Literature DB >> 31424131

Quantitative susceptibility mapping of the spine using in-phase echoes to initialize inhomogeneous field and R2* for the nonconvex optimization problem of fat-water separation.

Yihao Guo1,2,3,4, Zhe Liu2,3, Yan Wen2,3, Pascal Spincemaille2, Honglei Zhang2, Ramin Jafari2,3, Shun Zhang2, Sarah Eskreis-Winkler2, Kelly M Gillen2, Peiwei Yi1, Qianjin Feng1,4, Yanqiu Feng1,4, Yi Wang2,3.   

Abstract

Quantitative susceptibility mapping (QSM) of human spinal vertebrae from a multi-echo gradient-echo (GRE) sequence is challenging, because comparable amounts of fat and water in the vertebrae make it difficult to solve the nonconvex optimization problem of fat-water separation (R2*-IDEAL) for estimating the magnetic field induced by tissue susceptibility. We present an in-phase (IP) echo initialization of R2*-IDEAL for QSM in the spinal vertebrae. Ten healthy human subjects were recruited for spine MRI. A 3D multi-echo GRE sequence was implemented to acquire out-phase and IP echoes. For the IP method, the R2* and field maps estimated by separately fitting the magnitude and phase of IP echoes were used to initialize gradient search R2*-IDEAL to obtain final R2*, field, water, and fat maps, and the final field map was used to generate QSM. The IP method was compared with the existing Zero method (initializing the field to zero), VARPRO-GC (variable projection using graphcuts but still initializing the field to zero), and SPURS (simultaneous phase unwrapping and removal of chemical shift using graphcuts for initialization) on both simulation and in vivo data. The single peak fat model was also compared with the multi-peak fat model. There was no substantial difference on QSM between the single peak and multi-peak fat models, but there were marked differences among different initialization methods. The simulations demonstrated that IP provided the lowest error in the field map. Compared to Zero, VARPRO-GC and SPURS, the proposed IP method provided substantially improved spine QSM in all 10 subjects.
© 2019 John Wiley & Sons, Ltd.

Entities:  

Keywords:  fat-water separation; in-phase echo; multi-peak fat model; proton density fat fraction; quantitative susceptibility mapping; single peak fat model; spine; vertebrae

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Substances:

Year:  2019        PMID: 31424131     DOI: 10.1002/nbm.4156

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  2 in total

1.  Quantitative susceptibility mapping of the head-and-neck using SMURF fat-water imaging with chemical shift and relaxation rate corrections.

Authors:  Beata Bachrata; Siegfried Trattnig; Simon Daniel Robinson
Journal:  Magn Reson Med       Date:  2021-11-30       Impact factor: 4.668

2.  Deep neural network for water/fat separation: Supervised training, unsupervised training, and no training.

Authors:  Ramin Jafari; Pascal Spincemaille; Jinwei Zhang; Thanh D Nguyen; Xianfu Luo; Junghun Cho; Daniel Margolis; Martin R Prince; Yi Wang
Journal:  Magn Reson Med       Date:  2020-10-26       Impact factor: 4.668

  2 in total

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