Extended phase graph formalism for systems with magnetization transfer and exchange

Improved gradient echo magnitude- and phase-based mapping of T 2 $$ {\mathrm{T}}_2 $$ using multiple RF spoiling increments at 3T and 7T

PURPOSE

The transverse relaxation time T  2 $$ {}_2 $$ holds significant relevance in clinical applications and research studies. Conventional T  2 $$ {}_2 $$ mapping approaches rely on spin-echo sequences, which require lengthy acquisition times and involve high radiofrequency (RF) power deposition. An alternative gradient echo (GRE) phase-based T  2 $$ {}_2 $$ mapping method, utilizing steady-state acquisitions at one small RF spoil phase increment, was recently demonstrated. Here, a modified magnitude- and phase-based T  2 $$ {}_2 $$ mapping approach is proposed, which improvesT 2 $$ {\mathrm{T}}_2 $$ estimations by simultaneous fitting ofT 1 $$ {\mathrm{T}}_1 $$ and signal amplitude (A ∝ P D $$ A\propto PD $$ ) at three or more RF spoiling phase increments, instead of assuming a fixedT 1 $$ {\mathrm{T}}_1 $$ value.

METHODS

The feasibility of the magnitude-phase-based method was assessed by simulations, in phantom and in vivo experiments using skipped-CAIPI three-dimensional-echo-planar imaging (3D-EPI) for rapid GRE imaging.T 2 $$ {\mathrm{T}}_2 $$ ,T 1 $$ {\mathrm{T}}_1 $$ and PD estimations obtained by our method were compared toT 2 $$ {\mathrm{T}}_2 $$ of the phase-based method andT 1 $$ {\mathrm{T}}_1 $$ and PD of spoiled GRE-based multi-parameter mapping using a multi-echo version of the same sequence.

RESULTS

The agreement of the proposedT 2 $$ {\mathrm{T}}_2 $$ with ground truth and referenceT 2 $$ {\mathrm{T}}_2 $$ values was higher than that of phase-basedT 2 $$ {\mathrm{T}}_2 $$ in simulations and in phantom data. While phase-basedT 2 $$ {\mathrm{T}}_2 $$ overestimation increases with actualT 2 $$ {\mathrm{T}}_2 $$ andT 1 $$ {\mathrm{T}}_1 $$ , the proposed method is accurate over a large range of physiologically meaningfulT 2 $$ {\mathrm{T}}_2 $$ andT 1 $$ {\mathrm{T}}_1 $$ values. At the same time, precision is improved. In vivo results were in line with these observations.

CONCLUSION

Accurate magnitude-phase-based T  2 $$ {}_2 $$ mapping is feasible in less than 5 min scan time for 1 mm nominal isotropic whole-head coverage at 3T and 7T.

Fast magnetization transfer saturation imaging of the brain using MP2RAGE T1 mapping

PURPOSE

Magnetization transfer saturation (MTsat) mapping is commonly used to examine the macromolecular content of brain tissue. This study compared variable flip angle (VFA) T1 mapping against compressed-sensing MP2RAGE (csMP2RAGE) T1 mapping for accelerating MTsat imaging.

METHODS

VFA, MP2RAGE, and csMP2RAGE were compared against inversion-recovery T1 in an aqueous phantom at 3 T. The same 1-mm VFA, MP2RAGE, and csMP2RAGE protocols were acquired in 4 healthy subjects to compare T1 and MTsat. Bloch-McConnell simulations were used to investigate differences between the phantom and in vivo T1 results. Ten healthy controls were imaged twice with the csMP2RAGE MTsat protocol to quantify repeatability.

RESULTS

The MP2RAGE and csMP2RAGE protocols were 13.7% and 32.4% faster than the VFA protocol, respectively. At these scan times, all approaches provided strong repeatability and accurate T1 times (< 5% difference) in the phantom, but T1 accuracy was more impacted by T2 for VFA than for MP2RAGE. In vivo, VFA estimated longer T1 times than MP2RAGE and csMP2RAGE. Simulations suggest that the differences in the T1 measured using VFA, MP2RAGE, and inversion recovery could be explained by the magnetization-transfer effects. In the test-retest experiment, we found that the csMP2RAGE has a minimum detectable change of 2.3% for T1 mapping and 7.8% for MTsat imaging.

CONCLUSIONS

We demonstrated that MP2RAGE can be used in place of VFA T1 mapping in an MTsat protocol. Furthermore, a shorter scan time and high repeatability can be achieved using the csMP2RAGE sequence.

Phase distribution graphs for fast, differentiable, and spatially encoded Bloch simulations of arbitrary MRI sequences

PURPOSE

An analytical approach to Bloch simulations for MRI sequences is introduced that enables time efficient calculations of signals free of Monte-Carlo noise, while providing full flexibility and differentiability in RF flip angles, RF phases, magnetic field gradients and time, as well as insights into image formation.

THEORY AND METHODS

We present an implementation of the extended phase graph (EPG) concept implemented in PyTorch, including an efficient state selection algorithm. This simulation is compared with an isochromat-based Bloch simulation with random isochromat distribution as well as with in vivo measurements using the Pulseq standard. Additionally, different sequences are tested and analyzed using this novel simulation approach.

RESULTS

Our simulation outperforms isochromat-based simulations in terms of computation time as well as signal quality, without exhibiting any kind of Monte-Carlo noise. The novel approach allows extracting useful information about the magnetization evolution not available otherwise. Our approach extends the common state-tensor-based EPG simulation approach for the contribution of dephased states including spatial encoding andT 2 ' $$ {T}_2^{\prime } $$ effects, and arbitrary timing. This allows calculation of echo shapes in addition to echo amplitudes only. Our implementation provides full differentiability in all input parameters allowing gradient descent optimization. Simulation of non-instantaneous pulses via hard-pulse approximation is left for future work, as the performance and accuracy characteristics are not yet analyzed.

CONCLUSIONS

Phase distribution graphs provide fast, differentiable, and spatially encoded Bloch simulations for most MRI sequences. It allows efficient simulation and optimization of arbitrary MRI sequences, which was previously only possible via high isochromat counts.

In vivo T2 measurements of the fetal brain using single-shot fast spin echo sequences

PURPOSE

We propose a quantitative framework for motion-corrected T2 fetal brain measurements in vivo and validate the single-shot fast spin echo (SS-FSE) sequence to perform these measurements.

METHODS

Stacks of two-dimensional SS-FSE slices are acquired with different echo times (TE) and motion-corrected with slice-to-volume reconstruction (SVR). The quantitative T2 maps are obtained by a fit to a dictionary of simulated signals. The sequence is selected using simulated experiments on a numerical phantom and validated on a physical phantom scanned on a 1.5T system. In vivo quantitative T2 maps are obtained for five fetuses with gestational ages (GA) 21-35 weeks on the same 1.5T system.

RESULTS

The simulated experiments suggested that a TE of 400 ms combined with the clinically utilized TEs of 80 and 180 ms were most suitable for T2 measurements in the fetal brain. The validation on the physical phantom confirmed that the SS-FSE T2 measurements match the gold standard multi-echo spin echo measurements. We measured average T2s of around 200 and 280 ms in the fetal brain grey and white matter, respectively. This was slightly higher than fetal T2* and the neonatal T2 obtained from previous studies.

CONCLUSION

The motion-corrected SS-FSE acquisitions with varying TEs offer a promising practical framework for quantitative T2 measurements of the moving fetus.

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.

High SNR full brain relaxometry at 7T by accelerated MR-STAT

PURPOSE

To demonstrate the feasibility and robustness of the Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) framework for fast, high SNR relaxometry at 7T.

METHODS

To deploy MR-STAT on 7T-systems, we designed optimized flip-angles using the BLAKJac-framework that incorporates the SAR-constraints. Transmit RF-inhomogeneities were mitigated by including a measuredB 1 + $$ {B}_1^{+} $$ -map in the reconstruction. Experiments were performed on a gel-phantom and on five volunteers to explore the robustness of the sequence and its sensitivity toB 1 + $$ {B}_1^{+} $$ inhomogeneities. The SNR-gain at 7T was explored by comparing phantom and in vivo results to MR-STAT at 3T in terms of SNR-efficiency.

RESULTS

The higher SNR at 7T enabled two-fold acceleration with respect to current 2D MR-STAT protocols at lower field strengths. The resulting scan had whole-brain coverage, with 1 x 1 x 3 mm3 resolution (1.5 mm slice-gap) and was acquired within 3 min including theB 1 + $$ {B}_1^{+} $$ -mapping. AfterB 1 + $$ {B}_1^{+} $$ -correction, the estimated T1 and T2 in a phantom showed a mean relative error of, respectively, 1.7% and 4.4%. In vivo, the estimated T1 and T2 in gray and white matter corresponded to the range of values reported in literature with a variation over the subjects of 1.0%-2.1% (WM-GM) for T1 and 4.3%-5.3% (WM-GM) for T2. We measured a higher SNR-efficiency at 7T (R = 2) than at 3T for both T1 and T2 with, respectively, a 4.1 and 2.3 times increase in SNR-efficiency.

CONCLUSION

We presented an accelerated version of MR-STAT tailored to high field (7T) MRI using a low-SAR flip-angle train and showed high quality parameter maps with an increased SNR-efficiency compared to MR-STAT at 3T.

