Detecting microstructural properties of white matter based on compartmentalization of magnetic susceptibility

Physiological noise compensation in gradient-echo myelin water imaging

In MRI, physiological noise which originates from cardiac and respiratory functions can induce substantial errors in detecting small signals in the brain. In this work, we explored the effects of the physiological noise and their compensation methods in gradient-echo myelin water imaging (GRE-MWI). To reduce the cardiac function induced inflow noise, flow saturation RF pulses were applied to the inferior portion of the head, saturating inflow blood signals. For the respiratory function induced B0 fluctuation compensation, a navigator echo was acquired, and respiration induced phase errors were corrected during reconstruction. After the compensations, the resulting myelin water images show substantially improved image quality and reproducibility. These improvements confirm the importance and usefulness of the physiological noise compensations in GRE-MWI.

Cerebral response to subject's own name showed high prognostic value in traumatic vegetative state

BACKGROUND

Previous studies have shown the prognostic value of stimulation elicited blood-oxygen-level-dependent (BOLD) signal in traumatic patients in vegetative state/unresponsive wakefulness syndrome (VS/UWS). However, to the best of our knowledge, no studies have focused on the relevance of etiology and level of consciousness in patients with disorders of consciousness (DOC) when explaining the relationship between BOLD signal and both outcome and signal variability. We herein propose a study in a large sample of traumatic and non-traumatic DOC patients in order to ascertain the relevance of etiology and level of consciousness in the variability and prognostic value of a stimulation-elicited BOLD signal.

METHODS

66 patients were included, and the response of each subject to his/her own name said by a familiar voice (SON-FV) was recorded using fMRI; 13 patients were scanned twice in the same day, respecting the exact same conditions in both cases. A behavioral follow-up program was carried out at 3, 6, and 12 months after scanning.

RESULTS

Of the 39 VS/UWS patients, 12 (75%) out of 16 patients with higher level activation patterns recovered to minimally conscious state (MCS) or emergence from MCS (EMCS) and 17 (74%) out of 23 patients with lower level activation patterns or no activation had a negative outcome. Taking etiology into account for VS/UWS patients, a higher positive predictive value was assigned to traumatic patients, i.e., up to 92% (12/13) patients with higher level activation pattern achieved good recovery whereas 11 out of 13 (85%) non-traumatic patients with lower level activation or without activation had a negative clinical outcome. The reported data from visual analysis of fMRI activation patterns were corroborated using ROC curve analysis, which supported the correlation between auditory cortex activation volume and VS/UWS patients' recovery. The average brain activity overlap in primary and secondary auditory cortices in patients scanned twice was 52%.

CONCLUSIONS

The activation type and volume in auditory cortex elicited by SON-FV significantly correlated with VS/UWS patients' prognosis, particularly in patients with traumatic etiology, however, this could not be established in MCS patients. Repeated use of this simple fMRI task might help obtain more reliable prognostic information.

Improved estimation of myelin water fraction using complex model fitting

In gradient echo (GRE) imaging, three compartment water modeling (myelin water, axonal water and extracellular water) in white matter has been demonstrated to show different frequency shifts that depend on the relative orientation of fibers and the B0 field. This finding suggests that in GRE-based myelin water imaging, a signal model may need to incorporate frequency offset terms and become a complex-valued model. In the current study, three different signal models and fitting approaches (a magnitude model fitted to magnitude data, a complex model fitted to magnitude data, and a complex model fitted to complex data) were investigated to address the reliability of each model in the estimation of the myelin water signal. For the complex model fitted to complex data, a new fitting approach that does not require background phase removal was proposed. When the three models were compared, the results from the new complex model fitting showed the most stable parameter estimation.

3D high spectral and spatial resolution imaging of ex vivo mouse brain

PURPOSE

Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T2*-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflect local anatomy. The resulting information compliments previous studies based on T2* and resonance frequency.

METHODS

The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm(3) and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16-24 h).

RESULTS

High contrast T2*-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at -7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not present at +7.0 Hz and may be specific to white matter anatomy. Moreover, a frequency shift of 6.76 ± 0.55 Hz was measured between the molecular and granular layers of the cerebellum. This shift is demonstrated in corresponding spectra; water peaks from voxels in the molecular and granular layers are consistently 2 bins apart (7.0 Hz, as dictated by the spectral resolution) from one another.

CONCLUSIONS

High spectral and spatial resolution MR imaging has the potential to accurately measure the changes in the water resonance in small voxels. This information can guide optimization and interpretation of more commonly used, more rapid imaging methods that depend on image contrast produced by local susceptibility gradients. In addition, with improved sampling methods, high spectral and spatial resolution data could be acquired in reasonable run times, and used for in vivo scans to increase sensitivity to variations in local susceptibility.

