Arnaud Guidon

Whole Brain Susceptibility Mapping Using Compressed Sensing

The derivation of susceptibility from image phase is hampered by the ill‐conditioned filter inversion in certain k‐space regions. In this article, compressed sensing is used to compensate for the k‐space regions where direct filter inversion is unstable. A significantly lower level of streaking artifacts is produced in the resulting susceptibility maps for both simulated and in vivo data sets compared to outcomes obtained using the direct threshold method. It is also demonstrated that the compressed sensing based method outperforms regularization based methods. The key difference between the regularized inversions and compressed sensing compensated inversions is that, in the former case, the entire k‐space spectrum estimation is affected by the ill‐conditioned filter inversion in certain k‐space regions, whereas in the compressed sensing based method only the ill‐conditioned k‐space regions are estimated. In the susceptibility map calculated from the phase measurement obtained using a 3T scanner, not only are the iron‐rich regions well depicted, but good contrast between white and gray matter interfaces that feature a low level of susceptibility variations are also obtained. The correlation between the iron content and the susceptibility levels in iron‐rich deep nucleus regions is studied, and strong linear relationships are observed which agree with previous findings. Magn Reson Med, 2011.

A robust multi-shot scan strategy for high-resolution diffusion weighted MRI enabled by multiplexed sensitivity-encoding (MUSE)

Diffusion weighted magnetic resonance imaging (DWI) data have been mostly acquired with single-shot echo-planar imaging (EPI) to minimize motion induced artifacts. The spatial resolution, however, is inherently limited in single-shot EPI, even when the parallel imaging (usually at an acceleration factor of 2) is incorporated. Multi-shot acquisition strategies could potentially achieve higher spatial resolution and fidelity, but they are generally susceptible to motion-induced phase errors among excitations that are exacerbated by diffusion sensitizing gradients, rendering the reconstructed images unusable. It has been shown that shot-to-shot phase variations may be corrected using navigator echoes, but at the cost of imaging throughput. To address these challenges, a novel and robust multi-shot DWI technique, termed multiplexed sensitivity-encoding (MUSE), is developed here to reliably and inherently correct nonlinear shot-to-shot phase variations without the use of navigator echoes. The performance of the MUSE technique is confirmed experimentally in healthy adult volunteers on 3Tesla MRI systems. This newly developed technique should prove highly valuable for mapping brain structures and connectivities at high spatial resolution for neuroscience studies.

High-resolution multishot spiral diffusion tensor imaging with inherent correction of motion-induced phase errors.

To develop and compare three novel reconstruction methods designed to inherently correct for motion‐induced phase errors in multishot spiral diffusion tensor imaging without requiring a variable‐density spiral trajectory or a navigator echo.

Myelin water weighted diffusion tensor imaging

In this study we describe our development and implementation of a magnetization transfer (MT) prepared stimulated-echo diffusion tensor imaging (DTI) technique that can be made sensitive to the microanatomy of myelin tissue. The short echo time (TE) enabled by the stimulated-echo acquisition preserves significant signal from the short T(2) component (myelin water), and the MT preparation further provides differentiating sensitization to this signal. It was found that this combined strategy could provide sufficient sensitivity in our first attempt to image myelin microstructure. Compared to the diffusion tensor derived from the conventional DTI technique, the myelin water weighted (MWW) tensor has the same principal diffusion direction but exhibits a significant increase in fractional anisotropy (FA), which is mainly due to a decrease in radial diffusivity. These findings are consistent with the microstructural organization of the myelin sheaths that wrap around the axons in the white matter and therefore hinder radial diffusion. Given that many white matter diseases (e.g. multiple sclerosis) begin with a degradation of myelin microanatomy but not a loss of myelin content (e.g. loosening of the myelin sheaths), our newly implemented MWW DTI has the potential to lead to improved assessment of myelin pathology and early detection of demyelination.

Acceleration of high angular and spatial resolution diffusion imaging using compressed sensing with multichannel spiral data

To accelerate the acquisition of simultaneously high spatial and angular resolution diffusion imaging.

