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Fast myelin water fraction estimation using 2D multislice CPMG
Author(s) -
AkhondiAsl Alireza,
Afacan Onur,
Balasubramanian Mukund,
Mulkern Robert V.,
Warfield Simon K.
Publication year - 2016
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.26034
Subject(s) - multislice , imaging phantom , myelin , relaxometry , bloch equations , partial volume , nuclear magnetic resonance , mathematics , biological system , chemistry , physics , algorithm , magnetic resonance imaging , computer science , spin echo , artificial intelligence , optics , medicine , radiology , neuroscience , biology , central nervous system
Purpose T 2 relaxometry based on multiexponential fitting to a single slice multiecho sequence has been the most common MRI technique for myelin water fraction mapping, where the short T 2 is associated with myelin water. However, very long acquisition times and physically unrealistic models for T 2 distribution are limitations of this approach. We present a novel framework for myelin imaging which substantially increases the imaging speed and myelin water fraction estimation accuracy. Method We used the 2D multislice Carr‐Purcell‐Meiboom‐Gill sequence to increase the volume coverage. To compensate for nonideal slice profiles, we numerically solved the Bloch equations for a range of T 2 and B 1 inhomogeneity scales to construct the bases for the estimation of the T 2 distribution. We used a finite mixture of continuous parametric distributions to describe the complete T 2 spectrum and used the constrained variable projection optimization algorithm to estimate myelin water fraction. To validate our model, synthetic, phantom, and in vivo brain experiments were conducted. Results Using the Bloch equations, we can model the slice profile and construct the forward model of the T 2 curve. Our method estimated myelin water fraction with smaller error than the nonnegative least squares algorithm. Conclusions The proposed framework can be used for reliable whole brain myelin imaging with a resolution of 2 × 2 × 4 mm 3in ≈ 17 min . Magn Reson Med 76:1301–1313, 2016. © 2015 Wiley Periodicals, Inc.