Literature DB >> 25339652

Quantitative susceptibility mapping of human brain at 3T: a multisite reproducibility study.

P-Y Lin1, T-C Chao2, M-L Wu3.   

Abstract

BACKGROUND AND
PURPOSE: Quantitative susceptibility mapping of the human brain has demonstrated strong potential in examining iron deposition, which may help in investigating possible brain pathology. This study assesses the reproducibility of quantitative susceptibility mapping across different imaging sites.
MATERIALS AND METHODS: In this study, the susceptibility values of 5 regions of interest in the human brain were measured on 9 healthy subjects following calibration by using phantom experiments. Each of the subjects was imaged 5 times on 1 scanner with the same procedure repeated on 3 different 3T systems so that both within-site and cross-site quantitative susceptibility mapping precision levels could be assessed. Two quantitative susceptibility mapping algorithms, similar in principle, one by using iterative regularization (iterative quantitative susceptibility mapping) and the other with analytic optimal solutions (deterministic quantitative susceptibility mapping), were implemented, and their performances were compared.
RESULTS: Results show that while deterministic quantitative susceptibility mapping had nearly 700 times faster computation speed, residual streaking artifacts seem to be more prominent compared with iterative quantitative susceptibility mapping. With quantitative susceptibility mapping, the putamen, globus pallidus, and caudate nucleus showed smaller imprecision on the order of 0.005 ppm, whereas the red nucleus and substantia nigra, closer to the skull base, had a somewhat larger imprecision of approximately 0.01 ppm. Cross-site errors were not significantly larger than within-site errors. Possible sources of estimation errors are discussed.
CONCLUSIONS: The reproducibility of quantitative susceptibility mapping in the human brain in vivo is regionally dependent, and the precision levels achieved with quantitative susceptibility mapping should allow longitudinal and multisite studies such as aging-related changes in brain tissue magnetic susceptibility.
© 2015 by American Journal of Neuroradiology.

Entities:  

Mesh:

Year:  2014        PMID: 25339652      PMCID: PMC8013073          DOI: 10.3174/ajnr.A4137

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  27 in total

1.  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

2.  Whole-brain susceptibility mapping at high field: a comparison of multiple- and single-orientation methods.

Authors:  Sam Wharton; Richard Bowtell
Journal:  Neuroimage       Date:  2010-07-06       Impact factor: 6.556

3.  Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization: validation and application to brain imaging.

Authors:  Ludovic de Rochefort; Tian Liu; Bryan Kressler; Jing Liu; Pascal Spincemaille; Vincent Lebon; Jianlin Wu; Yi Wang
Journal:  Magn Reson Med       Date:  2010-01       Impact factor: 4.668

4.  Whole brain susceptibility mapping using compressed sensing.

Authors:  Bing Wu; Wei Li; Arnaud Guidon; Chunlei Liu
Journal:  Magn Reson Med       Date:  2011-06-10       Impact factor: 4.668

5.  Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition.

Authors:  Wei Li; Bing Wu; Chunlei Liu
Journal:  Neuroimage       Date:  2011-01-09       Impact factor: 6.556

6.  Toward in vivo histology: a comparison of quantitative susceptibility mapping (QSM) with magnitude-, phase-, and R2*-imaging at ultra-high magnetic field strength.

Authors:  Andreas Deistung; Andreas Schäfer; Ferdinand Schweser; Uta Biedermann; Robert Turner; Jürgen R Reichenbach
Journal:  Neuroimage       Date:  2012-10-02       Impact factor: 6.556

7.  MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping.

Authors:  Berkin Bilgic; Adolf Pfefferbaum; Torsten Rohlfing; Edith V Sullivan; Elfar Adalsteinsson
Journal:  Neuroimage       Date:  2011-09-08       Impact factor: 6.556

8.  A novel background field removal method for MRI using projection onto dipole fields (PDF).

Authors:  Tian Liu; Ildar Khalidov; Ludovic de Rochefort; Pascal Spincemaille; Jing Liu; A John Tsiouris; Yi Wang
Journal:  NMR Biomed       Date:  2011-03-08       Impact factor: 4.044

9.  Fast and tissue-optimized mapping of magnetic susceptibility and T2* with multi-echo and multi-shot spirals.

Authors:  Bing Wu; Wei Li; Alexandru Vlad Avram; Sung-Min Gho; Chunlei Liu
Journal:  Neuroimage       Date:  2011-07-19       Impact factor: 6.556

10.  Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures.

Authors:  Issel Anne L Lim; Andreia V Faria; Xu Li; Johnny T C Hsu; Raag D Airan; Susumu Mori; Peter C M van Zijl
Journal:  Neuroimage       Date:  2013-06-12       Impact factor: 6.556

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  21 in total

1.  Quantitative susceptibility mapping of the motor cortex: a comparison of susceptibility among patients with amyotrophic lateral sclerosis, cerebrovascular disease, and healthy controls.

