Correction of FLASH-based MT saturation in human brain for residual bias of B1-inhomogeneity at 3T

Background: Magnetization transfer (MT) saturation reflects the additionalsaturation of the MRI signal imposed by an MT pulse and is largely driven bythe saturation of the bound pool. This reduction of the bound polarization bythe MT pulse is less efficient than predicted by the differential B1-square lawof absorption. Thus, B1 inhomogeneities lead to a residual bias in the MTsaturation maps. We derive a heuristic correction to reduce this bias for awidely used multi-parameter mapping protocol at 3T. Methods: The amplitude ofthe MT pulse was varied via the nominal flip angle to mimic variations in B1.The MT saturation's dependence on the actual flip angle features a linearcorrection term, which was determined separately for gray and white matter.Results: The deviation of MT saturation from differential B1-square law is welldescribed by a linear decrease with the actual flip angle of the MT pulse. Thisdecrease showed no significant differences between gray and white matter. Thus,the post hoc correction does not need to take different tissue types intoaccount. Bias-corrected MT saturation maps appeared more symmetric andhighlighted highly myelinated tracts. Discussion: Our correction involves acalibration that is specific for the MT pulse. While it can also be used torescale nominal flip angles, different MT pulses and/or protocols will requireindividual calibration. Conclusion: The suggested B1 correction of the MT mapscan be applied post hoc using an independently acquired flip angle map.<br

Correction of FLASH-based MT saturation in human brain for residual bias of B1-inhomogeneity at 3T

Background: Magnetization transfer (MT) saturation reflects the additional saturation of the MRI signal imposed by an MT pulse and is largely driven by the saturation of the bound pool. This reduction of the bound polarization by the MT pulse is less efficient than predicted by the differential B1-square law of absorption. Thus, B1 inhomogeneities lead to a residual bias in the MT saturation maps. We derive a heuristic correction to reduce this bias for a widely used multi-parameter mapping protocol at 3T. Methods: The amplitude of the MT pulse was varied via the nominal flip angle to mimic variations in B1. The MT saturation's dependence on the actual flip angle features a linear correction term, which was determined separately for gray and white matter. Results: The deviation of MT saturation from differential B1-square law is well described by a linear decrease with the actual flip angle of the MT pulse. This decrease showed no significant differences between gray and white matter. Thus, the post hoc correction does not need to take different tissue types into account. Bias-corrected MT saturation maps appeared more symmetric and highlighted highly myelinated tracts. Discussion:Our correction involves a calibration that is specific for the MT pulse. While it can also be used to rescale nominal flip angles, different MT pulses and/or protocols will require individual calibration. Conclusion: The suggested B1 correction of the MT maps can be applied post hoc using an independently acquired flip angle map

Brain microstructure by multi-modal MRI: Is the whole greater than the sum of its parts?

The MRI signal is dependent upon a number of sub-voxel properties of tissue, which makes it potentially able to detect changes occurring at a scale much smaller than the image resolution. This "microstructural imaging" has become one of the main branches of quantitative MRI. Despite the exciting promise of unique insight beyond the resolution of the acquired images, its widespread application is limited by the relatively modest ability of each microstructural imaging technique to distinguish between differing microscopic substrates. This is mainly due to the fact that MRI provides a very indirect measure of the tissue properties in which we are interested. A strategy to overcome this limitation lies in the combination of more than one technique, to exploit the relative contributions of differing physiological and pathological substrates to selected MRI contrasts. This forms the basis of multi-modal MRI, a broad concept that refers to many different ways of effectively combining information from more than one MRI contrast. This paper will review a range of methods that have been proposed to maximise the output of this combination, primarily falling into one of two approaches. The first one relies on data-driven methods, exploiting multivariate analysis tools able to capture overlapping and complementary information. The second approach, which we call "model-driven", aims at combining parameters extracted by existing biophysical or signal models to obtain new parameters, which are believed to be more accurate or more specific than the original ones. This paper will attempt to provide an overview of the advantages and limitations of these two philosophies

