Microstructure-Informed Myelin Mapping (MIMM), is proposed to quantify the myelin volume fraction (MVF) from a routine multi-gradient echo sequence (mGRE) using a multiscale biophysical signal model of the effects of microstructural myelin and iron. THEORY AND METHODS: In MIMM, the effects of myelin are modeled based on the Hollow Cylinder Fiber Model accounting for anisotropy, while iron is considered as an isotropic paramagnetic point source. This model is used to create a dictionary of mGRE magnitude signal evolution and total voxel susceptibility using finite elements of size 0.2 μm. Next, voxel-by-voxel stochastic matching pursuit between acquired mGRE data (magnitude+QSM) and the pre-computed dictionary generates quantitative MVF and iron susceptibility maps. Dictionary matching was evaluated under three conditions: (1) without fiber orientation (basic), (2) with fiber orientation obtained using DTI, and (3) with fiber orientation obtained using an atlas (atlas). MIMM was compared with the three-pool complex fitting (3PCF) using T2-relaxometry myelin water fraction (MWF) map as reference. RESULTS: The DTI MIMM and atlas MIMM approaches were equally effective in reducing the overestimation of MVF in certain white matter tracts observed in the basic MIMM approach, and they both showed good agreement with T2-relaxometry MWF. MIMM MVF reduced myelin overestimation of globus pallidus observed in 3PCF MWF. CONCLUSION: MIMM processing of mGRE data can provide MVF maps from routine clinical scans without requiring special sequences.