Authors:  Ji Young Lee; Young-Jun Lee; Dong Woo Park; Yoonho Nam; Seung Hyun Kim; Jinseok Park; Young Seo Kim; Hyun Young Kim; Ki-Wook Oh
Journal:  Neuroradiology       Date:  2017-10-11       Impact factor: 2.804

2.  Reproducibility of quantitative susceptibility mapping in the brain at two field strengths from two vendors.

Authors:  Kofi Deh; Thanh D Nguyen; Sarah Eskreis-Winkler; Martin R Prince; Pascal Spincemaille; Susan Gauthier; Ilhami Kovanlikaya; Yan Zhang; Yi Wang
Journal:  J Magn Reson Imaging       Date:  2015-05-09       Impact factor: 4.813

Review 3.  Clinical quantitative susceptibility mapping (QSM): Biometal imaging and its emerging roles in patient care.

Authors:  Yi Wang; Pascal Spincemaille; Zhe Liu; Alexey Dimov; Kofi Deh; Jianqi Li; Yan Zhang; Yihao Yao; Kelly M Gillen; Alan H Wilman; Ajay Gupta; Apostolos John Tsiouris; Ilhami Kovanlikaya; Gloria Chia-Yi Chiang; Jonathan W Weinsaft; Lawrence Tanenbaum; Weiwei Chen; Wenzhen Zhu; Shixin Chang; Min Lou; Brian H Kopell; Michael G Kaplitt; David Devos; Toshinori Hirai; Xuemei Huang; Yukunori Korogi; Alexander Shtilbans; Geon-Ho Jahng; Daniel Pelletier; Susan A Gauthier; David Pitt; Ashley I Bush; Gary M Brittenham; Martin R Prince
Journal:  J Magn Reson Imaging       Date:  2017-03-10       Impact factor: 4.813

4.  Mapping of thalamic magnetic susceptibility in multiple sclerosis indicates decreasing iron with disease duration: A proposed mechanistic relationship between inflammation and oligodendrocyte vitality.

Authors:  Ferdinand Schweser; Ana Luiza Raffaini Duarte Martins; Jesper Hagemeier; Fuchun Lin; Jannis Hanspach; Bianca Weinstock-Guttman; Simon Hametner; Niels Bergsland; Michael G Dwyer; Robert Zivadinov
Journal:  Neuroimage       Date:  2017-10-31       Impact factor: 6.556

5.  Simultaneous QSM and metabolic imaging of the brain using SPICE.

Authors:  Xi Peng; Fan Lam; Yudu Li; Bryan Clifford; Zhi-Pei Liang
Journal:  Magn Reson Med       Date:  2017-10-24       Impact factor: 4.668

6.  Quantitative susceptibility mapping (QSM) minimizes interference from cellular pathology in R2* estimation of liver iron concentration.

Authors:  Jianqi Li; Huimin Lin; Tian Liu; Zhuwei Zhang; Martin R Prince; Kelly Gillen; Xu Yan; Qi Song; Ting Hua; Xiance Zhao; Miao Zhang; Yu Zhao; Gaiying Li; Guangyu Tang; Guang Yang; Gary M Brittenham; Yi Wang
Journal:  J Magn Reson Imaging       Date:  2018-03-22       Impact factor: 4.813

7.  Clinical feasibility of brain quantitative susceptibility mapping.

Authors:  Shun Zhang; Zhe Liu; Thanh D Nguyen; Yihao Yao; Kelly M Gillen; Pascal Spincemaille; Ilhami Kovanlikaya; Ajay Gupta; Yi Wang
Journal:  Magn Reson Imaging       Date:  2019-04-04       Impact factor: 2.546

8.  Clinical Integration of Automated Processing for Brain Quantitative Susceptibility Mapping: Multi-Site Reproducibility and Single-Site Robustness.

Authors:  Pascal Spincemaille; Zhe Liu; Shun Zhang; Ilhami Kovanlikaya; Matteo Ippoliti; Marcus Makowski; Richard Watts; Ludovic de Rochefort; Vijay Venkatraman; Patricia Desmond; Mathieu D Santin; Stéphane Lehéricy; Brian H Kopell; Patrice Péran; Yi Wang
Journal:  J Neuroimaging       Date:  2019-08-04       Impact factor: 2.486

9.  Multicenter reproducibility of quantitative susceptibility mapping in a gadolinium phantom using MEDI+0 automatic zero referencing.

Authors:  Kofi Deh; Keigo Kawaji; Marjolein Bulk; Louise Van Der Weerd; Emelie Lind; Pascal Spincemaille; Kelly McCabe Gillen; Johan Van Auderkerke; Yi Wang; Thanh D Nguyen
Journal:  Magn Reson Med       Date:  2018-10-04       Impact factor: 4.668

10.  Age and sex related differences in subcortical brain iron concentrations among healthy adults.

Authors:  Ninni Persson; Jianlin Wu; Qing Zhang; Ting Liu; Jing Shen; Ruyi Bao; Mingfei Ni; Tian Liu; Yi Wang; Pascal Spincemaille
Journal:  Neuroimage       Date:  2015-07-26       Impact factor: 6.556

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