Probing the myelin water compartment with a saturation‐recovery, multi‐echo gradient‐recalled echo sequence

PurposeTo investigate the effect of varying levels of urn:x-wiley:07403194:media:mrm28695:mrm28695-math-0001‐weighting on the evolution of the complex signal from white matter in a multi‐echo gradient‐recalled echo (mGRE) saturation‐recovery sequence.Theory and MethodsAnalysis of the complex signal evolution in an mGRE sequence allows the contributions from short‐ and long‐urn:x-wiley:07403194:media:mrm28695:mrm28695-math-0002 components to be separated, thus providing a measure of the relative strength of signals from the myelin water, and the external and intra‐axonal compartments. Here we evaluated the effect of different levels of urn:x-wiley:07403194:media:mrm28695:mrm28695-math-0003‐weighting on these signals, expecting that the previously reported, short urn:x-wiley:07403194:media:mrm28695:mrm28695-math-0004 of the myelin water would lead to a relative enhancement of the myelin water signal in the presence of signal saturation. Complex, saturation‐recovery mGRE data from the splenium of the corpus callosum from 5 healthy volunteers were preprocessed using a frequency difference mapping (FDM) approach and analyzed using the 3‐pool model of complex signal evolution in white matter.ResultsAn increase in the apparent urn:x-wiley:07403194:media:mrm28695:mrm28695-math-0005 as a function of echo time was demonstrated, but this increase was an order of magnitude smaller than that expected from previously reported myelin water urn:x-wiley:07403194:media:mrm28695:mrm28695-math-0006‐values. This suggests the presence of magnetization transfer and exchange effects which counteract the urn:x-wiley:07403194:media:mrm28695:mrm28695-math-0007‐weighting.ConclusionVariation of the urn:x-wiley:07403194:media:mrm28695:mrm28695-math-0008 amplitude in a saturation‐recovery mGRE sequence can be used to modulate the relative strength of signals from the different compartments in white matter, but the modulation is less than predicted from previously reported urn:x-wiley:07403194:media:mrm28695:mrm28695-math-0009‐values

Fiber-orientation independent component of R2* obtained from single-orientation MRI measurements in simulations and a post-mortem human optic chiasm

The effective transverse relaxation rate (R2*) is sensitive to the microstructure of the human brain like the g-ratio which characterises the relative myelination of axons. However, the fibre-orientation dependence of R2* degrades its reproducibility and any microstructural derivative measure. To estimate its orientation-independent part (R2,iso*) from single multi-echo gradient-recalled-echo (meGRE) measurements at arbitrary orientations, a second-order polynomial in time model (hereafter M2) can be used. Its linear time-dependent parameter, β1, can be biophysically related to R2,iso* when neglecting the myelin water (MW) signal in the hollow cylinder fibre model (HCFM). Here, we examined the performance of M2 using experimental and simulated data with variable g-ratio and fibre dispersion. We found that the fitted β1 can estimate R2,iso* using meGRE with long maximum-echo time (TEmax ≈ 54 ms), but not accurately captures its microscopic dependence on the g-ratio (error 84%). We proposed a new heuristic expression for β1 that reduced the error to 12% for ex vivo compartmental R2 values. Using the new expression, we could estimate an MW fraction of 0.14 for fibres with negligible dispersion in a fixed human optic chiasm for the ex vivo compartmental R2 values but not for the in vivo values. M2 and the HCFM-based simulations failed to explain the measured R2*-orientation-dependence around the magic angle for a typical in vivo meGRE protocol (with TEmax ≈ 18 ms). In conclusion, further validation and the development of movement-robust in vivo meGRE protocols with TEmax ≈ 54 ms are required before M2 can be used to estimate R2,iso* in subjects

The impact of head orientation with respect to B0 on diffusion tensor MRI measures

