Asymmetries of the balanced SSFP profile. Part II: white matter

Getting the phase consistent: The importance of phase description in balanced steady-state free precession MRI of multi-compartment systems

PURPOSE

Determine the correct mathematical phase description for balanced steady-state free precession (bSSFP) signals in multi-compartment systems.

THEORY AND METHODS

Based on published bSSFP signal models, different phase descriptions can be formulated: one predicting the presence and the other predicting the absence of destructive interference effects in multi-compartment systems. Numerical simulations of bSSFP signals of water and acetone were performed to evaluate the predictions of these different phase descriptions. For experimental validation, bSSFP profiles were measured at 3T using phase-cycled bSSFP acquisitions performed in a phantom containing mixtures of water and acetone, which replicates a system with two signal components. Localized single voxel MRS was performed at 7T to determine the relative chemical shift of the acetone-water mixtures.

RESULTS

Based on the choice of phase description, the simulated bSSFP profiles of water-acetone mixtures varied significantly, either displaying or lacking destructive interference effects, as predicted theoretically. In phantom experiments, destructive interference was consistently observed in the measured bSSFP profiles of water-acetone mixtures, supporting the theoretical description that predicts such interference effects. The connection between the choice of phase description and predicted observation enables unambiguous experimental identification of the correct phase description for multi-compartment bSSFP profiles, which is consistent with the Bloch equations.

CONCLUSION

The study emphasizes that consistent phase descriptions are crucial for accurately describing multi-compartment bSSFP signals, as incorrect phase descriptions result in erroneous predictions.

Myelin water imaging at 0.55 T using a multigradient-echo sequence

PURPOSE

To investigate the prospects of a multigradient-echo (mGRE) acquisition for in vivo myelin water imaging at 0.55 T.

METHODS

Scans were performed on the brain of four healthy volunteers at 0.55 and 3 T, using a 3D mGRE sequence. The myelin water fraction (MWF) was calculated for both field strengths using a nonnegative least squares (NNLS) algorithm, implemented in the qMRLab suite. The quality of these maps as well as single-voxel fits were compared visually for 0.55 and 3 T.

RESULTS

The obtained MWF values at 0.55 T are consistent with previously reported ones at higher field strengths. The MWF maps are a considerable improvement over the ones at 3 T. Example fits show that 0.55 T data is better described by an exponential model than 3 T data, making the assumed multi-exponential model of the NNLS algorithm more accurate.

CONCLUSION

This first assessment shows that mGRE myelin water imaging at 0.55 T is feasible and has the potential to yield better results than at higher fields.

SPARCQ: A new approach for fat fraction mapping using asymmetries in the phase-cycled balanced SSFP signal profile

PURPOSE

To develop SPARCQ (Signal Profile Asymmetries for Rapid Compartment Quantification), a novel approach to quantify fat fraction (FF) using asymmetries in the phase-cycled balanced SSFP (bSSFP) profile.

METHODS

SPARCQ uses phase-cycling to obtain bSSFP frequency profiles, which display asymmetries in the presence of fat and water at certain TRs. For each voxel, the measured signal profile is decomposed into a weighted sum of simulated profiles via multi-compartment dictionary matching. Each dictionary entry represents a single-compartment bSSFP profile with a specific off-resonance frequency and relaxation time ratio. Using the results of dictionary matching, the fractions of the different off-resonance components are extracted for each voxel, generating quantitative maps of water and FF and banding-artifact-free images for the entire image volume. SPARCQ was validated using simulations, experiments in a water-fat phantom and in knees of healthy volunteers. Experimental results were compared with reference proton density FFs obtained with 1 H-MRS (phantoms) and with multiecho gradient-echo MRI (phantoms and volunteers). SPARCQ repeatability was evaluated in six scan-rescan experiments.

RESULTS

Simulations showed that FF quantification is accurate and robust for SNRs greater than 20. Phantom experiments demonstrated good agreement between SPARCQ and gold standard FFs. In volunteers, banding-artifact-free quantitative maps and water-fat-separated images obtained with SPARCQ and ME-GRE demonstrated the expected contrast between fatty and non-fatty tissues. The coefficient of repeatability of SPARCQ FF was 0.0512.

