Extended Phase Graph Research Articles

Improving Accuracy and Reproducibility of Cartilage T2 Mapping in the OAI Dataset Through Extended Phase Graph Modeling.

The Osteoarthritis Initiative (OAI) collected extensive imaging data, including Multi-Echo Spin-Echo (MESE) sequences for measuring knee cartilage T2 relaxation times. Mono-exponential models are used in the OAI for T2 fitting, which neglects stimulated echoes and B1 inhomogeneities. Extended Phase Graph (EPG) modeling addresses these limitations but has not been applied to the OAI dataset. To assess how different fitting methods, including EPG-based and exponential-based approaches, affect the accuracy and reproducibility of cartilage T2 in the OAI dataset. Retrospective. From OAI dataset, 50 subjects, stratified by osteoarthritis (OA) severity using Kellgren-Lawrence grades (KLG), and 50 subjects without OA diagnosis during OAI duration were selected (each group: 25 females, mean ages ~61 years). 3-T, two-dimensional (2D) MESE sequence. Femoral and tibial cartilages were segmented from DESS images, subdivided into seven sub-regions, and co-registered to MESE. T2 maps were obtained using three EPG-based methods (nonlinear least squares, dictionary matching, and deep learning) and three mono-exponential approaches (linear least squares, nonlinear least squares, and noise-corrected exponential). Average T2 values within sub-regions were obtained. Pair-wise agreement among fitting methods was evaluated using the stratified subjects, while reproducibility using healthy subjects. Each method's T2 accuracy and repeatability varying signal-to-noise ratio (SNR) were assessed with simulations. Bland-Altman analysis, Lin's concordance coefficient, and coefficient of variation assessed agreement, repeatability, and reproducibility. Statistical significance was set at P-value <0.05. EPG-based methods demonstrated superior T2 accuracy (mean absolute error below 0.5 msec at SNR > 100) compared to mono-exponential methods (error > 7 msec). EPG-based approaches had better reproducibility, with limits of agreement 1.5-5 msec narrower than exponential-based methods. T2 values from EPG methods were systematically 10-17 msec lower than those from mono-exponential fitting. EPG modeling improved agreement and reproducibility of cartilage T2 mapping in subjects from the OAI dataset. 3 TECHNICAL EFFICACY: Stage 1.

Age-specific optimization of the T2-weighted MRI contrast in infant and toddler brain.

In 0-2-year-old brains, the T2-weighted (T2w) contrast between white matter (WM) and gray matter (GM) is weaker compared with that in adult brains and rapidly changes with age. This study aims to design variable-flip-angle (VFA) trains in 3D fast spin-echo sequence that adapt to the dynamically changing relaxation times to improve the contrast in the T2w images of the developing brains. T1 and T2 relaxation times in 0-2-year-old brains were measured, and several age groups were defined according to the age-dependent pattern of T2 values. Based on the static pseudo-steady-state theory and the extended phase graph algorithm, VFA trains were designed for each age group to maximize WM/GM contrast, constrained by the maximum specific absorption rate and overall signal intensity. The optimized VFA trains were compared with the default one used for adult brains based on the relative contrast between WM and GM. Dice coefficient was used to demonstrate the advantage of contrast-improved images as inputs for automatic tissue segmentation in infant brains. The 0-2-year-old pool was divided into groups of 0-8 months, 8-12 months, and 12-24 months. The optimal VFA trains were tested in each age group in comparison with the default sequence. Quantitative analyses demonstrated improved relative contrasts in infant and toddler brains by 1.5-2.3-fold at different ages. The Dice coefficient for contrast-optimized images was improved compared with default images (p < 0.001). An effective strategy was proposed to improve the 3D T2w contrast in 0-2-year-old brains.

