Quantitative Susceptibility Mapping in the Human Brain

Magnetic resonance imaging (MRI) offers a good tissue contrast and the ability to visualize many disease related morphologies. The work presented in this thesis investigates the study of underlying structure of the brain using quantitative methods with a special emphasis on quantitative susceptibility mapping (QSM). Magnetic susceptibility reflects the interaction of a material to the magnetic field and measures in biological tissues the magnetic susceptibility of inclusions. The reconstruction of QSM requires further processing steps as the magnetic field produced by the sources needs to be disentangled from the orders of magnitude bigger background field. The produced field also depends not only on the shape and the orientation, but also on the anisotropy of susceptibility and the microstructural compartmentalization of the biological source. For this reason, reconstruction methods need to be capable to calculate accurate values for different brain regions as well as applicable in the everyday clinical diagnosis. Within the framework of the thesis a data acquisition protocol based on a multiple-echo gradient echo sequence as well as a post-processing protocol was implemented. One of the processing steps, the background removal method, was applied to preserve the brain regions close to the cerebrospinal fluid (CSF). This method outperforms state of the art methods in this regions but is computationally intensive. Different brain regions were studied using quantitative methods with special emphasis on the QSM. A new method, modulated closed form solution, with extremely fast computational time is proposed. The comparison with other single orientation methods revealed similar results and the highest correlation to the state-of-the-art method (COSMOS) in the deep gray matter. The R2* maps calculated from the same dataset are also able to distinguish the deep gray matter structures with a similar quality. However, QSM shows a higher sensitivity in early stage multiple sclerosis lesions as well as white matter-gray matter structures. In the human cortex the obtained cortical maps show enhancement of primary sensory cortex, which is known to be highly myelinated, on three evaluated quantitative contrasts R1,R2* and susceptibility. The contrasts based on the relaxation rates, R1 and R2*, show a monotonically decrease from the white matter to the CSF imitating the decrease in iron and myelin. The susceptibility behaviour is more complex as iron and myelin content introduce an opposing sensitivity, allowing to study iron and myelin content when combining the three contrasts. The microstructural organization of white matter influences the R2*, R2 as well as field map from which QSM is calculated. This structure leads to an orientation dependence of the studied contrasts and for QSM the spherical assumption is not valid anymore. Therefore a new QSM method is introduced, which includes the Lorentzian correction in white matter. Main fibres such as forceps major and minor were analysed for the three different quantitative contrasts. The anisotropic component associated with susceptibility is similar for the relaxation rates whereas the isotropic component of R2* shows a higher variability. The resulting deep gray matter structure of the new QSM method remained similar to the state-of-the-art method when comparing the isotropic component but calculates physically meaningful susceptibility maps with improved contrast between known fibre bundles.

Studying cyto and myeloarchitecture of the human cortex at ultra-high field with quantitative imaging: R1, R⁎2 and susceptibility

Rolf Gruetter, Diana Khabipova, José Pedro Rebelo Ferreira Marques

In this manuscript, the use of quantitative imaging at ultra-high field is evaluated as a mean to study cyto and myelo-architecture of the cortex. The quantitative contrasts used are the longitudinal relaxation rate (R1), apparent transverse relaxation rate (R2⁎) and quantitative susceptibility mapping (QSM). The quantitative contrasts were computed using high resolution in-vivo (0.65mm isotropic) brain data acquired at 7 T. The performance of the different quantitative approaches was evaluated by visualizing the contrast between known highly myelinated primary sensory cortex regions and the neighbouring cortex. The transition from the inner layers to the outer layers (from white matter to the pial surface) of the human cortex, which is known to have varying cyto- and myelo architecture, was evaluated. The across cortex and through depth behaviour observed for the different quantitative maps was in good agreement between the different subjects, clearly allowing the differentiation between different Brodmann regions, suggesting these features could be used for individual cortical brain parcellation. While both R1 and R2⁎ maps decrease monotonically from the white matter to the pial surface due to the decrease of myelin and iron between these regions, magnetic susceptibility maps have a more complex behaviour reflecting its opposing sensitivity to myelin and iron concentration.