CONCLUSION

SPARCQ demonstrates potential for fat quantification using asymmetries in bSSFP profiles and may be a promising alternative to conventional FF quantification techniques.

High-resolution neural network-driven mapping of multiple diffusion metrics leveraging asymmetries in the balanced steady-state free precession frequency profile

We propose to utilize the rich information content about microstructural tissue properties entangled in asymmetric balanced steady-state free precession (bSSFP) profiles to estimate multiple diffusion metrics simultaneously by neural network (NN) parameter quantification. A 12-point bSSFP phase-cycling scheme with high-resolution whole-brain coverage is employed at 3 and 9.4 T for NN input. Low-resolution target diffusion data are derived based on diffusion-weighted spin-echo echo-planar-imaging (SE-EPI) scans, that is, mean, axial, and radial diffusivity (MD, AD, and RD), fractional anisotropy (FA), as well as the spherical coordinates (azimuth Φ and inclination ϴ) of the principal diffusion eigenvector. A feedforward NN is trained with incorporated probabilistic uncertainty estimation. The NN predictions yielded highly reliable results in white matter (WM) and gray matter structures for MD. The quantification of FA, AD, and RD was overall in good agreement with the reference but the dependence of these parameters on WM anisotropy was somewhat biased (e.g. in corpus callosum). The inclination ϴ was well predicted for anisotropic WM structures, while the azimuth Φ was overall poorly predicted. The findings were highly consistent across both field strengths. Application of the optimized NN to high-resolution input data provided whole-brain maps with rich structural details. In conclusion, the proposed NN-driven approach showed potential to provide distortion-free high-resolution whole-brain maps of multiple diffusion metrics at high to ultrahigh field strengths in clinically relevant scan times.

Constrained Ellipse Fitting for Efficient Parameter Mapping With Phase-Cycled bSSFP MRI

Balanced steady-state free precession (bSSFP) imaging enables high scan efficiency in MRI, but differs from conventional sequences in terms of elevated sensitivity to main field inhomogeneity and nonstandard [Formula: see text]-weighted tissue contrast. To address these limitations, multiple bSSFP images of the same anatomy are commonly acquired with a set of different RF phase-cycling increments. Joint processing of phase-cycled acquisitions serves to mitigate sensitivity to field inhomogeneity. Recently phase-cycled bSSFP acquisitions were also leveraged to estimate relaxation parameters based on explicit signal models. While effective, these model-based methods often involve a large number of acquisitions (N ≈ 10-16), degrading scan efficiency. Here, we propose a new constrained ellipse fitting method (CELF) for parameter estimation with improved efficiency and accuracy in phase-cycled bSSFP MRI. CELF is based on the elliptical signal model framework for complex bSSFP signals; and it introduces geometrical constraints on ellipse properties to improve estimation efficiency, and dictionary-based identification to improve estimation accuracy. CELF generates maps of [Formula: see text], [Formula: see text], off-resonance and on-resonant bSSFP signal by employing a separate [Formula: see text] map to mitigate sensitivity to flip angle variations. Our results indicate that CELF can produce accurate off-resonance and banding-free bSSFP maps with as few as N = 4 acquisitions, while estimation accuracy for relaxation parameters is notably limited by biases from microstructural sensitivity of bSSFP imaging.

Pure balanced steady-state free precession imaging (pure bSSFP)

Purpose

To show that for tissues the conspicuous asymmetries in the frequency response function of bSSFP can be mitigated by using a short enough TR.

Theory and Methods

Configuration theory indicates that bSSFP becomes apparently “pure” (i.e., exhibiting a symmetric profile) in the limit of TR →0. To this end, the frequency profile of bSSFP was measured as a function of the TR using a manganese‐doped aqueous probe, as well as brain tissue that was shown to exhibit a pronounced asymmetry due to its microstructure. The frequency response function was sampled using N=72 (phantom) and N=36 (in vivo) equally distributed linear RF phase increments in the interval [0,2π). Imaging was performed with 2.0 mm isotropic resolution over a TR range of 1.5–8 ms at 3 and 1.5 T.

