Quantitative Susceptibility Mapping: Contrast Mechanisms and Clinical Applications.

Quantitative susceptibility mapping (QSM) is a recently developed MRI technique for quantifying the spatial distribution of magnetic susceptibility within biological tissues. It first uses the frequency shift in the MRI signal to map the magnetic field profile within the tissue. The resulting field map is then used to determine the spatial distribution of the underlying magnetic susceptibility by solving an inverse problem. The solution is achieved by deconvolving the field map with a dipole field, under the assumption that the magnetic field is a result of the superposition of the dipole fields generated by all voxels and that each voxel has its unique magnetic susceptibility. QSM provides improved contrast to noise ratio for certain tissues and structures compared to its magnitude counterpart. More importantly, magnetic susceptibility is a direct reflection of the molecular composition and cellular architecture of the tissue. Consequently, by quantifying magnetic susceptibility, QSM is becoming a quantitative imaging approach for characterizing normal and pathological tissue properties. This article reviews the mechanism generating susceptibility contrast within tissues and some associated applications

Probing white-matter microstructure with higher-order diffusion tensors and susceptibility tensor MRI.

Diffusion MRI has become an invaluable tool for studying white matter microstructure and brain connectivity. The emergence of quantitative susceptibility mapping and susceptibility tensor imaging (STI) has provided another unique tool for assessing the structure of white matter. In the highly ordered white matter structure, diffusion MRI measures hindered water mobility induced by various tissue and cell membranes, while susceptibility sensitizes to the molecular composition and axonal arrangement. Integrating these two methods may produce new insights into the complex physiology of white matter. In this study, we investigated the relationship between diffusion and magnetic susceptibility in the white matter. Experiments were conducted on phantoms and human brains in vivo. Diffusion properties were quantified with the diffusion tensor model and also with the higher order tensor model based on the cumulant expansion. Frequency shift and susceptibility tensor were measured with quantitative susceptibility mapping and susceptibility tensor imaging. These diffusion and susceptibility quantities were compared and correlated in regions of single fiber bundles and regions of multiple fiber orientations. Relationships were established with similarities and differences identified. It is believed that diffusion MRI and susceptibility MRI provide complementary information of the microstructure of white matter. Together, they allow a more complete assessment of healthy and diseased brains

Magnetic susceptibility anisotropy of myocardium imaged by cardiovascular magnetic resonance reflects the anisotropy of myocardial filament α-helix polypeptide bonds.

BackgroundA key component of evaluating myocardial tissue function is the assessment of myofiber organization and structure. Studies suggest that striated muscle fibers are magnetically anisotropic, which, if measurable in the heart, may provide a tool to assess myocardial microstructure and function.MethodsTo determine whether this weak anisotropy is observable and spatially quantifiable with cardiovascular magnetic resonance (CMR), both gradient-echo and diffusion-weighted data were collected from intact mouse heart specimens at 9.4 Tesla. Susceptibility anisotropy was experimentally calculated using a voxelwise analysis of myocardial tissue susceptibility as a function of myofiber angle. A myocardial tissue simulation was developed to evaluate the role of the known diamagnetic anisotropy of the peptide bond in the observed susceptibility contrast.ResultsThe CMR data revealed that myocardial tissue fibers that were parallel and perpendicular to the magnetic field direction appeared relatively paramagnetic and diamagnetic, respectively. A linear relationship was found between the magnetic susceptibility of the myocardial tissue and the squared sine of the myofiber angle with respect to the field direction. The multi-filament model simulation yielded susceptibility anisotropy values that reflected those found in the experimental data, and were consistent that this anisotropy decreased as the echo time increased.ConclusionsThough other sources of susceptibility anisotropy in myocardium may exist, the arrangement of peptide bonds in the myofilaments is a significant, and likely the most dominant source of susceptibility anisotropy. This anisotropy can be further exploited to probe the integrity and organization of myofibers in both healthy and diseased heart tissue

The effect of realistic geometries on the susceptibility-weighted MR signal in white matter

