Computation of Magnetic Field Distortions and Impact on T2∗-weighted MRI, with Applications to Magnetic Susceptibility Parameter Estimation

Corey E. Cruttenden, Xiao Hong Zhu, Wei Chen, Rajesh Rajamani

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


A two-step numerical computation of T2∗ signal weighting maps in gradient echo magnetic resonance imaging in the presence of an object with varied susceptibility property is presented. In the first step, the magnetic scalar potential is computed for an arbitrary 2D magnetic susceptibility distribution using an algebraic solver. The corresponding magnetic field disturbance is computed from the magnetic scalar potential. In the second step, nonlinear operations are used to compute T2∗ from the magnetic field disturbance and then to generate a map of T2∗ signal weighting. The linearity of the first step of the solution process is used to implement a superposition of basis solutions approach that increases computational efficiency. Superposition of basis solutions, computed from a system composed of a single node of differing magnetic susceptibility from the surround, herein referred to as the base system, is found to provide an accurate estimation of the scalar potential for arbitrary susceptibility distributions. Afterwards, nonlinear computation of the T2∗ signal weighting maps can be performed. The properties of the algebraic magnetic scalar potential solver are discussed in this work. Finally, the linearity of the magnetic scalar potential solver is used to estimate the magnetic susceptibility of various objects from in vitro MR-imaging data acquired at 9.4 T.

Original languageEnglish (US)
Article number045029
JournalBiomedical Physics and Engineering Express
Issue number4
StatePublished - Jun 14 2018

Bibliographical note

Funding Information:
This work was supported in part by an Institute for Engineering in Medicine (IEM) Group Grant at the University of Minnesota, the University of Minnesota MnDrive RSAM Initiative Grant, the Minnesota Supercomputing Institute (MSI) at the University of Minnesota, NIH grants R01 MH111413, R01 NS070839, R24 MH106049, P41 EB015894, P30 NS076408, the W M Keck Foundation, and NSF-IGERT DGE-1069104.

Publisher Copyright:
© 2018 IOP Publishing Ltd.


  • magnetic field distortion
  • magnetic susceptibility
  • numerical solver


Dive into the research topics of 'Computation of Magnetic Field Distortions and Impact on T<sub>2</sub>∗-weighted MRI, with Applications to Magnetic Susceptibility Parameter Estimation'. Together they form a unique fingerprint.

Cite this