Results

As expected, pure substances showed a symmetric TR‐independent frequency profile, whereas brain tissue revealed a pronounced asymmetry. The observed asymmetry for the tissue, however, decreases with decreasing TR and gives strong evidence that the frequency response function of bSSFP becomes symmetric in the limit of TR →0, in agreement with theory. The limit of apparently pure bSSFP imaging can thus be achieved for a TR ∼ 1.5 ms at 1.5 T, whereas at 3 T, tissues still show some residual asymmetry.

Conclusion

In the limit of short enough TR, tissues become apparently pure for bSSFP. This limit can be reached for brain tissue at 1.5 T with TR ∼ 1–2 ms at clinically relevant resolutions.

From signal-based to comprehensive magnetic resonance imaging

We present and evaluate a new insight into magnetic resonance imaging (MRI). It is based on the algebraic description of the magnetization during the transient response—including intrinsic magnetic resonance parameters such as longitudinal and transverse relaxation times (T₁, T₂) and proton density (PD) and experimental conditions such as radiofrequency field (B₁) and constant/homogeneous magnetic field (B₀) from associated scanners. We exploit the correspondence among three different elements: the signal evolution as a result of a repetitive sequence of blocks of radiofrequency excitation pulses and encoding gradients, the continuous Bloch equations and the mathematical description of a sequence as a linear system. This approach simultaneously provides, in a single measurement, all quantitative parameters of interest as well as associated system imperfections. Finally, we demonstrate the in-vivo applicability of the new concept on a clinical MRI scanner.

Configuration-based electrical properties tomography

PURPOSE

To introduce phase-based conductivity mapping from a configuration space analysis.

METHODS

The frequency response function of balanced SSFP (bSSFP) is used to perform a configuration space analysis. It is shown that the transceive phase for conductivity mapping can be directly obtained by a simple fast Fourier transform of a series of phase-cycled bSSFP scans. For validation, transceive phase and off-resonance mapping with fast Fourier transform is compared with phase estimation using a recently proposed method, termed PLANET. Experiments were performed in phantoms and for in vivo brain imaging at 3 T using a quadrature head coil.

RESULTS

For fast Fourier transform, aliasing can lead to systematic phase errors. This bias, however, decreases rapidly with increasing sampling points. Interestingly, Monte Carlo simulations revealed a lower uncertainty for the transceive phase and the off-resonance using fast Fourier transform as compared with PLANET. Both methods, however, essentially retrieve the same phase information from a set of phase-cycled bSSFP scans. As a result, configuration-based conductivity mapping was successfully performed using eight phase-cycled bSSFP scans in the phantoms and for brain tissues. Overall, the retrieved values were in good agreement with expectations. Conductivity estimation and mapping of the field inhomogeneities can therefore be performed in conjunction with the estimation of other quantitative parameters, such as relaxation, using configuration theory.

CONCLUSIONS

Phase-based conductivity mapping can be estimated directly from a simple Fourier analysis, such as in conjunction with relaxometry, using a series of phase-cycled bSSFP scans.

Myelin water fraction estimation using small-tip fast recovery MRI

PURPOSE

To demonstrate the feasibility of an optimized set of small-tip fast recovery (STFR) MRI scans for rapidly estimating myelin water fraction (MWF) in the brain.

METHODS

We optimized a set of STFR scans to minimize the Cramér-Rao Lower Bound of MWF estimates. We evaluated the RMSE of MWF estimates from the optimized scans in simulation. We compared STFR-based MWF estimates (both modeling exchange and not modeling exchange) to multi-echo spin echo (MESE)-based estimates. We used the optimized scans to acquire in vivo data from which a MWF map was estimated. We computed the STFR-based MWF estimates using PERK, a recently developed kernel regression technique, and the MESE-based MWF estimates using both regularized non-negative least squares (NNLS) and PERK.

RESULTS

In simulation, the optimized STFR scans led to estimates of MWF with low RMSE across a range of tissue parameters and across white matter and gray matter. The STFR-based MWF estimates that modeled exchange compared well to MESE-based MWF estimates in simulation. When the optimized scans were tested in vivo, the MWF map that was estimated using a 3-compartment model with exchange was closer to the MESE-based MWF map.

