MR susceptometry: an external‐phantom method for measuring bulk susceptibility from field‐echo phase reconstruction maps

Holt, Randall W.; Diaz, Pedro J.; Duerk, Jeffrey L.; Bellon, Errol M.

doi:10.1002/jmri.1880040612

Cited by 38 publications

(30 citation statements)

References 14 publications

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“…The field perturbation of the model was calculated by fast forward field computation (Holt et al, 1994;Koch et al, 2006;Marques and Bowtell, 2005;Salomir et al, 2003) (B 0 = 3 T; axial orientation) and converted to GRE phase values (TE = 22 ms). Afterwards, a pattern of normally distributed noise (standard deviation: 0.03 rad) was added to mimic measurement phase noise in the presence of a high signalto-noise ratio of the magnitude signal (Gudbjartsson and Patz, 1995).…”

Section: Realistic Numerical Brain Modelmentioning

confidence: 99%

Quantitative susceptibility mapping for investigating subtle susceptibility variations in the human brain

et al. 2012

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Section: Realistic Numerical Brain Modelmentioning

confidence: 99%

Quantitative susceptibility mapping for investigating subtle susceptibility variations in the human brain

et al. 2012

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“…Recently scientists and clinicians have a growing interest in quantification of susceptibility distribution and susceptibility weighted imaging using MRI because of the direct benefits in diagnosis and study of diseases, such as tumors, hemorrhage, multiple sclerosis, stroke, trauma, cerebral amyloid angiopathy, and iron overloading in organs, like liver and heart [3][4][5][6][7][8][9][10][11][12]. Based on certain geometrical models, such as an infinite cylinder or sphere, or by analyzing boundary conditions for more complex shapes, susceptibility is quantified for specific applications [13][14][15][16]. However, it is an intrinsically ill-posed problem that susceptibility inversion from the measured magnetic field inhomogeneity remains challenging.…”

Section: Introductionmentioning

confidence: 99%

Susceptibility quantification in MRI using modified conjugate gradient least square method

2011

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MR susceptometry provides a new approach to enhance contrast in MR imaging and quantify substances such as iron, calcium, blood oxygenation in various organs for the clinical diagnosis of many diseases. Susceptibility is closely related to the magnetic field inhomogeneity in MRI, and calculation of susceptibility from the measured magnetic field is an illposed inverse problem. Conjugate gradient least square (CGLS) method with Tikhonov regularization is a powerful tool to solve the inverse problems. However, the estimated quantity in CGLS method is usually in one-dimensional (e.g., a column vector) while the most of MR data are in the form of three dimensions. In this work, the least square problem is modified to enable the calculation of susceptibility directly from three-dimensional MR phase maps, which has the benefit of reducing the size of associated matrices and usage of computer memories. Numerical simulations were used to find the proper regularization parameters and study the influence of different noise levels of the magnetic field on the regularization parameters. Experiments of superparamagnetic iron oxide phantom were also conducted. Both of the results demonstrate the validation and accuracy of this method.

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“…Testing of material brought into the magnetic field is one way to assure magnetic compatibility, e.g., in advance of implantation 19 or in advance of use in surgical interventions.…”

Section: Introductionmentioning

confidence: 99%

Numerical modeling of needle tip artifacts in MR gradient echo imaging

Müller‐Bierl¹,

Graf²,

Lauer³

et al. 2004

Med. Phys.

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Exact determination of needle tip position is obsolete for interventional procedures under control of magnetic resonance imaging (MRI). Exact needle tip navigation is complicated by the paramagnetism of microsurgical instruments: Local magnetic field inhomogeneities are induced resulting in position encoding artifacts and in signal voids in the surrounding of instruments and especially near their tips. The artifacts generated by the susceptibility of the material are not only dependent on the material properties themselves and on the applied MRI sequences and parameters, but also on the geometric shape of the instruments and on the orientation to the static magnetic field in the MR unit. A numerical model based on superposition of induced elementary dipole fields was developed for studying the field distortions near paramagnetic needle tips. The model was validated by comparison with experimental data using field mapping MRI techniques. Comparison between experimental data and numerical simulations revealed good correspondence for the induced field inhomogeneities. Further systematic numerical studies of the field distribution were performed for variable types of concentric and asymmetric tip shapes, for different ratios between tip length and needle diameter, and for different orientations of the needle axis in the external static magnetic field. Based on the computed local inhomogeneities of the magnetic field in the surroundings of the needle tips, signal voids in usual gradient echo images were simulated for a prediction of the artifacts. The practically relevant spatial relation between those artifacts and the hidden tip of the needle was calculated for the different tip shapes and orientations in the external field. As needle tip determination is crucial in interventional procedures, e.g., in taking biopsies, the present model can help to instruct the physician prior to surgical interventions in better estimating the needle tip position for different orientations and needle tip shapes as they appear in interventional procedures. As manufacturing prototypes with subsequent measurements of artifacts in MRI are a costly procedure the presented model may also help to optimize shapes of needle tips and of other parts of MR-compatible instruments and implants with low expense prior to production if some shape parameters can be chosen freely.

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MR susceptometry: an external‐phantom method for measuring bulk susceptibility from field‐echo phase reconstruction maps

Cited by 38 publications

References 14 publications

Quantitative susceptibility mapping for investigating subtle susceptibility variations in the human brain

Quantitative susceptibility mapping for investigating subtle susceptibility variations in the human brain

Susceptibility quantification in MRI using modified conjugate gradient least square method

Numerical modeling of needle tip artifacts in MR gradient echo imaging

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