Magnetic resonance fingerprinting-based myelin water fraction mapping for the assessment of white matter maturation and integrity in typical development and leukodystrophies

A quantitative biomarker for myelination, such as myelin water fraction (MWF), would boost the understanding of normative and pathological neurodevelopment, improving patients' diagnosis and follow-up. We quantified the fraction of a rapidly relaxing pool identified as MW using multicomponent three-dimensional (3D) magnetic resonance fingerprinting (MRF) to evaluate white matter (WM) maturation in typically developing (TD) children and alterations in leukodystrophies (LDs). We acquired DTI and 3D MRF-based R1, R2 and MWF data of 15 TD children and 17 LD patients (9 months-12.5 years old) at 1.5 T. We computed normative maturation curves in corpus callosum and corona radiata and performed WM tract profile analysis, comparing MWF with R1, R2 and fractional anisotropy (FA). Normative maturation curves demonstrated a steep increase for all tissue parameters in the first 3 years of age, followed by slower growth for MWF while R1, R2R2 and FA reached a plateau. Unlike FA, MWF values were similar for regions of interest (ROIs) with different degrees of axonal packing, suggesting independence from fiber bundle macro-organization and higher myelin specificity. Tract profile analysis indicated a specific spatial pattern of myelination in the major fiber bundles, consistent across subjects. LD were better distinguished from TD by MWF rather than FA, showing reduced MWF with respect to age-matched controls in both ROI-based and tract analysis. In conclusion, MRF-based MWF provides myelin-specific WM maturation curves and is sensitive to alteration due to LDs, suggesting its potential as a biomarker for WM disorders. As MRF allows fast simultaneous acquisition of relaxometry and MWF, it can represent a valuable diagnostic tool to study and follow up developmental WM disorders in children.

The effect of and correction for through-slice dephasing on 2D gradient-echo double angle B 1 + mapping

PURPOSE

To show thatB 0 $$ {\mathrm{B}}_0 $$ variations through slice and slice profile effects are two major confounders affecting 2D dual angleB 1 + $$ {\mathrm{B}}_1^{+} $$ maps using gradient-echo signals and thus need to be corrected to obtain accurateB 1 + $$ {\mathrm{B}}_1^{+} $$ maps.

METHODS

The 2D gradient-echo transverse complex signal was Bloch-simulated and integrated across the slice dimension including nonlinear variations inB 0 $$ {\mathrm{B}}_0 $$ inhomogeneities through slice. A nonlinear least squares fit was used to find theB 1 + $$ {\mathrm{B}}_1^{+} $$ factor corresponding to the best match between the two gradient-echo signals experimental ratio and the Bloch-simulated ratio. The correction was validated in phantom and in vivo at 3T.

RESULTS

For our RF excitation pulse, the error in theB 1 + $$ {\mathrm{B}}_1^{+} $$ factor scales by approximately 3.8% for every 10 Hz/cm variation inB 0 $$ {\mathrm{B}}_0 $$ along the slice direction. Higher accuracy phantomB 1 + $$ {\mathrm{B}}_1^{+} $$ maps were obtained after applying the proposed correction; the root mean squareB 1 + $$ {\mathrm{B}}_1^{+} $$ error relative to the gold standardB 1 + $$ {\mathrm{B}}_1^{+} $$ decreased from 6.4% to 2.6%. In vivo whole-liverT 1 $$ {\mathrm{T}}_1 $$ maps using the correctedB 1 + $$ {\mathrm{B}}_1^{+} $$ map registered a significant decrease inT 1 $$ {\mathrm{T}}_1 $$ gradient through slice.

CONCLUSION

B 0 $$ {\mathrm{B}}_0 $$ inhomogeneities varying through slice were seen to have an impact on the accuracy of 2D double angleB 1 + $$ {\mathrm{B}}_1^{+} $$ maps using gradient-echo sequences. Consideration of this confounder is crucial for research relying on accurate knowledge of the true excitation flip angles, as is the case ofT 1 $$ {\mathrm{T}}_1 $$ mapping using a spoiled gradient recalled echo sequence.

Emerging Trends in Magnetic Resonance Fingerprinting for Quantitative Biomedical Imaging Applications: A Review

Magnetic resonance imaging (MRI) stands as a vital medical imaging technique, renowned for its ability to offer high-resolution images of the human body with remarkable soft-tissue contrast. This enables healthcare professionals to gain valuable insights into various aspects of the human body, including morphology, structural integrity, and physiological processes. Quantitative imaging provides compositional measurements of the human body, but, currently, either it takes a long scan time or is limited to low spatial resolutions. Undersampled k-space data acquisitions have significantly helped to reduce MRI scan time, while compressed sensing (CS) and deep learning (DL) reconstructions have mitigated the associated undersampling artifacts. Alternatively, magnetic resonance fingerprinting (MRF) provides an efficient and versatile framework to acquire and quantify multiple tissue properties simultaneously from a single fast MRI scan. The MRF framework involves four key aspects: (1) pulse sequence design; (2) rapid (undersampled) data acquisition; (3) encoding of tissue properties in MR signal evolutions or fingerprints; and (4) simultaneous recovery of multiple quantitative spatial maps. This paper provides an extensive literature review of the MRF framework, addressing the trends associated with these four key aspects. There are specific challenges in MRF for all ranges of magnetic field strengths and all body parts, which can present opportunities for further investigation. We aim to review the best practices in each key aspect of MRF, as well as for different applications, such as cardiac, brain, and musculoskeletal imaging, among others. A comprehensive review of these applications will enable us to assess future trends and their implications for the translation of MRF into these biomedical imaging applications.

Cramér-Rao Bound Optimized Subspace Reconstruction in Quantitative MRI

We extend the traditional framework for estimating subspace bases that maximize the preserved signal energy to additionally preserve the Cramér-Rao bound (CRB) of the biophysical parameters and, ultimately, improve accuracy and precision in the quantitative maps. To this end, we introduce an approximate compressed CRB based on orthogonalized versions of the signal's derivatives with respect to the model parameters. This approximation permits singular value decomposition (SVD)-based minimization of both the CRB and signal losses during compression. Compared to the traditional SVD approach, the proposed method better preserves the CRB across all biophysical parameters with negligible cost to the preserved signal energy, leading to reduced bias and variance of the parameter estimates in simulation. In vivo, improved accuracy and precision are observed in two quantitative neuroimaging applications, permitting the use of smaller basis sizes in subspace reconstruction and offering significant computational savings.

Optimal flip angles for in vivo liver 3D T1 mapping and B1+ mapping at 3T

PURPOSE

The spoiled gradient recalled echo (SPGR) sequence with variable flip angles (FAs) enables whole liverT 1 $$ {T}_1 $$ mapping at high spatial resolutions but is strongly affected byB 1 + $$ {B}_1^{+} $$ inhomogeneities. The aim of this work was to study how the precision of acquiredT 1 $$ {T}_1 $$ maps is affected by theT 1 $$ {T}_1 $$ andB 1 + $$ {B}_1^{+} $$ ranges observed in the liver at 3T, as well as how noise propagates from the acquired signals into the resultingT 1 $$ {T}_1 $$ map.

THEORY

TheT 1 $$ {T}_1 $$ variance was estimated through the Fisher information matrix with a total noise variance including, for the first time, theB 1 + $$ {B}_1^{+} $$ map noise as well as contributions from the SPGR noise.

METHODS

Simulations were used to find the optimal FAs for both theB 1 + $$ {B}_1^{+} $$ mapping andT 1 $$ {T}_1 $$ mapping. The simulations results were validated in 10 volunteers.

RESULTS

Four optimized SPGR FAs of 2°, 2°, 15°, and 15° (TR = 4.1 ms) andB 1 + $$ {B}_1^{+} $$ map FAs of 65° and 130° achieved aT 1 $$ {T}_1 $$ coefficient of variation of 6.2 ± 1.7% across 10 volunteers and validated our theoretical model. Four optimal FAs outperformed five uniformly spaced FAs, saving the patient one breath-hold. For the liverB 1 + $$ {B}_1^{+} $$ andT 1 $$ {T}_1 $$ parameter space at 3T, a higher return inT 1 $$ {T}_1 $$ precision was obtained by investing FAs in the SPGR acquisition rather than in theB 1 + $$ {B}_1^{+} $$ map.

CONCLUSION

A novel framework was developed and validated to calculate the SPGRT 1 $$ {T}_1 $$ variance. This framework efficiently identifies optimal FA values and determines the total number of SPGR andB 1 + $$ {B}_1^{+} $$ measurements needed to achieve a desiredT 1 $$ {T}_1 $$ precision.

Deep-Learning-Based Contrast Synthesis From MRF Parameter Maps in the Knee Joint

BACKGROUND

Magnetic resonance fingerprinting (MRF) is a method to speed up acquisition of quantitative MRI data. However, MRF does not usually produce contrast-weighted images that are required by radiologists, limiting reachable total scan time improvement. Contrast synthesis from MRF could significantly decrease the imaging time.

PURPOSE

To improve clinical utility of MRF by synthesizing contrast-weighted MR images from the quantitative data provided by MRF, using U-nets that were trained for the synthesis task utilizing L1- and perceptual loss functions, and their combinations.

STUDY TYPE

Retrospective.

POPULATION

Knee joint MRI data from 184 subjects from Northern Finland 1986 Birth Cohort (ages 33-35, gender distribution not available).

FIELD STRENGTH AND SEQUENCE

A 3 T, multislice-MRF, proton density (PD)-weighted 3D-SPACE (sampling perfection with application optimized contrasts using different flip angle evolution), fat-saturated T2-weighted 3D-space, water-excited double echo steady state (DESS).

ASSESSMENT

Data were divided into training, validation, test, and radiologist's assessment sets in the following way: 136 subjects to training, 3 for validation, 3 for testing, and 42 for radiologist's assessment. The synthetic and target images were evaluated using 5-point Likert scale by two musculoskeletal radiologists blinded and with quantitative error metrics.