CONCLUSIONS

The optimized STFR scans appear to be well suited for estimating MWF in simulation and in vivo when we model exchange in training. In this case, the STFR-based MWF estimates are close to the MESE-based estimates.

Multi-parametric artificial neural network fitting of phase-cycled balanced steady-state free precession data

PURPOSE

Standard relaxation time quantification using phase-cycled balanced steady-state free precession (bSSFP), eg, motion-insensitive rapid configuration relaxometry (MIRACLE), is subject to a considerable underestimation of tissue T₁ and T₂ due to asymmetric intra-voxel frequency distributions. In this work, an artificial neural network (ANN) fitting approach is proposed to simultaneously extract accurate reference relaxation times (T₁ , T₂ ) and robust field map estimates ( B 1 + , ΔB₀ ) from the bSSFP profile.

METHODS

Whole-brain bSSFP data acquired at 3T were used for the training of a feedforward ANN with N = 12, 6, and 4 phase-cycles. The magnitude and phase of the Fourier transformed complex bSSFP frequency response served as input and the multi-parametric reference set [T₁ , T₂ , B 1 + , ∆B₀ ] as target. The ANN predicted relaxation times were validated against the target and MIRACLE.

RESULTS

The ANN prediction of T₁ and T₂ for trained and untrained data agreed well with the reference, even for only four acquired phase-cycles. In contrast, relaxometry based on 4-point MIRACLE was prone to severe off-resonance-related artifacts. ANN predicted B 1 + and ∆B₀ maps showed the expected spatial inhomogeneity patterns in high agreement with the reference measurements for 12-point, 6-point, and 4-point bSSFP phase-cycling schemes.

CONCLUSION

ANNs show promise to provide accurate brain tissue T₁ and T₂ values as well as reliable field map estimates. Moreover, the bSSFP acquisition can be accelerated by reducing the number of phase-cycles while still delivering robust T₁ , T₂ , B 1 + , and ∆B₀ estimates.

Structure or Exchange? On the Feasibility of Chemical Exchange Detection with Balanced Steady-State Free Precession in Tissue - An In Vitro Study

Balanced steady-state free precession imaging has recently been suggested for chemical exchange detection (bSSFPX). The objective of this work is to investigate the contributions of microstructural, chemical shift and chemical exchange effects to the asymmetry of the bSSFP profile at field strengths of 3 T and 9.4 T. To this end, in vitro bSSFPX experiments are performed for a range of repetition times and flip angles in glucose water solutions with different MnCl₂ concentrations and tissue homogenates obtained from the brainstem of pig brains. The experimental results are compared to multi-pool Bloch-McConnell simulations. Additionally, the influence of white matter tract geometry is analyzed ex vivo in pig brain hemispheres measured at two different angles with respect to B₀ . The detectable bSSFP profile asymmetry in glucose solutions with tissue-like relaxation times and white matter homogenates was consistent with Bloch-McConnell simulations but relatively small. In intact white matter tracts, the asymmetry was dominated by structural effects with a strong dependency on tract orientation relative to B₀ . In tracts perpendicular to B₀ , the asymmetry was ≈ 3-4 times higher than in the homogenates, thus barely affected by chemical exchange effects. In conclusion, chemical exchange-related bSSFP profile asymmetries are detectable in tissue homogenates, however, the observed asymmetry level is generally low and prone to confounding structural effects rendering in vivo chemical exchange detection with bSSFP challenging in the brain.

Magnetization transfer and frequency distribution effects in the SSFP ellipse

Purpose

To demonstrate that quantitative magnetization transfer (qMT) parameters can be extracted from steady‐state free‐precession (SSFP) data with no external T₁ map or banding artifacts.

Methods

SSFP images with multiple MT weightings were acquired and qMT parameters fitted with a two‐stage elliptical signal model.

Results

Monte Carlo simulations and data from a 3T scanner indicated that most qMT parameters could be recovered with reasonable accuracy. Systematic deviations from theory were observed in white matter, consistent with previous literature on frequency distribution effects.

