Non-negative least squares computation for in vivo myelin mapping using simulated multi-echo spin-echo T₂ decay data

Multi-compartment T₂ mapping has gained particular relevance for the study of myelin water in the 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 T₂ 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 T₂ and MWF maps. We generated multi-echo spin-echo T₂ decay curves following the Carr-Purcell-Meiboom-Gill approach for various myelin concentrations and myelin T₂ 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 T₂ (gmT₂ ). MWF estimates were more stable than myelin water gmT₂ time across different settings of the T₂ analysis. We observed that the lower limit of the T₂ 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 T₂ signal. Among all parameters of interest, the estimated MWF and intra-/extracellular water gmT₂ 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 us to better characterize the T₂ distribution, including the myelin water, in vivo.