Purpose: To investigate the effect of realistic microstructural geometry on the susceptibility-weighted magnetic resonance (MR) signal in white matter (WM), with application to demyelination. Methods: Previous work has modeled susceptibility-weighted signals under the assumption that axons are cylindrical. In this work, we explore the implications of this assumption by considering the effect of more realistic geometries. A three-compartment WM model incorporating relevant properties based on literature was used to predict the MR signal. Myelinated axons were modeled with several cross-sectional geometries of increasing realism: nested circles, warped/elliptical circles and measured axonal geometries from electron micrographs. Signal simulations from the different microstructural geometries were compared to measured signals from a Cuprizone mouse model with varying degrees of demyelination. Results: Results from simulation suggest that axonal geometry affects the MR signal. Predictions with realistic models were significantly different compared to circular models under the same microstructural tissue properties, for simulations with and without diffusion. Conclusion: The geometry of axons affects the MR signal significantly. Literature estimates of myelin susceptibility, which are based on fitting biophysical models to the MR signal, are likely to be biased by the assumed geometry, as will any derived microstructural properties.Comment: Accepted March 4 2017, in publication at Magnetic Resonance in Medicin

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

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)

Quantitative Susceptibility Imaging of Tissue Microstructure Using Ultra-High Field MRI

This thesis has used ultra-high field (UHF) magnetic resonance imaging (MRI) to investigate the fundamental relationships between tissue microstructure and such susceptibility-based contrast parameters as the apparent transverse relaxation rate (R2*), the local Larmor frequency shift (LFS) and quantitative volume magnetic susceptibility (QS). The interaction of magnetic fields with biological tissues results in shifts in the LFS which can be used to distinguish underlying cellular architecture. The LFS is also linked to the relaxation properties of tissues in a gradient echo MRI sequence. Equally relevant, histological analysis has identified iron and myelin as two major sources of the LFS. As a result, computation of LFS and the associated volume magnetic susceptibility from MRI phase data may serve as a significant method for in vivo monitoring of changes in iron and myelin associated with normal, healthy aging, as well as neurological disease processes. In this research, the cellular level underpinnings of the R2* and LFS signals were examined in a model rat brain system using 9.4 T MRI. The study was carried out using biophysical modeling and correlation with quantitative histology. For the first time, multiple biophysical modeling schemes were compared in both gray and white matter of excised rat brain tissue. Suprisingly, R2* dependence on tissue orientation has not been fully understood. Accordingly, scaling relations were derived for calculating the reversible, mesoscopic magnetic field component, R2\u27, of the apparent transverse relaxation rate from the orientation dependence in gray and white matter. Our results demonstrate that the orientation dependence of R2* and LFS in both white and cortical gray matter has a sinusoidal dependence on tissue orientation and a linear dependence on the volume fraction of myelin in the tissue. A susceptibility processing pipeline was also developed and applied to the calculation of phase-combined LFS and QS maps. The processing pipeline was subsequently used to monitor myelin and iron changes in multiple sclerosis (MS) patients compared to healthy, age and gender-matched controls. With the use of QS and R2* mapping, evidence of statistically significant increases in iron deposition in sub-cortical gray matter, as well as myelin degeneration along the white matter skeleton, were identified in MS patients. The magnetic susceptibility-based MRI methods were then employed as potential clinical biomarkers for disease severity monitoring of MS. It was demonstrated that the combined use of R2* and QS, obtained from multi-echo gradient echo MRI, could serve as an improved metric for monitoring both gray and white matter changes in early MS