Diffusion tensor MRI (DT-MRI) remains the most commonly used approach to characterise white matter (WM) anisotropy. However, DT estimates may be affected by tissue orientation w.r.t. B→0 due to local gradients and intrinsic T2 orientation dependence induced by the microstructure. This work aimed to investigate whether and how diffusion tensor MRI-derived measures depend on the orientation of the head with respect to the static magnetic field, B→0 ⁠. By simulating WM as two compartments, we demonstrated that compartmental T2 anisotropy can induce the dependence of diffusion tensor measures on the angle between WM fibres and the magnetic field. In in vivo experiments, reduced radial diffusivity and increased axial diffusivity were observed in white matter fibres perpendicular to B→0 compared to those parallel to B→0 ⁠. Fractional anisotropy varied by up to 20% as a function of the angle between WM fibres and the orientation of the main magnetic field. To conclude, fibre orientation w.r.t. B→0 is responsible for up to 7% variance in diffusion tensor measures across the whole brain white matter from all subjects and head orientations. Fibre orientation w.r.t. B→0 may introduce additional variance in clinical research studies using diffusion tensor imaging, particularly when it is difficult to control for (e.g. fetal or neonatal imaging, or when the trajectories of fibres change due to e.g. space occupying lesions)

Fiber-orientation independent component of R2* obtained from single-orientation MRI measurements in simulations and a post-mortem human optic chiasm

The effective transverse relaxation rate (R2*) is sensitive to the microstructure of the human brain like the g-ratio which characterises the relative myelination of axons. However, the fibre-orientation dependence of R2* degrades its reproducibility and any microstructural derivative measure. To estimate its orientation-independent part (R2,iso*) from single multi-echo gradient-recalled-echo (meGRE) measurements at arbitrary orientations, a second-order polynomial in time model (hereafter M2) can be used. Its linear time-dependent parameter, β1, can be biophysically related to R2,iso* when neglecting the myelin water (MW) signal in the hollow cylinder fibre model (HCFM). Here, we examined the performance of M2 using experimental and simulated data with variable g-ratio and fibre dispersion. We found that the fitted β1 can estimate R2,iso* using meGRE with long maximum-echo time (TEmax ≈ 54 ms), but not accurately captures its microscopic dependence on the g-ratio (error 84%). We proposed a new heuristic expression for β1 that reduced the error to 12% for ex vivo compartmental R2 values. Using the new expression, we could estimate an MW fraction of 0.14 for fibres with negligible dispersion in a fixed human optic chiasm for the ex vivo compartmental R2 values but not for the in vivo values. M2 and the HCFM-based simulations failed to explain the measured R2*-orientation-dependence around the magic angle for a typical in vivo meGRE protocol (with TEmax ≈ 18 ms). In conclusion, further validation and the development of movement-robust in vivo meGRE protocols with TEmax ≈ 54 ms are required before M2 can be used to estimate R2,iso* in subjects

Orientation dependence of magnetization transfer parameters in human white matter

Quantification of magnetization-transfer (MT) experiments is typically based on a model comprising a liquid pool "a" of free water and a semisolid pool "b" of motionally restricted macromolecules or membrane compounds. By a comprehensive fitting approach, high quality MT parameter maps of the human brain are obtained. In particular, a distinct correlation between the diffusion-tensor orientation with respect to the B0-magnetic field and the apparent transverse relaxation time, T2b, of the semisolid pool (i.e., the width of its absorption line) is observed. This orientation dependence is quantitatively explained by a refined dipolar lineshape for pool b that explicitly considers the specific geometrical arrangement of lipid bilayers wrapped around a cylindrical axon. The model inherently reduces the myelin membrane to its lipid constituents, which is motivated by previous studies on efficient interaction sites (e.g., cholesterol or galactocerebrosides) in the myelin membrane and on the origin of ultrashort T2 signals in cerebral white matter. The agreement between MT orientation effects and corresponding forward simulations using empirical diffusion imaging results as input as well as results from fits employing the novel lineshape support previous suggestions that the fiber orientation distribution in a voxel can be modeled as a scaled Bingham distribution