STATISTICAL TESTS

Friedman's test accompanied with post hoc Wilcoxon signed-rank test and intraclass correlation coefficient. The statistical cutoff P <0.05 adjusted by Bonferroni correction as necessary was utilized.

RESULTS

The networks trained in the study could synthesize conventional images with high image quality (Likert scores 3-4 on a 5-point scale). Qualitatively, the best synthetic images were produced with combination of L1- and perceptual loss functions and perceptual loss alone, while L1-loss alone led to significantly poorer image quality (Likert scores below 3). The interreader and intrareader agreement were high (0.80 and 0.92, respectively) and significant. However, quantitative image quality metrics indicated best performance for the pure L1-loss.

DATA CONCLUSION

Synthesizing high-quality contrast-weighted images from MRF data using deep learning is feasible. However, more studies are needed to validate the diagnostic accuracy of these synthetic images.

EVIDENCE LEVEL

4.

TECHNICAL EFFICACY

Stage 1.

Quantitative magnetization transfer MRI unbiased by on-resonance saturation and dipolar order contributions

PURPOSE

To demonstrate the bias in quantitative MT (qMT) measures introduced by the presence of dipolar order and on-resonance saturation (ONRS) effects using magnetization transfer (MT) spoiled gradient-recalled (SPGR) acquisitions, and propose changes to the acquisition and analysis strategies to remove these biases.

METHODS

The proposed framework consists of SPGR sequences prepared with simultaneous dual-offset frequency-saturation pulses to cancel out dipolar order and associated relaxation (T_1D ) effects in Z-spectrum acquisitions, and a matched quantitative MT (qMT) mathematical model that includes ONRS effects of readout pulses. Variable flip angle and MT data were fitted jointly to simultaneously estimate qMT parameters (macromolecular proton fraction [MPF], T_2,f , T_2,b , R, and free pool T₁ ). This framework is compared with standard qMT and investigated in terms of reproducibility, and then further developed to follow a joint single-point qMT methodology for combined estimation of MPF and T₁ .

RESULTS

Bland-Altman analyses demonstrated a systematic underestimation of MPF (-2.5% and -1.3%, on average, in white and gray matter, respectively) and overestimation of T₁ (47.1 ms and 38.6 ms, on average, in white and gray matter, respectively) if both ONRS and dipolar order effects are ignored. Reproducibility of the proposed framework is excellent (ΔMPF = -0.03% and ΔT₁  = -19.0 ms). The single-point methodology yielded consistent MPF and T₁ values with respective maximum relative average bias of -0.15% and -3.5 ms found in white matter.

CONCLUSION

The influence of acquisition strategy and matched mathematical model with regard to ONRS and dipolar order effects in qMT-SPGR frameworks has been investigated. The proposed framework holds promise for improved accuracy with reproducibility.

Optimized three-dimensional ultrashort echo time: Magnetic resonance fingerprinting for myelin tissue fraction mapping

Quantitative assessment of brain myelination has gained attention for both research and diagnosis of neurological diseases. However, conventional pulse sequences cannot directly acquire the myelin-proton signals due to its extremely short T2 and T2* values. To obtain the myelin-proton signals, dedicated short T2 acquisition techniques, such as ultrashort echo time (UTE) imaging, have been introduced. However, it remains challenging to isolate the myelin-proton signals from tissues with longer T2. In this article, we extended our previous two-dimensional ultrashort echo time magnetic resonance fingerprinting (UTE-MRF) with dual-echo acquisition to three dimensional (3D). Given a relatively low proton density (PD) of myelin-proton, we utilized Cramér-Rao Lower Bound to encode myelin-proton with the maximal SNR efficiency for optimizing the MR fingerprinting design, in order to improve the sensitivity of the sequence to myelin-proton. In addition, with a second echo of approximately 3 ms, myelin-water component can be also captured. A myelin-tissue (myelin-proton and myelin-water) fraction mapping can be thus calculated. The optimized 3D UTE-MRF with dual-echo acquisition is tested in simulations, physical phantom and in vivo studies of both healthy subjects and multiple sclerosis patients. The results suggest that the rapidly decayed myelin-proton and myelin-water signal can be depicted with UTE signals of our method at clinically relevant resolution (1.8 mm isotropic) in 15 min. With its good sensitivity to myelin loss in multiple sclerosis patients demonstrated, our method for the whole brain myelin-tissue fraction mapping in clinical friendly scan time has the potential for routine clinical imaging.

Simultaneous Optimization of MP2RAGE T1 -weighted (UNI) and FLuid And White matter Suppression (FLAWS) brain images at 7T using Extended Phase Graph (EPG) Simulations

PURPOSE

The MP2RAGE sequence is typically optimized for either T1 -weighted uniform image (UNI) or gray matter-dominant fluid and white matter suppression (FLAWS) contrast images. Here, the purpose was to optimize an MP2RAGE protocol at 7 Tesla to provide UNI and FLAWS images simultaneously in a clinically applicable acquisition time at <0.7 mm isotropic resolution.

METHODS

Using the extended phase graph formalism, the signal evolution of the MP2RAGE sequence was simulated incorporating T2 relaxation, diffusion, RF spoiling, and B1 + variability. Flip angles and TI were optimized at different TRs (TRMP2RAGE ) to produce an optimal contrast-to-noise ratio for UNI and FLAWS images. Simulation results were validated by comparison to MP2RAGE brain scans of 5 healthy subjects, and a final protocol at TRMP2RAGE  = 4000 ms was applied in 19 subjects aged 8-62 years with and without epilepsy.

RESULTS

FLAWS contrast images could be obtained while maintaining >85% of the optimal UNI contrast-to-noise ratio. Using TI1 /TI2 /TRMP2RAGE of 650/2280/4000 ms, 6/8 partial Fourier in the inner phase-encoding direction, and GRAPPA factor = 4 in the other, images with 0.65 mm isotropic resolution were produced in <7.5 min. The contrast-to-noise ratio was around 20% smaller at TRMP2RAGE  = 4000 ms compared to that at TRMP2RAGE  = 5000 ms; however, the 20% shorter duration makes TRMP2RAGE  = 4000 ms a good candidate for clinical applications example, pediatrics.

CONCLUSION

FLAWS and UNI images could be obtained in a single scan with 0.65 mm isotropic resolution, providing a set of high-contrast images and full brain coverage in a clinically applicable scan time. Images with excellent anatomical detail were demonstrated over a wide age range using the optimized parameter set.

Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling

PURPOSE

The effective transverse relaxation rate (R 2 * $$ {\mathrm{R}}_2^{\ast } $$ ) is influenced by biological features that make it a useful means of probing brain microstructure. However, confounding factors such as dependence on flip angle (α) and fiber orientation with respect to the main field (θ $$ \uptheta $$ ) complicate interpretation. The α- andθ $$ \uptheta $$ -dependence stem from the existence of multiple sub-voxel micro-environments (e.g., myelin and non-myelin water compartments). Ordinarily, it is challenging to quantify these sub-compartments; therefore, neuroscientific studies commonly make the simplifying assumption of a mono-exponential decay obtaining a singleR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimate per voxel. In this work, we investigated how the multi-compartment nature of tissue microstructure affects single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.

METHODS

We used 2-pool (myelin and non-myelin water) simulations to characterize the bias in single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. Based on our numeric observations, we introduced a linear model that partitionsR 2 * $$ {\mathrm{R}}_2^{\ast } $$ into α-dependent and α-independent components and validated this in vivo at 7T. We investigated the dependence of both components on the sub-compartment properties and assessed their robustness, orientation dependence, and reproducibility empirically.

RESULTS

R 2 * $$ {\mathrm{R}}_2^{\ast } $$ increased with myelin water fraction and residency time leading to a linear dependence on α. We observed excellent agreement between our numeric and empirical results. Furthermore, the α-independent component of the proposed linear model was robust to the choice of α and reduced dependence on fiber orientation, although it suffered from marginally higher noise sensitivity.

CONCLUSION

We have demonstrated and validated a simple approach that mitigates flip angle and orientation biases in single-compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.

A joint linear reconstruction for multishot diffusion weighted non-Carr-Purcell-Meiboom-Gill fast spin echo with full signal

PURPOSE

Diffusion weighted Fast Spin Echo (DW-FSE) is a promising approach for distortionless DW imaging that is robust to system imperfections such as eddy currents and off-resonance. Due to non-Carr-Purcell-Meiboom-Gill (CPMG) magnetization, most DW-FSE sequences discard a large fraction of the signal (2 - 2 × $$ \sqrt{2}-2\times $$ ), reducing signal-to-noise ratio (SNR) efficiency compared to DW-EPI. The full FSE signal can be preserved by quadratically incrementing the transmit phase of the refocusing pulses, but this method of resolving non-CPMG magnetization has only been applied to single-shot DW-FSE due to challenges associated with image reconstruction. We present a joint linear reconstruction for multishot quadratic phase increment data that addresses these challenges and corrects ghosting from both shot-to-shot phase and intrashot signal oscillations. Multishot imaging reduces T2 blur and joint reconstruction of shots improves g-factor performance. A thorough analysis on the condition number of the proposed linear system is described.

METHODS

A joint multishot reconstruction is derived from the non-CPMG signal model. Multishot quadratic phase increment DW-FSE was tested in a standardized diffusion phantom and compared to single-shot DW-FSE and DW-EPI in vivo in the brain, cervical spine, and prostate. The pseudo multiple replica technique was applied to generate g-factor and SNR maps.

RESULTS

The proposed joint shot reconstruction eliminates ghosting from shot-to-shot phase and intrashot oscillations. g-factor performance is improved compared to previously proposed reconstructions, permitting efficient multishot imaging. apparent diffusion coefficient estimates in phantom experiments and in vivo are comparable to those obtained with conventional methods.