Conclusions

qMT parameters can be extracted from SSFP data alone, in a manner robust to banding artifacts, despite several confounds.

Transceive phase mapping using the PLANET method and its application for conductivity mapping in the brain

Purpose

To demonstrate feasibility of transceive phase mapping with the PLANET method and its application for conductivity reconstruction in the brain.

Methods

Accuracy and precision of transceive phase (ϕ^±) estimation with PLANET, an ellipse fitting approach to phase‐cycled balanced steady state free precession (bSSFP) data, were assessed with simulations and measurements and compared to standard bSSFP. Measurements were conducted on a homogeneous phantom and in the brain of healthy volunteers at 3 tesla. Conductivity maps were reconstructed with Helmholtz‐based electrical properties tomography. In measurements, PLANET was also compared to a reference technique for transceive phase mapping, i.e., spin echo.

Results

Accuracy and precision of ϕ^± estimated with PLANET depended on the chosen flip angle and TR. PLANET‐based ϕ^± was less sensitive to perturbations induced by off‐resonance effects and partial volume (e.g., white matter + myelin) than bSSFP‐based ϕ^±. For flip angle = 25° and TR = 4.6 ms, PLANET showed an accuracy comparable to that of reference spin echo but a higher precision than bSSFP and spin echo (factor of 2 and 3, respectively). The acquisition time for PLANET was ~5 min; 2 min faster than spin echo and 8 times slower than bSSFP. However, PLANET simultaneously reconstructed T₁, T₂, B₀ maps besides mapping ϕ^±. In the phantom, PLANET‐based conductivity matched the true value and had the smallest spread of the three methods. In vivo, PLANET‐based conductivity was similar to spin echo‐based conductivity.

Conclusion

Provided that appropriate sequence parameters are used, PLANET delivers accurate and precise ϕ^± maps, which can be used to reconstruct brain tissue conductivity while simultaneously recovering T₁, T₂, and B₀ maps.

Multi-slice passband bSSFP for human and rodent fMRI at ultra-high field

Balanced steady-state free precession (bSSFP) can be used as an alternative to gradient-echo (GE) EPI for BOLD functional MRI when image distortions and signal drop-outs are severe such as at ultra-high field. However, 3D-bSSFP acquisitions have distinct drawbacks on either human or animal MR systems. On clinical scanners, 3D imaging is suboptimal for localized fMRI applications. It can also display distortions when acceleration methods such as spiral read-outs are used, and, compared to multi-slice acquisitions, suffers from increased sensitivity to motion or physiological noise which further results in blurring. On pre-clinical systems, 3D acquisitions have low temporal resolution due to limited acceleration options, while single slice often results in insufficient coverage. The aim of the present study was to implement a multi-slice bSSFP acquisition with Cartesian read-out to obtain non-distorted BOLD fMRI activation maps in the human and rat brain at ultra-high field. We show that, when using a new pseudo-steady-state, the bSSFP signal characteristics are preserved. In the human brain at 7 T, we demonstrate that both task- and resting-state fMRI can be performed with multi-slice bSSFP, with a temporal SNR that matches that of 3D-bSSFP, resulting in - at least - equal performance. In the rat brain at 14 T, we show that the multi-slice bSSFP protocol has similar sensitivity to gradient-echo EPI for task fMRI, while benefitting from much reduced distortions and drop-outs. The advantages of passband bSSFP at 14 T in comparison with GE-EPI are expected to be even more marked for mouse brain.

Investigation of the influence of B0 drift on the performance of the PLANET method and an algorithm for drift correction

Purpose

The PLANET method was designed to simultaneously reconstruct maps of T₁ and T₂, the off‐resonance, the RF phase, and the banding free signal magnitude. The method requires a stationary B₀ field over the course of a phase‐cycled balanced SSFP acquisition. In this work we investigated the influence of B₀ drift on the performance of the PLANET method for single‐component and two‐component signal models, and we propose a strategy for drift correction.

