Non-negative least squares computation for in vivo myelin mapping using simulated multi-echo spin-echo T2decay data

Multi-compartment T 2 -mapping has gained particular relevance for the study of myelin water in brain. As a facilitator of rapid saltatory axonal signal transmission, myelin is a cornerstone indicator of white matter development and function. Regularized non-negative least squares fitting of multi-echo T 2 data has been widely employed for the computation of the myelin water fraction (MWF) and the obtained MWF maps have been histopathologically validated. MWF measurements depend upon the quality of the data acquisition, B1 + -homogeneity and a range of fitting parameters. In this special issue article, we discuss the relevance of these factors for the accurate computation of multi-compartment T 2 and MWF maps. We generated multi-echo spin-echo T 2 decay curves following the approach of CarrPurcell-Meiboom-Gill for various myelin concentrations and myelin T 2 scenarios by simulating the evolution of the magnetization vector between echoes based on the Bloch equations. We demonstrated that noise and imperfect refocusing flip angles yield systematic underestimations in MWF and intra-/extracellular water geometric mean (gm) T 2 . MWF estimates were more stable than myelin water gmT 2 time across different settings of the T 2 analysis. We observed that the lower limit of the T 2 distribution grid should be slightly shorter than TE1. Both TE1 and the acquisition echo spacing also have to be sufficiently short to capture the rapidly decaying myelin water T 2 signal. Among all parameters of interest, the estimated MWF and intra-/extracellular water gmT 2 differed by approximately 0.13-4 percentage points and 3-4 ms, respectively, from the true values, with larger deviations observed in the presence of greater B1 + -inhomogeneities and at lower signal-to-noise ratio. Tailoring acquisition strategies may allow to better characterize the T 2 distribution, including the myelin water, in vivo.