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The influence of molecular order and microstructure on the R2* and the magnetic susceptibility tensor
2016
Magnetic Resonance Imaging
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Wisnieff et al.
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Magn Reson Imaging. Author manuscript; available in PMC 2017 June 01. Wisnieff et al. ...
doi:10.1016/j.mri.2015.12.003
pmid:26692502
pmcid:PMC4860046
fatcat:nlsyzwmyvfghxo36kgalgxtxyu
Magnetic susceptibility anisotropy: Cylindrical symmetry from macroscopically ordered anisotropic molecules and accuracy of MRI measurements using few orientations
2013
NeuroImage
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Like these materials, the highly structured and organized nature of the myelin sheath of the white matter leads to its anisotropic magnetic behavior (Liu, 2010; Wisnieff et al., 2012a; Wisnieff et al. ...
doi:10.1016/j.neuroimage.2012.12.050
pmid:23296181
pmcid:PMC3580080
fatcat:skj6eyxdrjaqlomo43jbeveina
Noise Effects in Various Quantitative Susceptibility Mapping Methods
2013
IEEE Transactions on Biomedical Engineering
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Various regularization methods have been proposed for single-orientation quantitative susceptibility mapping (QSM), which is an ill-posed magnetic field to susceptibility source inverse problem. Noise amplification, a major issue in inverse problems, manifests as streaking artifacts and quantification errors in QSM and has not been comparatively evaluated in these algorithms. In this paper, various QSM methods were systematically categorized for noise analysis. Six representative QSM methods
doi:10.1109/tbme.2013.2266795
pmid:23751950
pmcid:PMC5553691
fatcat:dk4giupgzrbbnlgi3qbyehayuq
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... e selected from four categories: two non-Bayesian methods with alteration or approximation of the dipole kernel to overcome the ill conditioning; four Bayesian methods using a general mathematical prior or a specific physical structure prior to select a unique solution, and using a data fidelity term with or without noise weighting. The effects of noise in these QSM methods were evaluated by reconstruction errors in simulation and image quality in 50 consecutive human subjects. Bayesian QSM methods with noise weighting consistently reduced root mean squared errors in numerical simulations and increased image quality scores in the human brain images, when compared to non-Bayesian methods and to corresponding Bayesian methods without noise weighting (p ≤ 0.001). In summary, noise effects in QSM can be reduced using Bayesian methods with proper noise weighting.
Multiple sclerosis lesion geometry in quantitative susceptibility mapping (QSM) and phase imaging
2014
Journal of Magnetic Resonance Imaging
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Purpose-To demonstrate the phase and QSM patterns created by solid and shell spatial distributions of magnetic susceptibility in MS lesions. Materials and Methods-Numerical simulations and experimental phantoms of solid-and shell-shaped magnetic susceptibility sources were used to generate magnitude, phase, and QSM images. Imaging of 20 consecutive MS patients was also reviewed for this IRB-approved MRI study to identify appearance of solid and shell lesions on phase and QSM images.
doi:10.1002/jmri.24745
pmid:25174493
pmcid:PMC4733654
fatcat:l3hp2sxacvgivir36x23wcvwta
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... d and shell susceptibility sources were correctly reconstructed in QSM images, while the corresponding phase images depicted both geometries with shell-like patterns, making the underlying susceptibility distribution difficult to determine using phase alone. In MS patients, of the 60 largest lesions identified on T2, 30 lesions were detected on both QSM and phase, of which 83% were solid and 17% were shells on QSM, and of which 30% were solid and 70% were shell on phase. Of the 21 shell-like lesions on phase, 76% appeared solid on QSM, 24% appeared shell on QSM. Of the five shell-like lesions on QSM, all were shell-like on phase. Conclusion-QSM accurately depicts both solid and shell patterns of magnetic susceptibility, while phase imaging fails to distinguish them. Representative lesions in two MS patients demonstrate that shell appearance on HPF phase imaging can correspond to either solid (e.g. lesion 4) or shell (e.g. lesion 8) on QSM. On the right, lesions visible on T2w are numbered and their geometrical appearances on HPF phase and QSM are listed. Eskreis-Winkler et al.
Quantitative susceptibility mapping (QSM) of white matter multiple sclerosis lesions: Interpreting positive susceptibility and the presence of iron
2014
Magnetic Resonance in Medicine
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Fe] mg/kg QSM (ppb) χ Wisnieff et al. ...
