Susceptibility tensor imaging

Heterogeneity of magnetic susceptibility within brain tissues creates unique contrast between gray and white matter in magnetic resonance phase images acquired by gradient echo sequences. Detailed understanding of this contrast may provide meaningful diagnostic information. In this communication, we report an observation of extensive anisotropic magnetic susceptibility in the white matter of the central nervous system. Furthermore, we describe a susceptibility tensor imaging technique to measure and quantify this phenomenon. This technique relies on the measurement of resonance frequency offset at different orientations with respect to the main magnetic field. We propose to characterize this orientation variation using an apparent susceptibility tensor. The susceptibility tensor can be decomposed into three eigenvalues (principal susceptibilities) and associated eigenvectors that are coordinate‐system independent. We show that the principal susceptibilities offer strong contrast between gray and white matter, whereas the eigenvectors provide orientation information of an underlying magnetic network. We believe that this network may further offer information of white matter fiber orientation. Magn Reson Med 63:1471–1477, 2010. © 2010 Wiley‐Liss, Inc.

[1]  Pascal Spincemaille,et al.  Nonlinear Regularization for Per Voxel Estimation of Magnetic Susceptibility Distributions From MRI Field Maps , 2010, IEEE Transactions on Medical Imaging.

[2]  Jeff H. Duyn,et al.  On the contribution of deoxy-hemoglobin to MRI gray–white matter phase contrast at high field , 2010, NeuroImage.

[3]  K. Shmueli,et al.  The Contribution of Exchange to MRI Phase Contrast in the Human Brain , 2009, NeuroImage.

[4]  Jeff H. Duyn,et al.  Susceptibility contrast in high field MRI of human brain as a function of tissue iron content , 2009, NeuroImage.

[5]  Yi Wang,et al.  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 , 2009, Magnetic resonance in medicine.

[6]  E. Haacke,et al.  Susceptibility-Weighted Imaging: Technical Aspects and Clinical Applications, Part 1 , 2008, American Journal of Neuroradiology.

[7]  Yi Wang,et al.  Quantitative MR susceptibility mapping using piece‐wise constant regularized inversion of the magnetic field , 2008, Magnetic resonance in medicine.

[8]  Oliver Speck,et al.  The molecular basis for gray and white matter contrast in phase imaging , 2008, NeuroImage.

[9]  Carlo Ciulla,et al.  Establishing a baseline phase behavior in magnetic resonance imaging to determine normal vs. abnormal iron content in the brain , 2007, Journal of magnetic resonance imaging : JMRI.

[10]  G. Allan Johnson,et al.  High-throughput morphologic phenotyping of the mouse brain with magnetic resonance histology , 2007, NeuroImage.

[11]  Jeff H. Duyn,et al.  High-field MRI of brain cortical substructure based on signal phase , 2007, Proceedings of the National Academy of Sciences.

[12]  E M Haacke,et al.  Imaging cerebral amyloid angiopathy with susceptibility-weighted imaging. , 2007, AJNR. American journal of neuroradiology.

[13]  Yu-Chung N. Cheng,et al.  Susceptibility weighted imaging (SWI) , 2004, Zeitschrift fur medizinische Physik.

[14]  J. Reichenbach,et al.  Magnetic susceptibility-weighted MR phase imaging of the human brain. , 2005, AJNR. American journal of neuroradiology.

[15]  O. Seror,et al.  L'imagerie de susceptibilité magnétique: Théorie et applications , 2004 .

[16]  John S Leigh,et al.  Quantifying arbitrary magnetic susceptibility distributions with MR , 2004, Magnetic resonance in medicine.

[17]  M. Moseley,et al.  Magnetic Resonance in Medicine 51:924–937 (2004) Characterizing Non-Gaussian Diffusion by Using Generalized Diffusion Tensors , 2022 .

[18]  E. Haacke,et al.  [Susceptibility weighted imaging. Theory and applications]. , 2004, Journal de radiologie.

[19]  Rudolf Stollberger,et al.  Automated unwrapping of MR phase images applied to BOLD MR‐venography at 3 Tesla , 2003, Journal of magnetic resonance imaging : JMRI.

[20]  C. Moonen,et al.  A fast calculation method for magnetic field inhomogeneity due to an arbitrary distribution of bulk susceptibility , 2003 .

[21]  L. Hedlund,et al.  Magnetic resonance histology for morphologic phenotyping , 2002, Journal of magnetic resonance imaging : JMRI.

[22]  Lin Li,et al.  Magnetic susceptibility quantification for arbitrarily shaped objects in inhomogeneous fields , 2001, Magnetic resonance in medicine.

[23]  P. Basser,et al.  In vivo fiber tractography using DT‐MRI data , 2000, Magnetic resonance in medicine.

[24]  M. Raichle,et al.  Tracking neuronal fiber pathways in the living human brain. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[25]  P. V. van Zijl,et al.  Three‐dimensional tracking of axonal projections in the brain by magnetic resonance imaging , 1999, Annals of neurology.

[26]  M. Saunders Solution of sparse rectangular systems using LSQR and CRAIG , 1995 .

[27]  P. Basser Inferring microstructural features and the physiological state of tissues from diffusion‐weighted images , 1995, NMR in biomedicine.

[28]  P. Basser,et al.  Estimation of the effective self-diffusion tensor from the NMR spin echo. , 1994, Journal of magnetic resonance. Series B.

[29]  L. Kaufman,et al.  Hemorrhagic and nonhemorrhagic brain lesions: evaluation with 0.35-T fast MR imaging. , 1987, Radiology.

[30]  C. Higgins,et al.  Suspected intracardiac masses: evaluation with MR imaging. , 1987, Radiology.

[31]  G M Bydder,et al.  Clinical magnetic susceptibility mapping of the brain. , 1987, Journal of computer assisted tomography.

[32]  R R Edelman,et al.  MR of hemorrhage: a new approach. , 1986, AJNR. American journal of neuroradiology.

[33]  R. Zimmerman,et al.  Intracranial hematomas: imaging by high-field MR. , 1986, Radiology.