Cortical Depth Dependence of the Diffusion Anisotropy in the Human Cortical Gray Matter In Vivo

Diffusion tensor imaging (DTI) is typically used to study white matter fiber pathways, but may also be valuable to assess the microstructure of cortical gray matter. Although cortical diffusion anisotropy has previously been observed in vivo, its cortical depth dependence has mostly been examined in high-resolution ex vivo studies. This study thus aims to investigate the cortical depth dependence of the diffusion anisotropy in the human cortex in vivo on a clinical 3 T scanner. Specifically, a novel multishot constant-density spiral DTI technique with inherent correction of motion-induced phase errors was used to achieve a high spatial resolution (0.625×0.625×3 mm) and high spatial fidelity with no scan time penalty. The results show: (i) a diffusion anisotropy in the cortical gray matter, with a primarily radial diffusion orientation, as observed in previous ex vivo and in vivo studies, and (ii) a cortical depth dependence of the fractional anisotropy, with consistently higher values in the middle cortical lamina than in the deep and superficial cortical laminae, as observed in previous ex vivo studies. These results, which are consistent across subjects, demonstrate the feasibility of this technique for investigating the cortical depth dependence of the diffusion anisotropy in the human cortex in vivo.

No association of ZNF804A rs1344706 with white matter integrity in schizophrenia: a tract-based spatial statistics study.

Altered brain connectivity has been widely considered as a genetic risk mechanism for schizophrenia. Of the many susceptibility genes identified so far, ZNF804A (rs1344706) is the first common genetic variant associated with schizophrenia on a genome-wide level. Previous fMRI studies have found that carriers of rs1344706 exhibit altered functional connectivity. However, the relationship between ZNF804A and white matter structural connectivity in patients of schizophrenia remains unknown. In this study, 100 patients with schizophrenia and 69 healthy controls were genotyped at the single nucleotide polymorphism rs1344706. Diffusion tensor imaging (DTI) was conducted and analyzed with tract-based spatial statistics. Systematic statistical analysis was conducted on multiple diffusion indices, including fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity. Unpaired two-sample t-test revealed significant differences in fractional anisotropy and diffusivity between schizophrenia and control groups. A two-way ANOVA analysis was conducted to assess the main effects of and the interaction between schizophrenia and ZNF804A. Although significant main effects of the diagnosis of schizophrenia were found on radial diffusivity, no association between the ZNF804A (rs1344706) and white matter connectivity was found in the entire group of subjects or in a selected subgroup of age-matched subjects (n=72).

Improved delineation of short cortical association fibers and gray/white matter boundary using whole-brain three-dimensional diffusion tensor imaging at submillimeter spatial resolution.

Recent emergence of human connectome imaging has led to a high demand on angular and spatial resolutions for diffusion magnetic resonance imaging (MRI). While there have been significant growths in high angular resolution diffusion imaging, the improvement in spatial resolution is still limited due to a number of technical challenges, such as the low signal-to-noise ratio and high motion artifacts. As a result, the benefit of a high spatial resolution in the whole-brain connectome imaging has not been fully evaluated in vivo. In this brief report, the impact of spatial resolution was assessed in a newly acquired whole-brain three-dimensional diffusion tensor imaging data set with an isotropic spatial resolution of 0.85 mm. It was found that the delineation of short cortical association fibers is drastically improved as well as the definition of fiber pathway endings into the gray/white matter boundary-both of which will help construct a more accurate structural map of the human brain connectome.

Acceleration of high angular and spatial resolution diffusion imaging using compressed sensing

Achieving simultaneously high angular and spatial resolution in diffusion imaging is challenging because of the long acquisition times involved. We propose a novel compressed sensing method to acquire high angular and spatial resolution diffusion imaging data, while keeping the scan time reasonable. We show that joint under sampling of 6-D k-q space is more efficient than undersampling only one of the dimensions. We use a sparse Gaussian mixture model and an iterative reconstruction scheme to recover the peaks of the orientation distribution functions (ODF) with high accuracy. We show that at least 6-fold acceleration of acquisition is possible, thereby enabling high angular and spatial resolution diffusion imaging in a reasonable scan time.

Dynamic and inherent B0 correction for DTI using stimulated echo spiral imaging.

To present a novel technique for high‐resolution stimulated echo diffusion tensor imaging with self‐navigated interleaved spirals readout trajectories that can inherently and dynamically correct for image artifacts due to spatial and temporal variations in the static magnetic field (B0) resulting from eddy currents, tissue susceptibilities, subject/physiological motion, and hardware instabilities.