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doi:10.1002/mrm.25420
pmid:25137340
pmcid:PMC4333139
fatcat:2mhr7iwsqjd2rj7bxmtvbunj3u
Morphology enabled dipole inversion for quantitative susceptibility mapping using structural consistency between the magnitude image and the susceptibility map
2012
NeuroImage
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The magnetic susceptibility of tissue can be determined in gradient echo MRI by deconvolving the local magnetic field with the magnetic field generated by a unit dipole. This Quantitative Susceptibility Mapping (QSM) problem is unfortunately ill-posed. By transforming the problem to the Fourier domain, the susceptibility appears to be undersampled only at points where the dipole kernel is zero, suggesting that a modest amount of additional information may be sufficient for uniquely resolving
doi:10.1016/j.neuroimage.2011.08.082
pmid:21925276
pmcid:PMC3254812
fatcat:xks6mznokzenloty5iiah23yyq
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... ceptibility. A Morphology Enabled Dipole Inversion (MEDI) approach is developed that exploits the structural consistency between the susceptibility map and the magnitude image reconstructed from the same gradient echo MRI. Specifically, voxels that are part of edges in the susceptibility map but not in the edges of the magnitude image are considered to be sparse. In this approach an L 1 norm minimization is used to express this sparsity property. Numerical simulations and phantom experiments are performed to demonstrate the superiority of this L 1 minimization approach over the previous L 2 minimization method. Preliminary brain imaging results in healthy subjects and in patients with intracerebral hemorrhages illustrate that QSM is feasible in practice.
Reducing the object orientation dependence of susceptibility effects in gradient echo MRI through quantitative susceptibility mapping
2012
Magnetic Resonance in Medicine
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This study demonstrates the dependence of non-local susceptibility effects on object orientation in gradient echo MRI and the reduction of non-local effects by deconvolution using quantitative susceptibility mapping (QSM). Imaging experiments were performed on a 3T MRI system using a spoiled 3D multi-echo GRE sequence on phantoms of known susceptibilities, and on human brains of healthy subjects and patients with intracerebral hemorrhages. Magnetic field measurements were determined from
doi:10.1002/mrm.24135
pmid:22851199
pmcid:PMC3493252
fatcat:5zsixyjew5aedlo4kmcfm5c7ku
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... e echo phase data. To determine the QSM, these field measurements were deconvolved through a dipole inversion kernel under a constraint of consistency with the magnitude images. Phantom and human data demonstrated that the hypointense region in GRE magnitude image corresponding to a susceptibility source increased in volume with TE and varied with the source orientation. The induced magnetic field extended beyond the susceptibility source and varied with its orientation. In QSM, these blooming artifacts, including their dependence on object orientation, were reduced and material susceptibilities were quantified.
Accuracy of the Morphology Enabled Dipole Inversion (MEDI) Algorithm for Quantitative Susceptibility Mapping in MRI
2012
IEEE Transactions on Medical Imaging
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ACKNOWLEDGMENT We thank Cynthia Wisnieff and Richard Wong at biomedical engineering department of Cornell University for their assistance in preparing the phantom experiment. ...
doi:10.1109/tmi.2011.2182523
pmid:22231170
pmcid:PMC3613569
fatcat:rzzqifsfqzhvvm7x4ldlzknjdi
MAGNETIC SUSCEPTIBILITY APPROACH FOR QUANTITATIVE CEREBRAL OXYGEN METABOLISM MAPPING
2017
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Sanelli, Cynthia Wisnieff, Pascal Spincemaille, and Yi Wang, Abstract 20, Traditional Poster, Cerebral Metabolic Rate of Oxygen (CMRO2) Quantitative Mapping Using Quantitative Susceptibility Mapping (QSM ...
Sanelli, Cynthia Wisnieff, Pascal Spincemaille, and Yi Wang, Abstract, traditional poster, Cerebral Metabolic Rate of Oxygen (CMRO2) Mapping Using Quantitative Susceptibility Mapping (QSM), 25th International ...
doi:10.7298/x4wd3xq6
fatcat:in3zw2ap2rba3fflgw72a6zgk4
APPLICATION-SPECIFIC OPTIMIZATION OF QUANTITATIVE SUSCEPTIBILITY MAPPING FOR CLINICAL IMAGING
2017
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I would like to thank, in no particular order, my other colleagues and friends who on many occasions provided valuable assistance, advices and feedback on my work: Jingwei Zhang, Cynthia Wisnieff, Mitch ...
doi:10.7298/x4m043k7
fatcat:kxpeaopzm5a25o6ry3lzaiwniu