CONCLUSION

Multi-shot non-CPMG DW-FSE data with full signal can be jointly reconstructed using a linear model.

Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions

Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acquired in a healthy population. This study focuses on multi-echo T₂ relaxometry, a qMRI technique that probes the complex tissue microstructure by differentiating compartment-specific T₂ relaxation times. However, estimation methods are still limited by their sensitivity to the underlying noise. Moreover, estimating the model's parameters is challenging because the resulting inverse problem is ill-posed, requiring advanced numerical regularization techniques. As a result, the estimates from distinct regularization strategies are different. In this work, we aimed to investigate the variability and reproducibility of different techniques for estimating the transverse relaxation time of the intra- and extra-cellular space (T2IE) in gray (GM) and white matter (WM) tissue in a clinical setting, using a multi-site, multi-session, and multi-run T₂ relaxometry dataset. To this end, we evaluated three different techniques for estimating the T₂ spectra (two regularized non-negative least squares methods and a machine learning approach). Two independent analyses were performed to study the effect of using raw and denoised data. For both the GM and WM regions, and the raw and denoised data, our results suggest that the principal source of variance is the inter-subject variability, showing a higher coefficient of variation (CoV) than those estimated for the inter-site, inter-session, and inter-run, respectively. For all reconstruction methods studied, the CoV ranged between 0.32 and 1.64%. Interestingly, the inter-session variability was close to the inter-scanner variability with no statistical differences, suggesting that T2IE is a robust parameter that could be employed in multi-site neuroimaging studies. Furthermore, the three tested methods showed consistent results and similar intra-class correlation (ICC), with values superior to 0.7 for most regions. Results from raw data were slightly more reproducible than those from denoised data. The regularized non-negative least squares method based on the L-curve technique produced the best results, with ICC values ranging from 0.72 to 0.92.

Reproducibility of rapid multi-parameter mapping at 3T and 7T with highly segmented and accelerated 3D-EPI

PURPOSE

Quantitative multi-parameter mapping (MPM) has been shown to provide good longitudinal and cross-sectional reproducibility for clinical research. Unfortunately, acquisition times (TAs) are typically infeasible for routine scanning at high resolutions.

METHODS

A fast whole-brain MPM protocol based on interleaved multi-shot 3D-EPI with controlled aliasing (SC-EPI) at 3T and 7T is proposed and compared with MPM using a standard spoiled gradient echo (FLASH) sequence. Four parameters (R₁ , PD, R 2 * $$ {R}_2^{\ast } $$ , and MTsat) were measured in less than 3 min at 1 mm isotropic resolution. Five subjects went through the same scanning sessions twice at each scanner. The intra-subject coefficient of variation (scan-rescan) (CoV) was estimated for each protocol and scanner to assess the longitudinal reproducibility.

RESULTS

At 3T, the CoV of SC-EPI ranged between 1.2%-4.8% for PD and R₁ , 2.8%-10.6% for R 2 * $$ {R}_2^{\ast } $$ and MTsat, which was comparable with FLASH (0.6%-4.9% for PD and R₁ , 2.6%-11.3% for R 2 * $$ {R}_2^{\ast } $$ and MTsat). At 7T, where the SC-EPI TA was reduced to ∼2 min, the CoV of SC-EPI (1.4%-10.6% for PD, R₁ , and R 2 * $$ {R}_2^{\ast } $$ ) was 1.2-2.4 times larger than the CoV of FLASH (1.0%-15%) and MTsat showed much higher variability across subjects. The SC-EPI-MPM protocol at 3T showed high reproducibility and yielded stable quantitative maps at a clinically feasible resolution and scan time, whereas at 7T, MT saturation homogeneity needs to be improved.

CONCLUSION

SC-EPI-based MPM is feasible as an additional MRI modality in clinical or population studies where the parameters offer great potential as biomarkers.

A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN)

Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool to investigate equivocal neurological patterns during fetal development. However, the number of acquisitions of satisfactory quality available in this cohort of sensitive subjects remains scarce, thus hindering the validation of advanced image processing techniques. Numerical phantoms can mitigate these limitations by providing a controlled environment with a known ground truth. In this work, we present FaBiAN, an open-source Fetal Brain magnetic resonance Acquisition Numerical phantom that simulates clinical T2-weighted fast spin echo sequences of the fetal brain. This unique tool is based on a general, flexible and realistic setup that includes stochastic fetal movements, thus providing images of the fetal brain throughout maturation comparable to clinical acquisitions. We demonstrate its value to evaluate the robustness and optimize the accuracy of an algorithm for super-resolution fetal brain magnetic resonance imaging from simulated motion-corrupted 2D low-resolution series compared to a synthetic high-resolution reference volume. We also show that the images generated can complement clinical datasets to support data-intensive deep learning methods for fetal brain tissue segmentation.

T1-independent exchange rate quantification using saturation- or phase sensitive-water exchange spectroscopy

PURPOSE

Water Exchange Spectroscopy (WEX) is a direct measurement of the exchange rate k_sw of labile protons from a solute to water in which the exchange time is varied. However the useful information can be masked by the T₁-decay of the solvent pool. We propose Saturation-WEX and Phase Sensitive WEX (PS-WEX) as an extension upon the WEX approach to reduce T₁-masking. Additionally PS-WEX takes advantage of the phase information contained in the WEX signal to improve the dynamic range.

METHODS

By introducing an additional RF-pulse and fixing the exchange time delay the T₁-dependence of the signal is reduced. By exploiting the phase sensitivity of the WEX pathway the dynamic range can be increased. This approach is validated using simulations as well as phantom measurements.

RESULTS

The improved dynamic range is demonstrated in measurements. The fixed exchange time reduces the influence of the T₁-decay on the signal curve leading to improved fit quality.

CONCLUSION

Sat-WEX and PS-WEX are an extension to the well established WEX approach with a less complex fit equation and in the case of PS-WEX improved dynamic range, allowing more accurate quantification.

Abdominal T2-Weighted Imaging and T2 Mapping Using a Variable Flip Angle Radial Turbo Spin-Echo Technique

BACKGROUND

T2 mapping is of great interest in abdominal imaging but current methods are limited by low resolution, slice coverage, motion sensitivity, or lengthy acquisitions.

PURPOSE

Develop a radial turbo spin-echo technique with refocusing variable flip angles (RADTSE-VFA) for high spatiotemporal T2 mapping and efficient slice coverage within a breath-hold and compare to the constant flip angle counterpart (RADTSE-CFA).

STUDY TYPE

Prospective technical efficacy.

SUBJECTS

Testing performed on agarose phantoms and 12 patients. Focal liver lesion classification tested on malignant (N = 24) and benign (N = 11) lesions.

FIELD STRENGTH/SEQUENCE

1.5 T/RADTSE-VFA, RADTSE-CFA.

ASSESSMENT

A constrained objective function was used to optimize the refocusing flip angles. Phantom and/or in vivo data were used to assess relative contrast, T2 estimation, specific absorption rate (SAR), and focal liver lesion classification. STATISTICAL TESTS: t-Tests or Mann-Whitney Rank Sum tests were used.

RESULTS

Phantom data did not show significant differences in mean relative contrast (P = 0.10) and T2 accuracy (P = 0.99) between RADTSE-VFA and RADTSE-CFA. Adding noise caused T2 overestimation predominantly for RADTSE-CFA and low T2 values. In vivo results did not show significant differences in mean spleen-to-liver (P = 0.62) and kidney-to-liver (P = 0.49) relative contrast between RADTSE-VFA and RADTSE-CFA. Mean T2 values were not significantly different between the two techniques for spleen (T2VFA  = 109.2 ± 12.3 msec; T2CFA  = 110.7 ± 11.1 msec; P = 0.78) and kidney-medulla (T2VFA  = 113.0 ± 8.7 msec; T2CFA  = 114.0 ± 8.6 msec; P = 0.79). Liver T2 was significantly higher for RADTSE-CFA (T2VFA  = 52.6 ± 6.6 msec; T2CFA  = 60.4 ± 8.0 msec) consistent with T2 overestimation in the phantom study. Focal liver lesion classification had comparable T2 distributions for RADTSE-VFA and RADTSE-CFA for malignancies (P = 1.0) and benign lesions (P = 0.39). RADTSE-VFA had significantly lower SAR than RADTSE-CFA increasing slice coverage by 1.5.

DATA CONCLUSION

RADTSE-VFA provided noise-robust T2 estimation compared to the constant flip angle counterpart while generating T2-weighted images with comparable contrast. The VFA scheme minimized SAR improving slice efficiency for breath-hold imaging.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 1.

Revisiting the T2 spectrum imaging inverse problem: Bayesian regularized non-negative least squares

Multi-echo T₂ magnetic resonance images contain information about the distribution of T₂ relaxation times of compartmentalized water, from which we can estimate relevant brain tissue properties such as the myelin water fraction (MWF). Regularized non-negative least squares (NNLS) is the tool of choice for estimating non-parametric T₂ spectra. However, the estimation is ill-conditioned, sensitive to noise, and highly affected by the employed regularization weight. The purpose of this study is threefold: first, we want to underline that the apparently innocuous use of two alternative parameterizations for solving the inverse problem, which we called the standard and alternative regularization forms, leads to different solutions; second, to assess the performance of both parameterizations; and third, to propose a new Bayesian regularized NNLS method (BayesReg). The performance of BayesReg was compared with that of two conventional approaches (L-curve and Chi-square (X²) fitting) using both regularization forms. We generated a large dataset of synthetic data, acquired in vivo human brain data in healthy participants for conducting a scan-rescan analysis, and correlated the myelin content derived from histology with the MWF estimated from ex vivo data. Results from synthetic data indicate that BayesReg provides accurate MWF estimates, comparable to those from L-curve and X², and with better overall stability across a wider signal-to-noise range. Notably, we obtained superior results by using the alternative regularization form. The correlations reported in this study are higher than those reported in previous studies employing the same ex vivo and histological data. In human brain data, the estimated maps from L-curve and BayesReg were more reproducible. However, the T₂ spectra produced by BayesReg were less affected by over-smoothing than those from L-curve. These findings suggest that BayesReg is a good alternative for estimating T₂ distributions and MWF maps.