Quantitative susceptibility mapping (QSM): Decoding MRI data for a tissue magnetic biomarker

In MRI, the main magnetic field polarizes the electron cloud of a molecule, generating a chemical shift for observer protons within the molecule and a magnetic susceptibility inhomogeneity field for observer protons outside the molecule. The number of water protons surrounding a molecule for detecting its magnetic susceptibility is vastly greater than the number of protons within the molecule for detecting its chemical shift. However, the study of tissue magnetic susceptibility has been hindered by poor molecular specificities of hitherto used methods based on MRI signal phase and T2* contrast, which depend convolutedly on surrounding susceptibility sources. Deconvolution of the MRI signal phase can determine tissue susceptibility but is challenged by the lack of MRI signal in the background and by the zeroes in the dipole kernel. Recently, physically meaningful regularizations, including the Bayesian approach, have been developed to enable accurate quantitative susceptibility mapping (QSM) for studying iron distribution, metabolic oxygen consumption, blood degradation, calcification, demyelination, and other pathophysiological susceptibility changes, as well as contrast agent biodistribution in MRI. This paper attempts to summarize the basic physical concepts and essential algorithmic steps in QSM, to describe clinical and technical issues under active development, and to provide references, codes, and testing data for readers interested in QSM.

Microstructural origins of gadolinium-enhanced susceptibility contrast and anisotropy

PURPOSE

MR histology based on magnetic susceptibility can be used to visualize diamagnetic myelin (and its deterioration) in the central nervous system and is facilitated by the application of high magnetic field strengths and paramagnetic contrast agents. Characterizing the effect of these tools will aid in assessing white matter myelin content and microstructure.

METHODS

Image data from six gadolinium-perfused mouse brain specimens were acquired at 2.0, 7.0, and 9.4 Tesla. Magnetic susceptibility contrast was analyzed for its dependence on field strength, gadolinium concentration, and white matter fiber orientation. A model for this contrast is presented based on the three-pool model for white matter.

RESULTS

The specimen data illustrate that white-gray matter susceptibility contrast is field strength independent. White-gray matter contrast improves significantly as a function of gadolinium contrast agent in the tissue, i.e., white matter appears increasingly more diamagnetic relative to gray matter. The simulated data from the model suggest that susceptibility anisotropy of white matter fiber bundles increases nonlinearly as a function of gadolinium concentration due to contrast agent compartmentalization into the extracellular white matter water pool.

CONCLUSION

Using contrast agents in MR histology facilitates white-gray matter susceptibility contrast modulation and the probing of white matter microstructure and orientation.

Diffusion-assisted selective dynamical recoupling: a new approach to measure background gradients in magnetic resonance

Dynamical decoupling, a generalization of the original NMR spin-echo sequence, is becoming increasingly relevant as a tool for reducing decoherence in quantum systems. Such sequences apply non-equidistant refocusing pulses for optimizing the coupling between systems, and environmental fluctuations characterized by a given noise spectrum. One such sequence, dubbed Selective Dynamical Recoupling (SDR) [P. E. S. Smith, G. Bensky, G. A. Álvarez, G. Kurizki, and L. Frydman, Proc. Natl. Acad. Sci. 109, 5958 (2012)], allows one to coherently reintroduce diffusion decoherence effects driven by fluctuations arising from restricted molecular diffusion [G. A. Álvarez, N. Shemesh, and L. Frydman, Phys. Rev. Lett. 111, 080404 (2013)]. The fully-refocused, constant-time, and constant-number-of-pulses nature of SDR also allows one to filter out "intrinsic" T1 and T2 weightings, as well as pulse errors acting as additional sources of decoherence. This article explores such features when the fluctuations are now driven by unrestricted molecular diffusion. In particular, we show that diffusion-driven SDR can be exploited to investigate the decoherence arising from the frequency fluctuations imposed by internal gradients. As a result, SDR presents a unique way of probing and characterizing these internal magnetic fields, given an a priori known free diffusion coefficient. This has important implications in studies of structured systems, including porous media and live tissues, where the internal gradients may serve as fingerprints for the system's composition or structure. The principles of this method, along with full analytical solutions for the unrestricted diffusion-driven modulation of the SDR signal, are presented. The potential of this approach is demonstrated with the generation of a novel source of MRI contrast, based on the background gradients active in an ex vivo mouse brain. Additional features and limitations of this new method are discussed.

Susceptibility-weighted imaging and quantitative susceptibility mapping in the brain

Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) technique that enhances image contrast by using the susceptibility differences between tissues. It is created by combining both magnitude and phase in the gradient echo data. SWI is sensitive to both paramagnetic and diamagnetic substances which generate different phase shift in MRI data. SWI images can be displayed as a minimum intensity projection that provides high resolution delineation of the cerebral venous architecture, a feature that is not available in other MRI techniques. As such, SWI has been widely applied to diagnose various venous abnormalities. SWI is especially sensitive to deoxygenated blood and intracranial mineral deposition and, for that reason, has been applied to image various pathologies including intracranial hemorrhage, traumatic brain injury, stroke, neoplasm, and multiple sclerosis. SWI, however, does not provide quantitative measures of magnetic susceptibility. This limitation is currently being addressed with the development of quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI). While QSM treats susceptibility as isotropic, STI treats susceptibility as generally anisotropic characterized by a tensor quantity. This article reviews the basic principles of SWI, its clinical and research applications, the mechanisms governing brain susceptibility properties, and its practical implementation, with a focus on brain imaging.

