Literature DB >> 21671269

Whole brain susceptibility mapping using compressed sensing.

Bing Wu1, Wei Li, Arnaud Guidon, Chunlei Liu.   

Abstract

The derivation of susceptibility from image phase is hampered by the ill-conditioned filter inversion in certain k-space regions. In this article, compressed sensing is used to compensate for the k-space regions where direct filter inversion is unstable. A significantly lower level of streaking artifacts is produced in the resulting susceptibility maps for both simulated and in vivo data sets compared to outcomes obtained using the direct threshold method. It is also demonstrated that the compressed sensing based method outperforms regularization based methods. The key difference between the regularized inversions and compressed sensing compensated inversions is that, in the former case, the entire k-space spectrum estimation is affected by the ill-conditioned filter inversion in certain k-space regions, whereas in the compressed sensing based method only the ill-conditioned k-space regions are estimated. In the susceptibility map calculated from the phase measurement obtained using a 3T scanner, not only are the iron-rich regions well depicted, but good contrast between white and gray matter interfaces that feature a low level of susceptibility variations are also obtained. The correlation between the iron content and the susceptibility levels in iron-rich deep nucleus regions is studied, and strong linear relationships are observed which agree with previous findings.
Copyright © 2011 Wiley-Liss, Inc.

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Year:  2011        PMID: 21671269      PMCID: PMC3249423          DOI: 10.1002/mrm.23000

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  29 in total

1.  Parallel imaging reconstruction using automatic regularization.

Authors:  Fa-Hsuan Lin; Kenneth K Kwong; John W Belliveau; Lawrence L Wald
Journal:  Magn Reson Med       Date:  2004-03       Impact factor: 4.668

2.  Susceptibility mapping in the human brain using threshold-based k-space division.

Authors:  Sam Wharton; Andreas Schäfer; Richard Bowtell
Journal:  Magn Reson Med       Date:  2010-05       Impact factor: 4.668

Review 3.  Imaging iron stores in the brain using magnetic resonance imaging.

Authors:  E Mark Haacke; Norman Y C Cheng; Michael J House; Qiang Liu; Jaladhar Neelavalli; Robert J Ogg; Asadullah Khan; Muhammad Ayaz; Wolff Kirsch; Andre Obenaus
Journal:  Magn Reson Imaging       Date:  2005-01       Impact factor: 2.546

4.  High-field MRI of brain cortical substructure based on signal phase.

Authors:  Jeff H Duyn; Peter van Gelderen; Tie-Qiang Li; Jacco A de Zwart; Alan P Koretsky; Masaki Fukunaga
Journal:  Proc Natl Acad Sci U S A       Date:  2007-06-22       Impact factor: 11.205

5.  Sparse MRI: The application of compressed sensing for rapid MR imaging.

Authors:  Michael Lustig; David Donoho; John M Pauly
Journal:  Magn Reson Med       Date:  2007-12       Impact factor: 4.668

6.  Calculation of susceptibility through multiple orientation sampling (COSMOS): a method for conditioning the inverse problem from measured magnetic field map to susceptibility source image in MRI.

Authors:  Tian Liu; Pascal Spincemaille; Ludovic de Rochefort; Bryan Kressler; Yi Wang
Journal:  Magn Reson Med       Date:  2009-01       Impact factor: 4.668

7.  Unambiguous identification of superparamagnetic iron oxide particles through quantitative susceptibility mapping of the nonlinear response to magnetic fields.

Authors:  Tian Liu; Pascal Spincemaille; Ludovic de Rochefort; Richard Wong; Martin Prince; Yi Wang
Journal:  Magn Reson Imaging       Date:  2010-08-04       Impact factor: 2.546

8.  Improving non-contrast-enhanced steady-state free precession angiography with compressed sensing.

Authors:  Tolga Cukur; Michael Lustig; Dwight G Nishimura
Journal:  Magn Reson Med       Date:  2009-05       Impact factor: 4.668

9.  MR of human postmortem brain tissue: correlative study between T2 and assays of iron and ferritin in Parkinson and Huntington disease.

