Quantifying MRI frequency shifts due to structures with anisotropic magnetic susceptibility using pyrolytic graphite sheet

Abstract

Magnetic susceptibility is an important source of contrast in magnetic resonance imaging (MRI), with spatial variations in the susceptibility of tissue affecting both the magnitude and phase of the measured signals. This contrast has generally been interpreted by assuming that tissues have isotropic magnetic susceptibility, but recent work has shown that the anisotropic magnetic susceptibility of ordered biological tissues, such as myelinated nerves and cardiac muscle fibers, gives rise to unexpected image contrast. This behavior occurs because the pattern of field variation generated by microstructural elements formed from material of anisotropic susceptibility can be very different from that predicted by modelling the effects in terms of isotropic susceptibility. In MR images of tissue, such elements are manifested at a sub-voxel length-scale, so the patterns of field variation that they generate cannot be directly visualized. Here, we used pyrolytic graphite sheet which has a large magnetic susceptibility anisotropy to form structures of known geometry with sizes large enough that the pattern of field variation could be mapped directly using MRI. This allowed direct validation of theoretical expressions describing the pattern of field variation from anisotropic structures with biologically relevant shapes (slabs, spherical shells and cylindrical shells).

Diagnostic accuracy of quantitative susceptibility mapping in multiple system atrophy: The impact of echo time and the potential of histogram analysis

“…Modeling the complex gray matter microstructure is remarkably challenging, but, even in white matter, the multi-component simulations of phase evolution could only partially explain the variability of measured susceptibility across TEs ( Cronin et al, 2017 ). Even though QSM provides reproducible measurements of tissue susceptibility for matching TEs at the same field strength ( Lancione et al, 2019 , Rua et al, 2020 , Spincemaille et al, 2020 ) when scanning parameters such as coverage ( Elkady et al, 2016 , Karsa et al, 2018 ) and spatial resolution ( Karsa et al, 2018 , Zhou et al, 2017 ) are fixed and the subject’s head is accurately positioned along the same orientation ( Cronin and Bowtell, 2018 , Lancione et al, 2017 , Li et al, 2012 ), the choice of these experimental factors can affect differently the susceptibility values measured in distinct populations. In fact, the net magnitude and phase signal from a voxel with inhomogeneous composition sampled at a certain TE contain information on the subcompartments whose relaxation time T2* is not much shorter than TE.…”

Rapid calculation of static magnetic field perturbation generated by magnetized objects in arbitrary orientations

“…In MRI, susceptibility tensor is studied mostly in the context of tissue microstructure anisotropy 19,35 . Its effect is usually small and highly localized, although an experimental model involving large pyrolytic graphite sheets has been recently considered 36 . Due to its localized effect, susceptibility tensor‐induced B 0 may well be handled by conventional, KD‐based method without concern of aliasing artifacts.…”

“…19,35 Its effect is usually small and highly localized, although an experimental model involving large pyrolytic graphite sheets has been recently considered. 36 Due to its localized effect, susceptibility tensor-induced B 0 may well be handled by conventional, KD-based method without concern of aliasing artifacts. The SVC-based method may still hold benefits in terms of ringing artifact reduction.…”

The 2016 QSM Challenge: Lessons learned and considerations for a future challenge design

“…The latter is the result of microstructure effects and the tensor nature of the susceptibilities of certain tissues. Whereas some studies [40][41][42] have described how microstructure affects phase contrast and its impact on both QSM and STI, we are interested in providing a scalar apparent susceptibility ground truth from STI. For this effect, a projection of the STI data onto a scalar value is required.…”