Methods

The complex phase‐cycled balanced SSFP signal was modeled with and without frequency drift. The behavior of the signal influenced by drift was mathematically interpreted as a sum of drift‐dependent displacement of the data points along an ellipse and drift‐dependent rotation around the origin. The influence of drift on parameter estimates was investigated experimentally on a phantom and on the brain of healthy volunteers and was verified by numerical simulations. A drift correction algorithm was proposed and tested on a phantom and in vivo.

Results

Drift can be assumed to be linear over the typical duration of a PLANET acquisition. In a phantom (a single‐component signal model), drift induced errors of 4% and 8% in the estimated T₁ and T₂ values. In the brain, where multiple components are present, drift only had a minor effect. For both single‐component and two‐component signal models, drift‐induced errors were successfully corrected by applying the proposed drift correction algorithm.

Conclusion

We have demonstrated theoretically and experimentally the sensitivity of the PLANET method to B₀ drift and have proposed a drift correction method.

Magnetic resonance fingerprinting with quadratic RF phase for measurement of T2 * simultaneously with δf , T1 , and T2

PURPOSE

This study explores the possibility of using a gradient moment balanced sequence with a quadratically varied RF excitation phase in the magnetic resonance fingerprinting (MRF) framework to quantify T₂ ^* in addition to δ f , T₁ , and T₂ tissue properties.

METHODS

The proposed quadratic RF phase-based MRF method (qRF-MRF) combined a varied RF excitation phase with the existing balanced SSFP (bSSFP)-based MRF method to generate signals that were uniquely sensitive to δ f , T₁ , T₂ , as well as the distribution width of intravoxel frequency dispersion, Γ . A dictionary, generated through Bloch simulation, containing possible signal evolutions within the physiological range of δ f , T₁ , T₂ , and Γ , was used to perform parameter estimation. The estimated T₂ and Γ were subsequently used to estimate T₂ ^* . The proposed method was evaluated in phantom experiments and healthy volunteers (N = 5).

RESULTS

The T₁ and T₂ values from the phantom by qRF-MRF demonstrated good agreement with values obtained by traditional gold standard methods (r² = 0.995 and 0.997, respectively; concordance correlation coefficient = 0.978 and 0.995, respectively). The T₂ ^* values from the phantom demonstrated good agreement with values obtained through the multi-echo gradient-echo method (r² = 0.972, concordance correlation coefficient = 0.983). In vivo qRF-MRF-measured T₁ , T₂ , and T₂ ^* values were compared with measurements by existing methods and literature values.

CONCLUSION

The proposed qRF-MRF method demonstrated the potential for simultaneous quantification of δ f , T₁ , T₂ , and T₂ ^* tissue properties.

On the accuracy and precision of PLANET for multiparametric MRI using phase-cycled bSSFP imaging

Purpose

In this work we demonstrate how sequence parameter settings influence the accuracy and precision in T₁, T₂, and off‐resonance maps obtained with the PLANET method for a single‐component signal model. In addition, the performance of the method for the particular case of a two‐component relaxation model for white matter tissue was assessed.

Methods

Numerical simulations were performed to investigate the influence of sequence parameter settings on the accuracy and precision in the estimated parameters for a single‐component model, as well as for a two‐component white matter model. Phantom and in vivo experiments were performed for validation. In addition, the effects of Gibbs ringing were investigated.

Results

By making a proper choice for sequence parameter settings, accurate and precise parameter estimation can be achieved for a single‐component signal model over a wide range of relaxation times at realistic SNR levels. Due to the presence of a second myelin‐related signal component in white matter, an underestimation of approximately 30% in T₁ and T₂ was observed, predicted by simulations and confirmed by measurements. Gibbs ringing artifacts correction improved the precision and accuracy of the parameter estimates.

Conclusion

For a single‐component signal model there is a broad “sweet spot” of sequence parameter combinations for which a high accuracy and precision in the parameter estimates is achieved over a wide range of relaxation times. For a multicomponent signal model, the single‐component PLANET reconstruction results in systematic errors in the parameter estimates as expected.