Simultaneous T1 , T2 , and T1ρ cardiac magnetic resonance fingerprinting for contrast agent-free myocardial tissue characterization

PURPOSE

To develop a simultaneous T₁ , T₂ , and T_1ρ cardiac magnetic resonance fingerprinting (MRF) approach to enable comprehensive contrast agent-free myocardial tissue characterization in a single breath-hold scan.

METHODS

A 2D gradient-echo electrocardiogram-triggered cardiac MRF sequence with low flip angles, varying magnetization preparation, and spiral trajectory was acquired at 1.5 T to encode T₁ , T₂ , and T_1⍴ simultaneously. The MRF images were reconstructed using low-rank inversion, regularized with a multicontrast patch-based higher-order reconstruction. Parametric maps were generated and matched in the singular value domain to extended phase graph-based dictionaries. The proposed approach was tested in phantoms and 10 healthy subjects and compared against conventional methods in terms of coefficients of determination and best fits for the phantom study, and in terms of Bland-Altman agreement, average values and coefficient of variation of T₁ , T₂ , and T_1⍴ for the healthy subjects study.

RESULTS

The T₁ , T₂ , and T_1⍴ MRF values showed excellent correlation with conventional spin-echo and clinical mapping methods in phantom studies (r² > 0.97). Measured MRF values in myocardial tissue (mean ± SD) were 1133 ± 33 ms, 38.8 ± 3.5 ms, and 52.0 ± 4.0 ms for T₁ , T₂ and T1_⍴ , respectively, against 1053 ± 47 ms, 50.4 ± 3.9 ms, and 55.9 ± 3.3 ms for T₁ modified Look-Locker inversion imaging, T₂ gradient and spin echo, and T_1⍴ turbo field echo, respectively.

CONCLUSION

A cardiac MRF approach for simultaneous quantification of myocardial T₁ , T₂ , and T_1ρ in a single breath-hold MR scan of about 16 seconds has been proposed. The approach has been investigated in phantoms and healthy subjects showing good agreement with reference spin echo measurements and conventional clinical maps.

A strategy to reduce the sensitivity of inhomogeneous magnetization transfer (ihMT) imaging to radiofrequency transmit field variations at 3 T

PURPOSE

To minimize the sensitivity of inhomogeneous magnetization transfer gradient-echo (ihMT-GRE) imaging to radiofrequency (RF) transmit field ( B 1 + ) inhomogeneities at 3 T.

METHODS

The ihMT-GRE sequence was optimized by varying the concentration of the RF saturation energy over time, obtained by increasing the saturation pulse power while extending the sequence repetition time (TR). Different protocols were tested using numerical simulations and human in vivo experiments in the brain white matter (WM) of healthy subjects at 3 T. The sensitivity of the ihMT ratio (ihMTR) to B 1 + variations was investigated by comparing measurements obtained at nominal transmitter adjustments and following a 20% global B 1 + drop. The resulting relative variations (δ_ihMTR ) were evaluated voxelwise as a function of the local B 1 + distribution. The reproducibility of the protocol providing minimal B 1 + bias was assessed in a test-retest experiment.

RESULTS

In line with simulations, ihMT-GRE experiments conducted at high concentration of the RF energy over time demonstrated strong reduction of the B 1 + inhomogeneity effects in the human WM. Under the optimal conditions of 350-ms TR and 3-µT root mean square (RMS) saturation power, 73% of all WM voxels presented δ_ihMTR below 10%. Reproducibility analysis yielded a close-to-zero systematic bias (ΔihMTR = -0.081%) and a high correlation (ρ² = 0.977) between test and retest experiments.

CONCLUSION

Concentrating RF saturation energy in ihMT-GRE sequences mitigates the sensitivity of the ihMTR to B 1 + variations and allows for clinical-ready ihMT imaging at 3 T. This feature is of particular interest for high and ultra-high field applications.

A unifying view on extended phase graphs and Bloch simulations for quantitative MRI

Quantitative MRI methods and learning-based algorithms require exact forward simulations. One critical factor to correctly describe magnetization dynamics is the effect of slice-selective RF pulses. While contemporary simulation techniques correctly capture their influence, they only provide final magnetization distributions, require to be run for each parameter set separately, and make it hard to derive general theoretical conclusions and to generate a fundamental understanding of echo formation in the presence of slice-profile effects. This work aims to provide a mathematically exact framework, which is equally intuitive as extended phase graphs (EPGs), but also considers slice-profiles through their natural spatial representation. We show, through an analytical, hybrid Bloch-EPG formalism, that the spatially-resolved EPG approach allows to exactly predict the signal dependency on off-resonance, spoiling moment, microscopic dephasing, and echo time. We also demonstrate that our formalism allows to use the same phase graph to simulate both gradient-spoiled and balanced SSFP-based MR sequences. We present a derivation of the formalism and identify the connection to existing methods, i.e. slice-selective Bloch, slice-selective EPG, and the partitioned EPG. As a use case, the proposed hybrid Bloch-EPG framework is applied to MR Fingerprinting.

Fast and accurate modeling of transient-state, gradient-spoiled sequences by recurrent neural networks

Fast and accurate modeling of MR signal responses are typically required for various quantitative MRI applications, such as MR fingerprinting. This work uses a new extended phase graph (EPG)-Bloch model for accurate simulation of transient-state, gradient-spoiled MR sequences, and proposes a recurrent neural network (RNN) as a fast surrogate of the EPG-Bloch model for computing large-scale MR signals and derivatives. The computational efficiency of the RNN model is demonstrated by comparisons with other existing models, showing one to three orders of acceleration compared with the latest GPU-accelerated, open-source EPG package. By using numerical and in vivo brain data, two used cases, namely, MRF dictionary generation and optimal experimental design, are also provided. Results show that the RNN surrogate model can be efficiently used for computing large-scale dictionaries of transient-state signals and derivatives within tens of seconds, resulting in several orders of magnitude acceleration with respect to state-of-the-art implementations. The practical application of transient-state quantitative techniques can therefore be substantially facilitated.

Age- and gender-related differences in brain tissue microstructure revealed by multi-component T2 relaxometry

In spite of extensive work, inconsistent findings and lack of specificity in most neuroimaging techniques used to examine age- and gender-related patterns in brain tissue microstructure indicate the need for additional research. Here, we performed the largest Multi-component T₂ relaxometry cross-sectional study to date in healthy adults (N = 145, 18-60 years). Five quantitative microstructure parameters derived from various segments of the estimated T₂ spectra were evaluated, allowing a more specific interpretation of results in terms of tissue microstructure. We found similar age-related myelin water fraction (MWF) patterns in men and women but we also observed differential male related results including increased MWF content in a few white matter tracts, a faster decline with age of the intra- and extra-cellular water fraction and its T₂ relaxation time (i.e. steeper age related negative slopes) and a faster increase in the free and quasi-free water fraction, spanning the whole grey matter. Such results point to a sexual dimorphism in brain tissue microstructure and suggest a lesser vulnerability to age-related changes in women.

Efficient T2 mapping with blip-up/down EPI and gSlider-SMS (T2 -BUDA-gSlider)

PURPOSE

To rapidly obtain high isotropic-resolution T₂ maps with whole-brain coverage and high geometric fidelity.

METHODS

A T₂ blip-up/down EPI acquisition with generalized slice-dithered enhanced resolution (T₂ -BUDA-gSlider) is proposed. A RF-encoded multi-slab spin-echo (SE) EPI acquisition with multiple TEs was developed to obtain high SNR efficiency with reduced TR. This was combined with an interleaved 2-shot EPI acquisition using blip-up/down phase encoding. An estimated field map was incorporated into the joint multi-shot EPI reconstruction with a structured low rank constraint to achieve distortion-free and robust reconstruction for each slab without navigation. A Bloch simulated subspace model was integrated into gSlider reconstruction and used for T₂ quantification.

RESULTS

In vivo results demonstrated that the T₂ values estimated by the proposed method were consistent with gold standard spin-echo acquisition. Compared to the reference 3D fast spin echo (FSE) images, distortion caused by off-resonance and eddy current effects were effectively mitigated.

CONCLUSION

BUDA-gSlider SE-EPI acquisition and gSlider-subspace joint reconstruction enabled distortion-free whole-brain T₂ mapping in 2 min at ~1 mm³ isotropic resolution, which could bring significant benefits to related clinical and neuroscience applications.

Imperfect spoiling in variable flip angle T1 mapping at 7T: Quantifying and minimizing impact

Purpose

The variable flip angle (VFA) approach to T₁ mapping assumes perfectly spoiled transverse magnetisation at the end of each repetition time (TR). Despite radiofrequency (RF) and gradient spoiling, this condition is rarely met, leading to erroneous T₁ estimates (T1app). Theoretical corrections can be applied but make assumptions about tissue properties, for example, a global T₂ time. Here, we investigate the effect of imperfect spoiling at 7T and the interaction between the RF and gradient spoiling conditions, additionally accounting for diffusion. We provide guidance on the optimal approach to maximise the accuracy of the T₁ estimate in the context of 3D multi‐echo acquisitions.