Myo-regressor Deep Informed Neural NetwOrk (Myo-DINO) for fast MR parameters mapping in neuromuscular disorders

Magnetic Resonance (MR) parameters mapping in muscle Magnetic Resonance Imaging (mMRI) is predominantly performed using pattern recognition-based algorithms, which are characterised by high computational costs and scalability issues in the context of multi-parametric mapping.Deep Learning (DL) has been demonstrated to be a robust and efficient method for rapid MR parameters mapping. However, its application in mMRI domain to investigate Neuromuscular Disorders (NMDs) has not yet been explored. In addition, data-driven DL models suffered in interpretation and explainability of the learning process. We developed a Physics Informed Neural Network called Myo-Regressor Deep Informed Neural NetwOrk (Myo-DINO) for efficient and explainable Fat Fraction (FF), water-T2 (wT2) and B1 mapping from a cohort of NMDs.A total of 2165 slices (232 subjects) from Multi-Echo Spin Echo (MESE) images were selected as the input dataset for which FF, wT2,B1 ground truth maps were computed using the MyoQMRI toolbox. This toolbox exploits the Extended Phase Graph (EPG) theory with a two-component model (water and fat signal) and slice profile to simulate the signal evolution in the MESE framework. A customized U-Net architecture was implemented as the Myo-DINO architecture. The squared L2 norm loss was complemented by two distinct physics models to define two ‘Physics-Informed’ loss functions: Cycling Loss 1 embedded a mono-exponential model to describe the relaxation of water protons, while Cycling Loss 2 incorporated the EPG theory with slice profile to model the magnetization dephasing under the effect of gradients and RF pulses. The Myo-DINO was trained with the hyperparameter value of the 'Physics-Informed' component held constant, i.e. λmodel = 1, while different hyperparameter values (λcnn) were applied to the squared L2 norm component in both the cycling loss. In particular, hard (λcnn=10), normal (λcnn=1) and self-supervised (λcnn=0) constraints were applied to gradually decrease the impact of the squared L2 norm component on the ‘Physics Informed’ term during the Myo-DINO training process.Myo-DINO achieved higher performance with Cycling Loss 2 for FF, wT2 and B1 prediction. In particular, high reconstruction similarity and quality (Structural Similarity Index > 0.92, Peak Signal to Noise ratio > 30.0 db) and small reconstruction error (Normalized Root Mean Squared Error < 0.038) to the reference maps were shown with self-supervised weighting of the Cycling Loss 2. In addition muscle-wise FF, wT2 and B1 predicted values showed good agreement with the reference values. The Myo-DINO has been demonstrated to be a robust and efficient workflow for MR parameters mapping in the context of mMRI. This provides preliminary evidence that it can be an effective alternative to the reference post-processing algorithm. In addition, our results demonstrate that Cycling Loss 2, which incorporates the Extended Phase Graph (EPG) model, provides the most robust and relevant physical constraints for Myo-DINO in this multi-parameter regression task. The use of Cycling Loss 2 with self-supervised constraint improved the explainability of the learning process because the network acquired domain knowledge solely in accordance with the assumptions of the EPG model.

Highly accelerated parameter mapping using model-based alternating reconstruction coupling fitting

Objective. A model-based alternating reconstruction coupling fitting, termed Model-based Alternating Reconstruction COupling fitting (MARCO), is proposed for accurate and fast magnetic resonance parameter mapping. Approach. MARCO utilizes the signal model as a regularization by minimizing the bias between the image series and the signal produced by the suitable signal model based on iteratively updated parameter maps when reconstructing. The technique can incorporate prior knowledge of both image series and parameters by adding sparsity constraints. The optimization problem is decomposed into three subproblems and solved through three alternating steps involving reconstruction and nonlinear least-square fitting, which can produce both contrast-weighted images and parameter maps simultaneously. Main results. The algorithm is applied to T 2 mapping with extended phase graph algorithm integrated and validated on undersampled multi-echo spin-echo data from both phantom and in vivo sources. Compared with traditional compressed sensing and model-based methods, the proposed approach yields more accurate T 2 maps with more details at high acceleration factors. Significance. The proposed method provides a basic framework for quantitative MR relaxometry, theoretically applicable to all quantitative MR relaxometry. It has the potential to improve the diagnostic utility of quantitative imaging techniques.

Fast and High-Resolution T2 Mapping Based on Echo Merging Plus k-t Undersampling with Reduced Refocusing Flip Angles (TEMPURA) as Methods for Human Renal MRI.