Authors:  J C Chen; P A Hardy; W Kucharczyk; M Clauberg; J G Joshi; A Vourlas; M Dhar; R M Henkelman
Journal:  AJNR Am J Neuroradiol       Date:  1993 Mar-Apr       Impact factor: 3.825

10.  Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data.

Authors:  Karin Shmueli; Jacco A de Zwart; Peter van Gelderen; Tie-Qiang Li; Stephen J Dodd; Jeff H Duyn
Journal:  Magn Reson Med       Date:  2009-12       Impact factor: 4.668

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  124 in total

1.  QSMGAN: Improved Quantitative Susceptibility Mapping using 3D Generative Adversarial Networks with increased receptive field.

Authors:  Yicheng Chen; Angela Jakary; Sivakami Avadiappan; Christopher P Hess; Janine M Lupo
Journal:  Neuroimage       Date:  2019-11-21       Impact factor: 6.556

2.  Streaking artifact reduction for quantitative susceptibility mapping of sources with large dynamic range.

Authors:  Hongjiang Wei; Russell Dibb; Yan Zhou; Yawen Sun; Jianrong Xu; Nian Wang; Chunlei Liu
Journal:  NMR Biomed       Date:  2015-08-27       Impact factor: 4.044

3.  Rapid multi-orientation quantitative susceptibility mapping.

Authors:  Berkin Bilgic; Luke Xie; Russell Dibb; Christian Langkammer; Aysegul Mutluay; Huihui Ye; Jonathan R Polimeni; Jean Augustinack; Chunlei Liu; Lawrence L Wald; Kawin Setsompop
Journal:  Neuroimage       Date:  2015-08-12       Impact factor: 6.556

4.  Quantitative Susceptibility Mapping Suggests Altered Brain Iron in Premanifest Huntington Disease.

Authors:  J M G van Bergen; J Hua; P G Unschuld; I A L Lim; C K Jones; R L Margolis; C A Ross; P C M van Zijl; X Li
Journal:  AJNR Am J Neuroradiol       Date:  2015-12-17       Impact factor: 3.825

5.  Methods for the computation of templates from quantitative magnetic susceptibility maps (QSM): Toward improved atlas- and voxel-based analyses (VBA).

Authors:  Jannis Hanspach; Michael G Dwyer; Niels P Bergsland; Xiang Feng; Jesper Hagemeier; Nicola Bertolino; Paul Polak; Jürgen R Reichenbach; Robert Zivadinov; Ferdinand Schweser
Journal:  J Magn Reson Imaging       Date:  2017-03-06       Impact factor: 4.813

6.  Quantitative oxygenation venography from MRI phase.

Authors:  Audrey P Fan; Berkin Bilgic; Louis Gagnon; Thomas Witzel; Himanshu Bhat; Bruce R Rosen; Elfar Adalsteinsson
Journal:  Magn Reson Med       Date:  2013-09-04       Impact factor: 4.668

Review 7.  Region-Specific Iron Measured by MRI as a Biomarker for Parkinson's Disease.

Authors:  Xiaojun Guan; Xiaojun Xu; Minming Zhang
Journal:  Neurosci Bull       Date:  2017-05-17       Impact factor: 5.203

8.  Simultaneous Time Interleaved MultiSlice (STIMS) for Rapid Susceptibility Weighted acquisition.

Authors:  Berkin Bilgic; Huihui Ye; Lawrence L Wald; Kawin Setsompop
Journal:  Neuroimage       Date:  2017-04-20       Impact factor: 6.556

9.  Simultaneous quantitative susceptibility mapping and Flutemetamol-PET suggests local correlation of iron and β-amyloid as an indicator of cognitive performance at high age.

Authors:  J M G van Bergen; X Li; F C Quevenco; A F Gietl; V Treyer; R Meyer; A Buck; P A Kaufmann; R M Nitsch; P C M van Zijl; C Hock; P G Unschuld
Journal:  Neuroimage       Date:  2018-03-13       Impact factor: 6.556

10.  Altered brain iron content and deposition rate in Huntington's disease as indicated by quantitative susceptibility MRI.

Authors:  Lin Chen; Jun Hua; Christopher A Ross; Shuhui Cai; Peter C M van Zijl; Xu Li
Journal:  J Neurosci Res       Date:  2018-11-29       Impact factor: 4.164

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