Methods

The impact of the spoiling regime was investigated through numerical simulations, phantom and invivo experiments.

Results

The predicted dependence of T1app on tissue properties, system settings, and spoiling conditions was observed in both phantom and in vivo experiments. Diffusion effects modulated the dependence of T1app on both B1+ efficiency and T₂ times.

Conclusion

Error in T1app can be minimized by using an RF spoiling increment and gradient spoiler moment combination that minimizes T₂‐dependence and safeguards image quality. Although the diffusion effect was comparatively small at 7T, correction factors accounting for this effect are recommended.

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Variable flip angle echo planar time-resolved imaging (vFA-EPTI) for fast high-resolution gradient echo myelin water imaging

Myelin water imaging techniques based on multi-compartment relaxometry have been developed as an important tool to measure myelin concentration in vivo, but are limited by the long scan time of multi-contrast multi-echo acquisition. In this work, a fast imaging technique, termed variable flip angle Echo Planar Time-Resolved Imaging (vFA-EPTI), is developed to acquire multi-echo and multi-flip-angle gradient-echo data with significantly reduced acquisition time, providing rich information for multi-compartment analysis of gradient-echo myelin water imaging (GRE-MWI). The proposed vFA-EPTI method achieved 26 folds acceleration with good accuracy by utilizing an efficient continuous readout, optimized spatiotemporal encoding across echoes and flip angles, as well as a joint subspace reconstruction. An approach to estimate off-resonance field changes between different flip-angle acquisitions was also developed to ensure high-quality joint reconstruction across flip angles. The accuracy of myelin water fraction (MWF) estimate under high acceleration was first validated by a retrospective undersampling experiment using a lengthy fully-sampled data as reference. Prospective experiments were then performed where whole-brain MWF and multi-compartment quantitative maps were obtained in 5 min at 1.5 mm isotropic resolution and 24 min at 1 mm isotropic resolution at 3T. Additionally, ultra-high resolution data at 600 μm isotropic resolution were acquired at 7T, which show detailed structures within the cortex such as the line of Gennari, demonstrating the ability of the proposed method for submillimeter GRE-MWI that can be used to study cortical myeloarchitecture in vivo.

Comparison of multi echo T2 relaxation and steady state approaches for myelin imaging in the central nervous system

The traditional approach for measuring myelin-associated water with quantitative magnetic resonance imaging (MRI) uses multi-echo T₂ relaxation data to calculate the myelin water fraction (MWF). A fundamentally different approach, abbreviated “mcDESPOT”, uses a more efficient steady-state acquisition to generate an equivalent metric (f_M). Although previous studies have demonstrated inherent instability and bias in the complex mcDESPOT analysis procedure, f_M has often been used as a surrogate for MWF. We produced and compared multivariate atlases of MWF and f_M in healthy human brain and cervical spinal cord (available online) and compared their ability to detect multiple sclerosis pathology. A significant bias was found in all regions (p < 10^–5), albeit reversed for spinal cord (f_M-MWF =  − 3.4%) compared to brain (+ 6.2%). MWF and f_M followed an approximately linear relationship for regions with MWF <  ~ 10%. For MWF >  ~ 10%, the relationship broke down and f_M no longer increased in tandem with MWF. For multiple sclerosis patients, MWF and f_M Z score maps showed overlapping areas of low Z score and similar trends between patients and brain regions, although those of f_M generally had greater spatial extent and magnitude of severity. These results will guide future choice of myelin-sensitive quantitative MRI and improve interpretation of studies using either myelin imaging approach.

Comparison of non-parametric T2 relaxometry methods for myelin water quantification

Multi-component T₂ relaxometry allows probing tissue microstructure by assessing compartment-specific T₂ relaxation times and water fractions, including the myelin water fraction. Non-negative least squares (NNLS) with zero-order Tikhonov regularization is the conventional method for estimating smooth T₂ distributions. Despite the improved estimation provided by this method compared to non-regularized NNLS, the solution is still sensitive to the underlying noise and the regularization weight. This is especially relevant for clinically achievable signal-to-noise ratios. In the literature of inverse problems, various well-established approaches to promote smooth solutions, including first-order and second-order Tikhonov regularization, and different criteria for estimating the regularization weight have been proposed, such as L-curve, Generalized Cross-Validation, and Chi-square residual fitting. However, quantitative comparisons between the available reconstruction methods for computing the T₂ distribution, and between different approaches for selecting the optimal regularization weight, are lacking. In this study, we implemented and evaluated ten reconstruction algorithms, resulting from the individual combinations of three penalty terms with three criteria to estimate the regularization weight, plus non-regularized NNLS. Their performance was evaluated both in simulated data and real brain MRI data acquired from healthy volunteers through a scan-rescan repeatability analysis. Our findings demonstrate the need for regularization. As a result of this work, we provide a list of recommendations for selecting the optimal reconstruction algorithms based on the acquired data. Moreover, the implemented methods were packaged in a freely distributed toolbox to promote reproducible research, and to facilitate further research and the use of this promising quantitative technique in clinical practice.

Model-informed machine learning for multi-component T2 relaxometry

Recovering the T₂ distribution from multi-echo T₂ magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-structure, such as the myelin water fraction (MWF). In this work, we propose to combine machine learning and aspects of parametric (fitting from the MRI signal using biophysical models) and non-parametric (model-free fitting of the T₂ distribution from the signal) approaches to T₂ relaxometry in brain tissue by using a multi-layer perceptron (MLP) for the distribution reconstruction. For training our network, we construct an extensive synthetic dataset derived from biophysical models in order to constrain the outputs with a priori knowledge of in vivo distributions. The proposed approach, called Model-Informed Machine Learning (MIML), takes as input the MR signal and directly outputs the associated T₂ distribution. We evaluate MIML in comparison to a Gaussian Mixture Fitting (parametric) and Regularized Non-Negative Least Squares algorithms (non-parametric) on synthetic data, an ex vivo scan, and high-resolution scans of healthy subjects and a subject with Multiple Sclerosis. In synthetic data, MIML provides more accurate and noise-robust distributions. In real data, MWF maps derived from MIML exhibit the greatest conformity to anatomical scans, have the highest correlation to a histological map of myelin volume, and the best unambiguous lesion visualization and localization, with superior contrast between lesions and normal appearing tissue. In whole-brain analysis, MIML is 22 to 4980 times faster than the non-parametric and parametric methods, respectively.

Quantitative magnetization transfer imaging for non-contrast enhanced detection of myocardial fibrosis

PURPOSE

To develop a novel gadolinium-free model-based quantitative magnetization transfer (qMT) technique to assess macromolecular changes associated with myocardial fibrosis.

METHODS

The proposed sequence consists of a two-dimensional breath-held dual shot interleaved acquisition of five MT-weighted (MTw) spoiled gradient echo images, with variable MT flip angles (FAs) and off-resonance frequencies. A two-pool exchange model and dictionary matching were used to quantify the pool size ratio (PSR) and bound pool T2 relaxation ( T 2 B ). The signal model was developed and validated using 25 MTw images on a bovine serum albumin (BSA) phantom and in vivo human thigh muscle. A protocol with five MTw images was optimized for single breath-hold cardiac qMT imaging. The proposed sequence was tested in 10 healthy subjects and 5 patients with myocardial fibrosis and compared to late gadolinium enhancement (LGE).

RESULTS

PSR values in the BSA phantom were within the confidence interval of previously reported values (concentration 10% BSA = 5.9 ± 0.1%, 15% BSA = 9.4 ± 0.2%). PSR and T 2 B in thigh muscle were also in agreement with literature (PSR = 10.9 ± 0.3%, T 2 B = 6.4 ± 0.4 us). In 10 healthy subjects, global left ventricular PSR was 4.30 ± 0.65%. In patients, PSR was reduced in areas associated with LGE (remote: 4.68 ± 0.70% vs. fibrotic: 3.12 ± 0.78 %, n = 5, P < .002).

CONCLUSION

In vivo model-based qMT mapping of the heart was performed for the first time, with promising results for non-contrast enhanced assessment of myocardial fibrosis.

Confounding factors in breast magnetic resonance fingerprinting: B 1 + , slice profile, and diffusion effects

PURPOSE

Magnetic resonance fingerprinting (MRF) offers rapid quantitative imaging but may be subject to confounding effects (CE) if these are not included in the model-based reconstruction. This study characterizes the influence of in-plane B 1 + , slice profile and diffusion effects on T₁ and T₂ estimation in the female breast at 1.5T.

METHODS

Simulations were used to predict the influence of each CE on the accuracy of MRF and to investigate the influence of electronic noise and spiral aliasing artefacts. The experimentally observed bias in regions of fibroglandular tissue (FGT) and fatty tissue (FT) was analyzed for undersampled spiral breast MRF data of 6 healthy volunteers by performing MRF reconstruction with and without a CE.

RESULTS

Theoretic analysis predicts T₁ under-/T₂ overestimation if the nominal flip angles are underestimated and inversely, T₁ under-/T₂ overestimation if omitting slice profile correction, and T₁ under-/T₂ underestimation if omitting diffusion in the signal model. Averaged over repeated signal simulations, including spiral aliasing artefacts affected precision more than accuracy. Strong in-plane B 1 + effects occurred in vivo, causing T₂ left-right inhomogeneity between both breasts. Their correction decreased the T₂ difference from 29 to 5 ms in FGT and from 29 to 9 ms in FT. Slice profile correction affected FGT T₂ most strongly, resulting in -22% smaller values. For the employed spoiler gradient strengths, diffusion did not affect the parameter maps, corresponding well with theoretic predictions.

CONCLUSION

Understanding CEs and their relative significance for an MRF sequence is important when defining an MRF signal model for accurate parameter mapping.