Extended phase graph formalism for systems with magnetization transfer and exchange

Purpose

An extended phase graph framework (EPG‐X) for modeling systems with exchange or magnetization transfer (MT) is proposed.

Theory

EPG‐X models coupled two‐compartment systems by describing each compartment with separate phase graphs that exchange during evolution periods. There are two variants: EPG‐X(BM) for systems governed by the Bloch‐McConnell equations, and EPG‐X(MT) for the pulsed MT formalism. For the MT case, the “bound” protons have no transverse components, so their phase graph consists of only longitudinal states.

Methods

The EPG‐X model was validated against steady‐state solutions and isochromat‐based simulation of gradient‐echo sequences. Three additional test cases were investigated: (i) MT effects in multislice turbo spin‐echo; (ii) variable flip angle gradient‐echo imaging of the type used for MR fingerprinting; and (iii) water exchange in multi‐echo spin‐echo T₂ relaxometry.

Results

EPG‐X was validated successfully against isochromat based transient simulations and known steady‐state solutions. EPG‐X(MT) simulations matched in‐vivo measurements of signal attenuation in white matter in multislice turbo spin‐echo images. Magnetic resonance fingerprinting–style experiments with a bovine serum albumin (MT) phantom showed that the data were not consistent with a single‐pool model, but EPG‐X(MT) could be used to fit the data well. The EPG‐X(BM) simulations of multi‐echo spin‐echo T₂ relaxometry suggest that exchange could lead to an underestimation of the myelin‐water fraction.

Conclusions

The EPG‐X framework can be used for modeling both steady‐state and transient signal response of systems exhibiting exchange or MT. This may be particularly beneficial for relaxometry approaches that rely on characterizing transient rather than steady‐state sequences. Magn Reson Med 80:767–779, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

PLANET: An ellipse fitting approach for simultaneous T1 and T2 mapping using phase-cycled balanced steady-state free precession

Purpose

To demonstrate the feasibility of a novel, ellipse fitting approach, named PLANET, for simultaneous estimation of relaxation times T₁ and T₂ from a single 3D phase‐cycled balanced steady‐state free precession (bSSFP) sequence.

Methods

A method is presented in which the elliptical signal model is used to describe the phase‐cycled bSSFP steady‐state signal. The fitting of the model to the acquired data is reformulated into a linear convex problem, which is solved directly by a linear least squares method, specific to ellipses. Subsequently, the relaxation times T₁ and T₂, the banding free magnitude, and the off‐resonance are calculated from the fitting results.

Results

Maps of T₁ and T₂, as well as an off‐resonance and a banding free magnitude can be simultaneously, quickly, and robustly estimated from a single 3D phase‐cycled bSSFP sequence. The feasibility of the method was demonstrated in a phantom and in the brain of healthy volunteers on a clinical MR scanner. The results were in good agreement for the phantom, but a systematic underestimation of T₁ was observed in the brain.

Conclusion

The presented method allows for accurate mapping of relaxation times and off‐resonance, and for the reconstruction of banding free magnitude images at realistic signal‐to‐noise ratios. Magn Reson Med 79:711–722, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

Direct visualization of short transverse relaxation time component (ViSTa)

White matter of the brain has been demonstrated to have multiple relaxation components. Among them, the short transverse relaxation time component (T2<40 ms; T2⁎<25 ms at 3 T) has been suggested to originate from myelin water whereas long transverse relaxation time components have been associated with axonal and/or interstitial water. In myelin water imaging, T2 or T2⁎ signal decay is measured to estimate myelin water fraction based on T2 or T2⁎ differences among the water components. This method has been demonstrated to be sensitive to demyelination in the brain but suffers from low SNR and image artifacts originating from ill-conditioned multi-exponential fitting. In this study, a novel approach that selectively acquires short transverse relaxation time signal is proposed. The method utilizes a double inversion RF pair to suppress a range of long T1 signal. This suppression leaves short T2⁎ signal, which has been suggested to have short T1, as the primary source of the image. The experimental results confirm that after suppression of long T1 signals, the image is dominated by short T2⁎ in the range of myelin water, allowing us to directly visualize the short transverse relaxation time component in the brain. Compared to conventional myelin water imaging, this new method of direct visualization of short relaxation time component (ViSTa) provides high quality images. When applied to multiple sclerosis patients, chronic lesions show significantly reduced signal intensity in ViSTa images suggesting sensitivity to demyelination.