Fiber orientation-dependent white matter contrast in gradient echo MRI

Recent studies have shown that there is a direct link between the orientation of the nerve fibers in white matter (WM) and the contrast observed in magnitude and phase images acquired using gradient echo MRI. Understanding the origin of this link is of great interest because it could offer access to a new diagnostic tool for investigating tissue microstructure. Since it has been suggested that myelin is the dominant source of this contrast, creating an accurate model for characterizing the effect of the myelin sheath on the evolution of the NMR signal is an essential step toward fully understanding WM contrast. In this study, we show by comparison of the results of simulations and experiments carried out on human subjects at 7T, that the magnitude and phase of signals acquired from WM in vivo can be accurately characterized by (i) modeling the myelin sheath as a hollow cylinder composed of material having an anisotropic magnetic susceptibility that is described by a tensor with a radially oriented principal axis, and (ii) adopting a two-pool model in which the water in the sheath has a reduced T2 relaxation time and spin density relative to its surroundings, and also undergoes exchange. The accuracy and intrinsic simplicity of the hollow cylinder model provides a versatile framework for future exploitation of the effect of WM microstructure on gradient echo contrast in clinical MRI. Gradient echo (GE) MRI is widely used in imaging the human brain, because both the phase and magnitude of the complex NMR signal measured with GE sequences can be used to create high-resolution images that show strong contrast between different types of brain tissue (1). Recent studies have shown that there is a direct link between the orientation of the nerve fibers in white matter (WM) with respect to the magnetic field and the contrast observed in magnitude and phase images (2⇓⇓⇓–6). Although the origin of this link is currently not fully understood, orientation-dependent contrast is of great interest because it could offer researchers access to a new diagnostic tool for investigating tissue microstructure using MRI. It has recently been suggested that the myelin sheaths that surround axons are the dominant source of WM contrast in GE MRI (7, 8). Creating an accurate model for characterizing the effect of the myelin sheath on the evolution of the magnitude and phase of the NMR signal is consequently an essential step toward fully understanding WM contrast and its relationship to fiber orientation. Such a model must incorporate two main features: (i) a representation of the microscopic spatial variation of resonant frequency, due to the myelin compartment—isotropic and anisotropic magnetic susceptibility effects (2, 9, 10) and chemical exchange of protons between water and macromolecules (11, 12), have been proposed as mechanisms through which myelin could perturb the resonant frequency in WM; (ii) a signal-weighting scheme to account for the reduced T2 relaxation time constant of the myelin water relative to that of water found outside the myelin sheath (13⇓–15). In this study, we show by comparison of the results of simulations and experiments that the fiber orientation dependence of the magnitude and phase of signals acquired from WM in vivo can be accurately characterized by (i) modeling the myelin sheath as a hollow cylinder composed of material having an anisotropic susceptibility that is described by a tensor with a radially oriented principal axis, and (ii) adopting a two-pool model in which the water in the sheath has a reduced T2 relaxation constant and effective spin density relative to its surroundings, and also undergoes exchange

Effects of white matter microstructure on phase and susceptibility maps

Purpose: To investigate the effects on quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI) of the frequency variation produced by the microstructure of white matter (WM). Methods: The frequency offsets in a WM tissue sample that are not explained by the effect of bulk isotropic or anisotropic magnetic susceptibility, but rather result from the local microstructure, were characterized for the first time. QSM and STI were then applied to simulated frequency maps that were calculated using a digitized whole-brain, WM model formed from anatomical and diffusion tensor imaging data acquired from a volunteer. In this model, the magnitudes of the frequency contributions due to anisotropy and microstructure were derived from the results of the tissue experiments. Results: The simulations suggest that the frequency contribution of microstructure is much larger than that due to bulk effects of anisotropic magnetic susceptibility. In QSM, the microstructure contribution introduced artificial WM heterogeneity. For the STI processing, the microstructure contribution caused the susceptibility anisotropy to be significantly overestimated. Conclusion: Microstructure-related phase offsets in WM yield artifacts in the calculated susceptibility maps. If susceptibility mapping is to become a robust MRI technique, further research should be carried out to reduce the confounding effects of microstructure-related frequency contribution

Effects of white matter microstructure on phase and susceptibility maps

Purpose: To investigate the effects on quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI) of the frequency variation produced by the microstructure of white matter (WM). Methods: The frequency offsets in a WM tissue sample that are not explained by the effect of bulk isotropic or anisotropic magnetic susceptibility, but rather result from the local microstructure, were characterized for the first time. QSM and STI were then applied to simulated frequency maps that were calculated using a digitized whole-brain, WM model formed from anatomical and diffusion tensor imaging data acquired from a volunteer. In this model, the magnitudes of the frequency contributions due to anisotropy and microstructure were derived from the results of the tissue experiments. Results: The simulations suggest that the frequency contribution of microstructure is much larger than that due to bulk effects of anisotropic magnetic susceptibility. In QSM, the microstructure contribution introduced artificial WM heterogeneity. For the STI processing, the microstructure contribution caused the susceptibility anisotropy to be significantly overestimated. Conclusion: Microstructure-related phase offsets in WM yield artifacts in the calculated susceptibility maps. If susceptibility mapping is to become a robust MRI technique, further research should be carried out to reduce the confounding effects of microstructure-related frequency contribution