Probing signal phase in direct visualization of short transverse relaxation time component (ViSTa)

PURPOSE

To demonstrate the phase evolutions of direct visualization of short transverse relaxation time component (ViSTa) matches with those of myelin water.

METHOD

Myelin water imaging (MWI) measures short transverse signals and has been suggested as a biomarker for myelin. Recently, a new approach, ViSTa, has been proposed to acquire short T2* signals by suppressing long T1 signals. This method does not require any ill-conditioned data processing and therefore provides high-quality images. In this study, the phase of the ViSTa signal was compared with the phase of myelin water simulated by the magnetic susceptibility model of hollow cylinder.

RESULTS

The phase evolutions of the ViSTa signal were similar to the simulated myelin water phase evolutions. When fiber orientation was perpendicular relative to the main magnetic field, both the ViSTa and the simulated myelin water phase showed large positive frequency shifts, whereas the gradient echo phase showed a slightly negative frequency shift. Additionally, the myelin water phase map generated using diffusion tensor imaging (DTI) information revealed a good match with the ViSTa phase image.

CONCLUSION

The results of this study support the origin of ViSTa signal as myelin water. ViSTa phase may potentially provide sensitivity to demyelination.

Mean magnetic susceptibility regularized susceptibility tensor imaging (MMSR-STI) for estimating orientations of white matter fibers in human brain

PURPOSE

An increasing number of studies show that magnetic susceptibility in white matter fibers is anisotropic and may be described by a tensor. However, the limited head rotation possible for in vivo human studies leads to an ill-conditioned inverse problem in susceptibility tensor imaging (STI). Here we suggest the combined use of limiting the susceptibility anisotropy to white matter and imposing morphology constraints on the mean magnetic susceptibility (MMS) for regularizing the STI inverse problem.

METHODS

The proposed MMS regularized STI (MMSR-STI) method was tested using computer simulations and in vivo human data collected at 3T. The fiber orientation estimated from both the STI and MMSR-STI methods was compared to that from diffusion tensor imaging (DTI).

RESULTS

Computer simulations show that the MMSR-STI method provides a more accurate estimation of the susceptibility tensor than the conventional STI approach. Similarly, in vivo data show that use of the MMSR-STI method leads to a smaller difference between the fiber orientation estimated from STI and DTI for most selected white matter fibers.

CONCLUSION

The proposed regularization strategy for STI can improve estimation of the susceptibility tensor in white matter.

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 contributions. Magn Reson Med 73:1258–1269, 2015. © 2014 Wiley Periodicals, Inc.

Separating acoustic deviance from novelty during the first year of life: a review of event-related potential evidence

Orienting to salient events in the environment is a first step in the development of attention in young infants. Electrophysiological studies have indicated that in newborns and young infants, sounds with widely distributed spectral energy, such as noise and various environmental sounds, as well as sounds widely deviating from their context elicit an event-related potential (ERP) similar to the adult P3a response. We discuss how the maturation of event-related potentials parallels the process of the development of passive auditory attention during the first year of life. Behavioral studies have indicated that the neonatal orientation to high-energy stimuli gradually changes to attending to genuine novelty and other significant events by approximately 9 months of age. In accordance with these changes, in newborns, the ERP response to large acoustic deviance is dramatically larger than that to small and moderate deviations. This ERP difference, however, rapidly decreases within first months of life and the differentiation of the ERP response to genuine novelty from that to spectrally rich but repeatedly presented sounds commences during the same period. The relative decrease of the response amplitudes elicited by high-energy stimuli may reflect development of an inhibitory brain network suppressing the processing of uninformative stimuli. Based on data obtained from healthy full-term and pre-term infants as well as from infants at risk for various developmental problems, we suggest that the electrophysiological indices of the processing of acoustic and contextual deviance may be indicative of the functioning of auditory attention, a crucial prerequisite of learning and language development.

Gradient echo based fiber orientation mapping using R2* and frequency difference measurements

Fiber orientation mapping through diffusion tensor imaging (DTI) is a powerful MRI-based technique for visualising white matter (WM) microstructure in the brain. Although DTI provides a robust way to measure fiber orientation, it has some limitations linked to the use of EPI read-outs and long diffusion encoding periods, including relatively low spatial resolution. Development of alternative MRI-based methods for fiber orientation mapping is therefore valuable, in part to allow validation of DTI results. In this study, we used the orientation dependence of R2* (1/T2*) and frequency difference measurements to generate three dimensional maps of the fiber orientation in WM from multi-echo gradient-echo (GE) images acquired from post mortem brain tissue samples oriented at multiple angles to B0. Through analytical derivation and numerical simulation, the relationships connecting variations in R2* and frequency difference values to the angle between the underlying WM fiber orientation and the direction of B0 were characterised. High resolution 3D fiber orientation maps (FOM) were then formed by comparing R2* and frequency difference data, acquired with the sample at multiple orientations to the field, to generalised models based on the derived expressions for the angular dependence of each parameter. By comparing the resulting GE-based FOM with DTI-based FOM from the same tissue sample, we demonstrate that fiber orientation mapping based on gradient echo MRI has the potential to become an important tool for investigating microstructure in brain tissue.