Micro-compartment specific T2* relaxation in the brain

MRI at high field can be sensitized to the magnetic properties of tissues, which introduces a signal dependence on the orientation of white matter (WM) fiber bundles relative to the magnetic field. In addition, study of the NMR relaxation properties of this signal has indicated contributions from compartmentalized water environments inside and outside the myelin sheath that may be separable. Here we further investigated the effects of water compartmentalization on the MRI signal with the goal of extracting compartment-specific information. By comparing MRI measurements of human and marmoset brain at 7T with magnetic field modeling, we show that: (1) water between the myelin lipid bilayers, in the axonal, and in the interstitial space each experience characteristic magnetic field effects that depend on fiber orientation (2) these field effects result in characteristic relaxation properties and frequency shifts for these compartments; and (3) compartmental contributions may be separated by multi-component fitting of the MRI signal relaxation (i.e. decay) curve. We further show the potential application of these findings to the direct mapping of myelin content and assessment of WM fiber integrity with high field MRI.

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

The microscopic structure of neuronal tissue is crucial to brain function, with axon diameter, axonal density and myelination directly influencing signal conduction in the white matter. There is increasing evidence that these microstructural properties alter signal in magnetic resonance imaging (MRI) driven by magnetic susceptibility of different compartments (e.g., myelin sheaths and iron-laden cells). To explain these observations, we have developed a multi-compartmental geometric model of whitematter microstructure. Using a single set of literature parameters, this forward model predicts experimentally observed orientation dependence and temporal evolution of the MRI signal. Where previous models have aimed to explain only the orientation dependence of signal phase, the proposed approach encapsulates the full repertoire of signal behavior. The frequency distribution underlying signal behavior is predicted to be a rich source of microstructural information with relevance to neuronal pathology.

Challenges of High-resolution Diffusion Imaging of the Human Medial Temporal Lobe in Alzheimer Disease

The human medial temporal lobe performs an essential role in memory formation and retrieval. Diseases involving the hippocampus such as Alzheimer disease present a unique opportunity for advanced imaging techniques to detect abnormalities at an early stage. In particular, it is possible that diffusion imaging will measure abnormal microarchitecture beyond the realm of macroscopic imaging. However, this task is formidable because of the detailed anatomy of the medial temporal lobe, the difficulties in obtaining high-quality diffusion images of adequate resolution, and the challenges in diffusion data processing. Moreover, it is unclear if any differences will be significant for an individual patient or simply groups of patients. Successful endeavors will need to address each of these challenges in an integrated fashion. The rewards of such analysis may be detection of microscopic disease in vivo, which could represent a landmark accomplishment for the field of neuroradiology.

Nonexponential T₂ decay in white matter

Visualizing myelin in human brain may help the study of diseases such as multiple sclerosis. Previous studies based on T(1) and T(2) relaxation contrast have suggested the presence of a distinct water pool that may report directly on local myelin content. Recent work indicates that T(2) contrast may offer particular advantages over T(1) and T(2) contrast, especially at high field. However, the complex mechanism underlying T(2) relaxation may render interpretation difficult. To address this issue, T(2) relaxation behavior in human brain was studied at 3 and 7 T. Multiple gradient echoes covering most of the decay curve were analyzed for deviations from mono-exponential behavior. The data confirm the previous finding of a distinct rapidly relaxing signal component (T(2) ∼ 6 ms), tentatively attributed to myelin water. However, in extension to previous findings, this rapidly relaxing component displayed a substantial resonance frequency shift, reaching 36 Hz in the corpus callosum at 7 T. The component's fractional amplitude and frequency shift appeared to depend on both field strength and fiber orientation, consistent with a mechanism originating from magnetic susceptibility effects. The findings suggest that T(2) contrast at high field may be uniquely sensitive to tissue myelin content and that proper interpretation will require modeling of susceptibility-induced resonance frequency shifts.