Elsevier2017

On the origin of the MR image phase contrast: An in vivo MR microscopy study of the rat brain at 14.1 T

Rolf Gruetter, Rajika Maddage, José Pedro Rebelo Ferreira Marques

Recent studies at high magnetic fields using the phase of gradient-echo MR images have shown the ability to unveil cortical substructure in the human brain. To investigate the contrast mechanisms in phase imaging, this study extends, for the first time, phase imaging to the rodent brain. Using a 14.1 T horizontal bore animal MRI scanner for in vivo micro-imaging, images with an in-plane resolution of 33 mu m were acquired. Phase images revealed, often more clearly than the corresponding magnitude images, hippocampal fields, cortical layers (e. g. layer 4), cerebellar layers (molecular and granule cell layers) and small white matter structures present in the striatum and septal nucleus. The contrast of the phase images depended in part on the orientation of anatomical structures relative to the magnetic field, consistent with bulk susceptibility variations between tissues. This was found not only for vessels, but also for white matter structures, such as the anterior commissure, and cortical layers in the cerebellum.

Elsevier2009

Exploring dynamic functional connectivity by incorporating prior knowledge of brain structure

Anjali Bagunu Tarun

The synchronized firing of distant neuronal populations gives rise to a wide array of functional brain networks that underlie human brain function. Given the enormous perception, learning, and cognition potential of the human brain, it is not surprising that network-level representations of brain function reveal intrinsically rich organizational structure. What remains puzzling is how the human brain maintains its vast repertoire of functional connectivity (FC) states despite being constrained by the underlying fixed anatomical substrate. Advances in modern neuroimaging technologies, such as diffusion-weighted magnetic resonance imaging (DW-MRI), have made it possible to map the brain's anatomical scaffold, while functional MRI (fMRI) provides complementary information on neural activity. In this thesis, we develop and apply methods for combining DW-MRI and fMRI data into an integrated framework to analyze the interplay between brain structure and function. We first explored the dynamics of brain function during wakefulness and across the different non-rapid eye movement (NREM) sleep stages. We applied the innovation-driven co-activation pattern (iCAP) analysis to uncover the spatial and temporal organization of overlapping large-scale brain networks. Our results reveal new spatial patterns covering regions that support the physiological organization of sleep and arousal. Contrary to the previously observed decreasing FC that accompanies increasing sleep depth, we instead observe a surge of network activity and cross-network interactions during NREM stage 2, followed by an abrupt decrease in NREM stage 3. In the next step of the thesis, we propose a new method that models all brain voxels as nodes of a high-resolution voxel-level brain graph. We provide two ways to construct the graph and we characterize their properties by performing a spectral analysis of the graph Laplacian operator. Our findings show that despite the huge dimensionality of the proposed brain graphs, the majority of the structural information is captured by the Laplacian's lowest frequency eigenmodes. The lower end of the Laplacian spectra also captures about 85% of the energy content of functional MRI, suggesting that functional patterns are overall smooth over the structure, thus providing, for the first time, a direct and quantitative measure of how much brain function is shaped by the anatomy. Going beyond a scalar measure of the SC-FC link, we introduce a new framework that interpolates gray matter signals onto the white matter using the structure embedded in the voxel-level brain grid to guide the process. This enables visualization of key white matter structures that link temporally coherent gray matter areas. We found whole-brain structure-function networks that extend currently known spatial patterns that are limited within the gray matter only. Finally, we assessed the collective mediation of white matter pathways by giving a quantitative measure of the overall anatomical range between temporally coherent gray matter areas. We utilized a canonical model of graph diffusion to extract the anatomical range of functional network interactions. We find that this measure meaningfully differentiates brain regions according to a behaviorally relevant macroscale gradient that divides the cortex between low-level primary sensory areas and high-level cognitive functions.

EPFL2020

Exploring dynamic functional connectivity by incorporating prior knowledge of brain structure

Anjali Bagunu Tarun

EPFL2020