Improved MR fingerprinting for relaxation measurement in the presence of semisolid magnetization transfer

PURPOSE

To characterize and minimize the magnetization transfer (MT) effect in MR fingerprinting (MRF) relaxation measurements with a 2-pool (2P) MT model of multiple tissue types.

THEORY AND METHODS

Semisolid MT effect in MRF was modeled using 2P Bloch-McConnell equations. The combinations of MT parameters of multiple tissues (white [WM] and gray matter [GM]) were used to build the MRF dictionary. Both 1-pool (1P) and 2P models were simulated to characterize the dependence on MT. Relaxations measured using MRF with spin-echo saturation-recovery (SR) or inversion-recovery preparations were compared with conventional SR-prepared T1 and multiple spin-echo T2 measurements. The simulations results were validated with phantoms and brain tissue samples.

RESULTS

The MRF signal was different from the 1P and 2P models. 1P MRF produced significantly (P < .05) underestimated T1 in WM (20-30%) and GM (7-10%), while 2P MRF measured consistent T1 and T2 in both WM and GM with conventional measurements (pairwise test P > .1; correlated P < .05). Simulations showed that SR-prepared MRF measuring T1 had much less errors against the variation of the macromolecular fraction. Compared with inversion-recovery preparation, SR-prepared MRF produced higher relaxation correlations (R > 0.9) with conventional measurements in both WM and GM across samples, suggesting that SR-prepared MRF was less sensitive to the compositive effect of multiple MT parameters variations.

CONCLUSIONS

2P MRF using a combination of MT parameters for multiple tissue types can measure consistent relaxations with conventional methods. With the 2P models, SR-prepared MRF would provide an option for robust relaxation measurement under heterogeneous MT.

Magnetization transfer in magnetic resonance fingerprinting

PURPOSE

To study the effects of magnetization transfer (MT, in which a semi-solid spin pool interacts with the free pool), in the context of magnetic resonance fingerprinting (MRF).

METHODS

Simulations and phantom experiments were performed to study the impact of MT on the MRF signal and its potential influence on T1 and T2 estimation. Subsequently, an MRF sequence implementing off-resonance MT pulses and a dictionary with an MT dimension, generated by incorporating a two-pool model, were used to estimate the fractional pool size in addition to the B 1 + , T1 , and T2 values. The proposed method was evaluated in the human brain.

RESULTS

Simulations and phantom experiments showed that an MRF signal obtained from a cross-linked bovine serum sample is influenced by MT. Using a dictionary based on an MT model, a better match between simulations and acquired MR signals can be obtained (NRMSE 1.3% vs. 4.7%). Adding off-resonance MT pulses can improve the differentiation of MT from T1 and T2 . In vivo results showed that MT affects the MRF signals from white matter (fractional pool-size ~16%) and gray matter (fractional pool-size ~10%). Furthermore, longer T1 (~1060 ms vs. ~860 ms) and T2 values (~47 ms vs. ~35 ms) can be observed in white matter if MT is accounted for.

CONCLUSION

Our experiments demonstrated a potential influence of MT on the quantification of T1 and T2 with MRF. A model that encompasses MT effects can improve the accuracy of estimated relaxation parameters and allows quantification of the fractional pool size.

Magnetic resonance neurography of the lumbosacral plexus at 3 Tesla - CSF-suppressed imaging with submillimeter resolution by a three-dimensional turbo spin echo sequence

PURPOSE

To investigate magnetic resonance neurography (MRN) of the lumbosacral plexus (LSP) with cerebrospinal fluid (CSF) suppression by using submillimeter resolution for three-dimensional (3D) turbo spin echo (TSE) imaging.

MATERIALS AND METHODS

Using extended phase graph (EPG) analysis, the signal response of CSF was simulated considering dephasing from coherent motion for frequency-encoding voxel sizes ranging from 0.3 to 1.3 mm and for CSF velocities ranging from 0 to 4 cm/s. In-vivo MRN included 3D TSE data with frequency encoding parallel to the feet/head axis from 15 healthy adults (mean age: 28.5 ± 3.8 years, 5 females; acquisition voxel size: 2 × 2 × 2 mm³) and 16 pediatric patients (mean age: 6.7 ± 4.1 years, 7 females; acquisition voxel size: 0.7 × 0.7 × 1.4 mm³) acquired at 3 Tesla. Five of the adults were scanned repetitively with changing acquisition voxel sizes (1 × 2 × 2 mm³, 0.7 × 2× 2 mm³, and 0.5 × 2 × 2 mm³). Measurements of the bilateral ganglion of the L5 nerve root, averaged between sides, as well as the CSF in the thecal sac were obtained for all included subjects and compared between adults and pediatric patients and between voxel sizes, using a CSF-to-nerve signal ratio (CSFNR).

RESULTS

According to simulations, the CSF signal is reduced along the echo train for moving spins. Specifically, it can be reduced by over 90% compared to the maximum simulated signal for flow velocities above 2 cm/s, and could be most effectively suppressed by considering a frequency-encoding voxel size of 0.8 mm or less. For in-vivo measurements, mean CSFNR was 1.52 ± 0.22 for adults and 0.10 ± 0.03 for pediatric patients (p < .0001). Differences in CSFNR were significant between measurements using a voxel size of 2 × 2 × 2 mm³ and measurements in data with reduced voxel sizes (p ≤ .0012), with submillimeter resolution (particularly 0.5 × 2 × 2 mm³) providing highest CSF suppression.

CONCLUSIONS

Applying frequency-encoding voxel sizes in submillimeter range for 3D TSE imaging with frequency encoding parallel to the feet/head axis may considerably improve MRN of LSP pathology in adults in the future because of favorable CSF suppression.

Numerical approximation to the general kinetic model for ASL quantification

PURPOSE

To develop a numerical approximation to the general kinetic model for arterial spin labeling (ASL) quantification that will enable greater flexibility in ASL acquisition methods.

THEORY

The Bloch-McConnell equations are extended to include the effects of single-compartment inflow and outflow on both the transverse and longitudinal magnetization. These can be solved using an extension of Jaynes' matrix formalism with piecewise constant approximation of incoming labeled arterial flow and a clearance operator for outgoing venous flow.

METHODS

The proposed numerical approximation is compared with the general kinetic model using simulations of pulsed labeling and pseudo-continuous labeling and a broad range of transit time and bolus duration for tissue blood flow of 0.6 mL/g/min. Accuracy of the approximation is studied as a function of the timestep using Monte-Carlo simulations. Three additional scenarios are demonstrated: (1) steady-pulsed ASL, (2) MR fingerprinting ASL, and (3) balanced SSFP and spoiled gradient-echo sequences.

RESULTS

The proposed approximation was found to be arbitrarily accurate for pulsed labeling and pseudo-continuous labeling. The pulsed labeling/pseudo-continuous labeling approximation error compared with the general kinetic model was less than 0.002% (<0.002%) and less than 0.05% (<0.05%) for timesteps of 3 ms and 35 ms, respectively. The proposed approximation matched well with customized signal expressions of steady-pulsed ASL and MR fingerprinting ASL. The simulations of simultaneous modeling of flow, T₂ , and magnetization transfer showed an increase in steady-state balanced SSFP and spoiled gradient signals.

CONCLUSION

We demonstrate a numerical approximation of the "Bloch-McConnell flow" equations that enables arbitrarily accurate modeling of pulsed ASL and pseudo-continuous labeling signals comparable to the general kinetic model. This enables increased flexibility in the experiment design for quantitative ASL.

Does the magnetization transfer effect bias chemical exchange saturation transfer effects? Quantifying chemical exchange saturation transfer in the presence of magnetization transfer

Purpose

Chemical exchange saturation transfer (CEST) is an MRI technique sensitive to the presence of low‐concentration solute protons exchanging with water. However, magnetization transfer (MT) effects also arise when large semisolid molecules interact with water, which biases CEST parameter estimates if quantitative models do not account for macromolecular effects. This study establishes under what conditions this bias is significant and demonstrates how using an appropriate model provides more accurate quantitative CEST measurements.

Methods

CEST and MT data were acquired in phantoms containing bovine serum albumin and agarose. Several quantitative CEST and MT models were used with the phantom data to demonstrate how underfitting can influence estimates of the CEST effect. CEST and MT data were acquired in healthy volunteers, and a two‐pool model was fit in vivo and in vitro, whereas removing increasing amounts of CEST data to show biases in the CEST analysis also corrupts MT parameter estimates.

Results

When all significant CEST/MT effects were included, the derived parameter estimates for each CEST/MT pool significantly correlated (P < .05) with bovine serum albumin/agarose concentration; minimal or negative correlations were found with underfitted data. Additionally, a bootstrap analysis demonstrated that significant biases occur in MT parameter estimates (P < .001) when unmodeled CEST data are included in the analysis.

Conclusions

These results indicate that current practices of simultaneously fitting both CEST and MT effects in model‐based analyses can lead to significant bias in all parameter estimates unless a sufficiently detailed model is utilized. Therefore, care must be taken when quantifying CEST and MT effects in vivo by properly modeling data to minimize these biases.

Free-running cardiac magnetic resonance fingerprinting: Joint T1/T2 map and Cine imaging

PURPOSE

To develop and evaluate a novel non-ECG triggered 2D magnetic resonance fingerprinting (MRF) sequence allowing for simultaneous myocardial T₁ and T₂ mapping and cardiac Cine imaging.

