5,363 research outputs found
Towards in vivo g-ratio mapping using MRI: unifying myelin and diffusion imaging
The g-ratio, quantifying the comparative thickness of the myelin sheath
encasing an axon, is a geometrical invariant that has high functional relevance
because of its importance in determining neuronal conduction velocity. Advances
in MRI data acquisition and signal modelling have put in vivo mapping of the
g-ratio, across the entire white matter, within our reach. This capacity would
greatly increase our knowledge of the nervous system: how it functions, and how
it is impacted by disease. This is the second review on the topic of g-ratio
mapping using MRI. As such, it summarizes the most recent developments in the
field, while also providing methodological background pertinent to aggregate
g-ratio weighted mapping, and discussing pitfalls associated with these
approaches. Using simulations based on recently published data, this review
demonstrates the relevance of the calibration step for three myelin-markers
(macromolecular tissue volume, myelin water fraction, and bound pool fraction).
It highlights the need to estimate both the slope and offset of the
relationship between these MRI-based markers and the true myelin volume
fraction if we are really to achieve the goal of precise, high sensitivity
g-ratio mapping in vivo. Other challenges discussed in this review further
evidence the need for gold standard measurements of human brain tissue from ex
vivo histology. We conclude that the quest to find the most appropriate MRI
biomarkers to enable in vivo g-ratio mapping is ongoing, with the potential of
many novel techniques yet to be investigated.Comment: Will be published as a review article in Journal of Neuroscience
Methods as parf of the Special Issue with Hu Cheng and Vince Calhoun as Guest
Editor
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
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
Measurement of T1 of the ultrashort T2* components in white matter of the brain at 3T.
Recent research demonstrates that white matter of the brain contains not only long T2 components, but a minority of ultrashort T2* components. Adiabatic inversion recovery prepared dual echo ultrashort echo time (IR-dUTE) sequences can be used to selectively image the ultrashort T2* components in white matter of the brain using a clinical whole body scanner. The T2*s of the ultrashort T2* components can be quantified using mono-exponential decay fitting of the IR-dUTE signal at a series of different TEs. However, accurate T1 measurement of the ultrashort T2* components is technically challenging. Efficient suppression of the signal from the majority of long T2 components is essential for robust T1 measurement. In this paper we describe a novel approach to this problem based on the use of IR-dUTE data acquisitions with different TR and TI combinations to selectively detect the signal recovery of the ultrashort T2* components. Exponential recovery curve fitting provides efficient T1 estimation, with minimized contamination from the majority of long T2 components. A rubber phantom and a piece of bovine cortical bone were used for validation of this approach. Six healthy volunteers were studied. An averaged T2* of 0.32 ± 0.09 ms, and a short mean T1 of 226 ± 46 ms were demonstrated for the healthy volunteers at 3T
Axon diameters and myelin content modulate microscopic fractional anisotropy at short diffusion times in fixed rat spinal cord
Mapping tissue microstructure accurately and noninvasively is one of the
frontiers of biomedical imaging. Diffusion Magnetic Resonance Imaging (MRI) is
at the forefront of such efforts, as it is capable of reporting on microscopic
structures orders of magnitude smaller than the voxel size by probing
restricted diffusion. Double Diffusion Encoding (DDE) and Double Oscillating
Diffusion Encoding (DODE) in particular, are highly promising for their ability
to report on microscopic fractional anisotropy ({\mu}FA), a measure of the pore
anisotropy in its own eigenframe, irrespective of orientation distribution.
However, the underlying correlates of {\mu}FA have insofar not been studied.
Here, we extract {\mu}FA from DDE and DODE measurements at ultrahigh magnetic
field of 16.4T in the aim to probe fixed rat spinal cord microstructure. We
further endeavor to correlate {\mu}FA with Myelin Water Fraction (MWF) derived
from multiexponential T2 relaxometry, as well as with literature-based
spatially varying axonal diameters. In addition, a simple new method is
presented for extracting unbiased {\mu}FA from three measurements at different
b-values. Our findings reveal strong anticorrelations between {\mu}FA (derived
from DODE) and axon diameter in the distinct spinal cord tracts; a moderate
correlation was also observed between {\mu}FA derived from DODE and MWF. These
findings suggest that axonal membranes strongly modulate {\mu}FA, which - owing
to its robustness towards orientation dispersion effects - reflects axon
diameter much better than its typical FA counterpart. The {\mu}FA exhibited
modulations when measured via oscillating or blocked gradients, suggesting
selective probing of different parallel path lengths and providing insight into
how those modulate {\mu}FA metrics. Our findings thus shed light into the
underlying microstructural correlates of {\mu}FA and are (...
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