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Improved quantification of myelin water fraction using joint sparsity of T 2 * distribution
Author(s) -
Chen Quan,
She Huajun,
Du Yiping P.
Publication year - 2020
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.27013
Subject(s) - mathematics , coefficient of variation , nuclear magnetic resonance , statistics , physics
Background Myelin water fraction (MWF) can be quantified with analysis of the T 2 * distribution, whereas deducing the T 2 * spectrum from several echoes is an underdetermined and ill‐posed problem. Purpose To improve the quantification of myelin water content by using nonnegative jointly sparse (NNJS) optimization. Study Type Prospective. Subjects Nine healthy subjects. Field Strength/Sequence 3T, multiecho gradient echo. Assessment The results of NNJS were compared with that of the nonnegative least square (NNLS)‐based algorithms. Simulated models with varied MWF at different noise levels were used to evaluate the accuracy of estimations. In human data, the MWF values of different regions were compared with previous studies and the coefficient of variation (COV) was used to assess the spatial coherence. Statistical Test Paired t ‐test. Results In simulation, the relative errors of MWF obtained from synthesized data with signal‐to‐noise ratio (SNR) at 500, 200, 150, and 100 were 0.08, 0.09, 0.10, and 0.12 for NNJS, 0.29, 0.43, 0.48, and 0.53 for regularized NNLS (rNNLS), and 0.19, 0.24, 0.25, and 0.26 for spatially‐regularized NNLS (srNNLS). In human data, the mean values of MWF produced by NNJS in different regions were consistent with previous studies. Compared with the NNLS‐based algorithms, lower COVs generated by NNJS were observed in genu, forceps minor, forceps major, and internal capsule, which were 0.44 ± 0.08, 0.48 ± 0.07, 0.46 ± 0.03, and 0.48 ± 0.09 in NNJS, 0.88 ± 0.28, 0.96 ± 0.18, 0.72 ± 0.03, and 0.85 ± 0.15 in rNNLS, and 0.56 ± 0.17, 0.64 ± 0.14, 0.50 ± 0.04 and 0.58 ± 0.13 in srNNLS. Data Conclusion Quantitative results of both simulated and human data show that NNJS provides more plausible estimation than the NNLS‐based algorithms. Visual advantages of NNJS in spatial consistency can be confirmed by the comparative COV index. The proposed algorithm might improve the quantification of myelin water content. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;52:146–158.