METHODS

Cardiac MRF (cMRF) has been recently proposed to provide joint T₁/T₂ myocardial mapping by triggering the acquisition to mid-diastole and relying on a subject-dependent dictionary of MR signal evolutions to generate the maps. In this work, we propose a novel "free-running" (non-ECG triggered) cMRF framework for simultaneous myocardial T₁ and T₂ mapping and cardiac Cine imaging in a single scan. Free-running cMRF is based on a transient state bSSFP acquisition with tiny golden angle radial readouts, varying flip angle and multiple adiabatic inversion pulses. The acquired data is retrospectively gated into several cardiac phases, which are reconstructed with an approach that combines parallel imaging, low rank modelling and patch-based high-order tensor regularization. Free-running cMRF was evaluated in a standardized phantom and ten healthy subjects. Comparison with reference spin-echo, MOLLI, SASHA, T₂-GRASE and Cine was performed.

RESULTS

T₁ and T₂ values obtained with the proposed approach were in good agreement with reference phantom values (ICC(A,1) > 0.99). Reported values for myocardium septum T₁ were 1043 ± 48 ms, 1150 ± 100 ms and 1160 ± 79 ms for MOLLI, SASHA and free-running cMRF respectively and for T₂ of 51.7 ± 4.1 ms and 44.6 ± 4.1 ms for T₂-GRASE and free-running cMRF respectively. Good agreement was observed between free-running cMRF and conventional Cine 2D ejection fraction (bias = -0.83%).

CONCLUSION

The proposed free-running cardiac MRF approach allows for simultaneous assessment of myocardial T₁ and T₂ and Cine imaging in a single scan.

Water-fat Dixon cardiac magnetic resonance fingerprinting

Purpose

Cardiac magnetic resonance fingerprinting (cMRF) has been recently introduced to simultaneously provide T₁, T₂, and M₀ maps. Here, we develop a 3‐point Dixon‐cMRF approach to enable simultaneous water specific T₁, T₂, and M₀ mapping of the heart and fat fraction (FF) estimation in a single breath‐hold scan.

Methods

Dixon‐cMRF is achieved by combining cMRF with several innovations that were previously introduced for other applications, including a 3‐echo GRE acquisition with golden angle radial readout and a high‐dimensional low‐rank tensor constrained reconstruction to recover the highly undersampled time series images for each echo. Water–fat separation of the Dixon‐cMRF time series is performed to allow for water‐ and fat‐specific T₁, T₂, and M₀ estimation, whereas FF estimation is extracted from the M₀ maps. Dixon‐cMRF was evaluated in a standardized T₁–T₂ phantom, in a water–fat phantom, and in healthy subjects in comparison to current clinical standards: MOLLI, SASHA, T₂‐GRASE, and 6‐point Dixon proton density FF (PDFF) mapping.

Results

Dixon‐cMRF water T₁ and T₂ maps showed good agreement with reference T₁ and T₂ mapping techniques (R² > 0.99 and maximum normalized RMSE ~5%) in a standardized phantom. Good agreement was also observed between Dixon‐cMRF FF and reference PDFF (R² > 0.99) and between Dixon‐cMRF water T₁ and T₂ and water selective T₁ and T₂ maps (R² > 0.99) in a water–fat phantom. In vivo Dixon‐cMRF water T₁ values were in good agreement with MOLLI and water T₂ values were slightly underestimated when compared to T₂‐GRASE. Average myocardium septal T₁ values were 1129 ± 38 ms, 1026 ± 28 ms, and 1045 ± 32 ms for SASHA, MOLLI, and the proposed water Dixon‐cMRF. Average T₂ values were 51.7 ± 2.2 ms and 42.8 ± 2.6 ms for T₂‐GRASE and water Dixon‐cMRF, respectively. Dixon‐cMRF FF maps showed good agreement with in vivo PDFF measurements (R² > 0.98) and average FF in the septum was measured at 1.3%.

Conclusion

The proposed Dixon‐cMRF allows to simultaneously quantify myocardial water T₁, water T₂, and FF in a single breath‐hold scan, enabling multi‐parametric T₁, T₂, and fat characterization. Moreover, reduced T₁ and T₂ quantification bias caused by water–fat partial volume was demonstrated in phantom experiments.

snapMRF: GPU-accelerated magnetic resonance fingerprinting dictionary generation and matching using extended phase graphs

PURPOSE

Magnetic resonance fingerprinting (MRF) is a state-of-the-art quantitative MRI technique with a computationally demanding reconstruction process, the accuracy of which depends on the accuracy of the signal model employed. Having a fast, validated, open-source MRF reconstruction would improve the dependability and accuracy of clinical applications of MRF.

METHODS

We parallelized both dictionary generation and signal matching on the GPU by splitting the simulation and matching of dictionary atoms across threads. Signal generation was modeled using both Bloch equation simulation and the extended phase graph (EPG) formalism. Unit tests were implemented to ensure correctness. The new package, snapMRF, was tested with a calibration phantom and an in vivo brain.

RESULTS

Compared with other online open-source packages, dictionary generation was accelerated by 10-1000× and signal matching by 10-100×. On a calibration phantom, T₁ and T₂ values were measured with relative errors that were nearly identical to those from existing packages when using the same sequence and dictionary configuration, but errors were much lower when using variable sequences that snapMRF supports but that competitors do not.

CONCLUSION

Our open-source package snapMRF was significantly faster and retrieved accurate parameters, possibly enabling real-time parameter map generation for small dictionaries. Further refinements to the acquisition scheme and dictionary setup could improve quantitative accuracy.

MR fingerprinting for water T1 and fat fraction quantification in fat infiltrated skeletal muscles

PURPOSE

To develop a fast MR fingerprinting (MRF) sequence for simultaneous estimation of water T1 (T1_H2O ) and fat fraction (FF) in fat infiltrated skeletal muscles.

METHODS

The MRF sequence for T1_H2O and FF quantification (MRF T1-FF) comprises a 1400 radial spokes echo train, following nonselective inversion, with varying echo and repetition time, as well as prescribed flip angle. Undersampled frames were reconstructed at different acquisition time-points by nonuniform Fourier transform, and a bi-component model based on Bloch simulations applied to adjust the signal evolution and extract T1_H2O and FF. The sequence was validated on a multi-vial phantom, in three healthy volunteers and five patients with neuromuscular diseases. We evaluated the agreement between MRF T1-FF parameters and reference values and confounding effects due to B0 and B1 inhomogeneities.

RESULTS

In phantom, T1_H2O and FF were highly correlated with references values measured with multi-inversion time inversion recovery-stimulated echo acquisition mode and Dixon, respectively (R² > 0.99). In vivo, T1_H2O and FF determined by the MRF T1-FF sequence were also correlated with reference values (R² = 0.98 and 0.97, respectively). The precision on T1_H2O was better than 5% for muscles where FF was less than 0.4. Both T1_H2O and FF values were not confounded by B0 nor B1 inhomogeneities.

CONCLUSION

The MRF T1-FF sequence derived T1_H2O and FF values in voxels containing a mixture of water and fat protons. This method can be used to comprehend and characterize the effects of tissue water compartmentation and distribution on muscle T1 values in patients affected by chronic fat infiltration.

FASt single-breathhold 2D multislice myocardial T1 mapping (FAST1) at 1.5T for full left ventricular coverage in three breathholds

Background

Conventional myocardial T₁ mapping techniques such as modified Look–Locker inversion recovery (MOLLI) generate one T₁ map per breathhold. T₁ mapping with full left ventricular coverage may be desirable when spatial T₁ variations are expected. This would require multiple breathholds, increasing patient discomfort and prolonging scan time.

Purpose

To develop and characterize a novel FASt single‐breathhold 2D multislice myocardial T₁ mapping (FAST1) technique for full left ventricular coverage.

Study Type

Prospective.

Population/Phantom

Numerical simulation, agarose/NiCl₂ phantom, 9 healthy volunteers, and 17 patients.

Field Strength/Sequence

1.5T/FAST1.

Assessment

Two FAST1 approaches, FAST1‐BS and FAST1‐IR, were characterized and compared with standard 5‐(3)‐3 MOLLI in terms of accuracy, precision/spatial variability, and repeatability.

Statistical Tests

Kruskal‐Wallis, Wilcoxon signed rank tests, intraclass correlation coefficient analysis, analysis of variance, Student's t‐tests, Pearson correlation analysis, and Bland–Altman analysis.

Results

In simulation/phantom, FAST1‐BS, FAST1‐IR, and MOLLI had an accuracy (expressed as T₁ error) of 0.2%/4%, 6%/9%, and 4%/7%, respectively, while FAST1‐BS and FAST1‐IR had a precision penalty of 1.7/1.5 and 1.5/1.4 in comparison with MOLLI, respectively. In healthy volunteers, FAST1‐BS/FAST1‐IR/MOLLI led to different native myocardial T₁ times (1016 ± 27 msec/952 ±22 msec/987 ± 23 msec, P < 0.0001) and spatial variability (66 ± 10 msec/57 ± 8 msec/46 ± 7 msec, P < 0.001). There were no statistically significant differences between all techniques for T₁ repeatability (P = 0.18). In vivo native and postcontrast myocardial T₁ times in both healthy volunteers and patients using FAST1‐BS/FAST1‐IR were highly correlated with MOLLI (Pearson correlation coefficient ≥0.93).

Data Conclusion

FAST1 enables myocardial T₁ mapping with full left ventricular coverage in three separated breathholds. In comparison with MOLLI, FAST1 yield a 5‐fold increase of spatial coverage, limited penalty of T₁ precision/spatial variability, no significant difference of T₁ repeatability, and highly correlated T₁ times. FAST1‐IR provides improved T₁ precision/spatial variability but reduced accuracy when compared with FAST1‐BS.

Level of Evidence: 1

Technical Efficacy: Stage 3

J. Magn. Reson. Imaging 2020;51:492–504.