To develop a highly accelerated multi-echo spin-echo method, TEMPURA, for reducing the acquisition time and/or increasing spatial resolution for kidney T2 mapping. TEMPURA merges several adjacent echoes into one k-space by either combining independent echoes or sharing one echo between k-spaces. The combined k-space is reconstructed based on compressed sensing theory. Reduced flip angles are used for the refocusing pulses, and the extended phase graph algorithm is used to correct the effects of indirect echoes. Two sequences were developed: a fast breath-hold sequence; and a high-resolution sequence. The performance was evaluated prospectively on a phantom, 16 healthy subjects, and two patients with different types of renal tumors. The fast TEMPURA method reduced the acquisition time from 3-5 min to one breath-hold (18 s). Phantom measurements showed that fast TEMPURA had a mean absolute percentage error (MAPE) of 8.2%, which was comparable to a standardized respiratory-triggered sequence (7.4%), but much lower than a sequence accelerated by purely k-t undersampling (21.8%). High-resolution TEMPURA reduced the in-plane voxel size from 3 × 3 to 1 × 1 mm2, resulting in improved visualization of the detailed anatomical structure. In vivo T2 measurements demonstrated good agreement (fast: MAPE = 1.3%-2.5%; high-resolution: MAPE = 2.8%-3.3%) and high correlation coefficients (fast: R = 0.85-0.98; high-resolution: 0.82-0.96) with the standardized method, outperforming k-t undersampling alone (MAPE = 3.3-4.5%, R = 0.57-0.59). TEMPURA provides fast and high-resolution renal T2 measurements. It has the potential to improve clinical throughput and delineate intratumoral heterogeneity and tissue habitats at unprecedented spatial resolution.

Accelerated 3D multi-echo spin-echo sequence with a subspace constrained reconstruction for whole mouse brain mapping.

To accelerate whole-brain quantitative mapping in preclinical imaging setting. A three-dimensional (3D) multi-echo spin echo sequence was highly undersampled with a variable density Poisson distribution to reduce the acquisition time. Advanced iterative reconstruction based on linear subspace constraints was employed to recover high-quality raw images. Different subspaces, generated using exponential or extended-phase graph (EPG) simulations or from low-resolution calibration images, were compared. The subspace dimension was investigated in terms of precision. The method was validated on a phantom containing a wide range of and was then applied to monitor metastasis growth in the mouse brain at 4.7T. Image quality and estimation were assessed for 3 acceleration factors (6/8/10). The EPG-based dictionary gave robust estimations of a large range of . A subspace dimension of 6 was the best compromise between precision and image quality. Combining the subspace constrained reconstruction with a highly undersampled dataset enabled the acquisition of whole-brain maps, the detection and the monitoring of metastasis growth of less than 500 . Subspace-based reconstruction is suitable for 3D mapping. This method can be used to reach an acceleration factor up to 8, corresponding to an acquisition time of 25 min for an isotropic 3D acquisition of 156 m on the mouse brain, used here for monitoring metastases growth.

A deep learning approach for fast muscle water T2 mapping with subject specific fat T2 calibration from multi-spin-echo acquisitions.

This work presents a deep learning approach for rapid and accurate muscle water T2 with subject-specific fat T2 calibration using multi-spin-echo acquisitions. This method addresses the computational limitations of conventional bi-component Extended Phase Graph fitting methods (nonlinear-least-squares and dictionary-based) by leveraging fully connected neural networks for fast processing with minimal computational resources. We validated the approach through in vivo experiments using two different MRI vendors. The results showed strong agreement of our deep learning approach with reference methods, summarized by Lin's concordance correlation coefficients ranging from 0.89 to 0.97. Further, the deep learning method achieved a significant computational time improvement, processing data 116 and 33 times faster than the nonlinear least squares and dictionary methods, respectively. In conclusion, the proposed approach demonstrated significant time and resource efficiency improvements over conventional methods while maintaining similar accuracy. This methodology makes the processing of water T2 data faster and easier for the user and will facilitate the utilization of the use of a quantitative water T2 map of muscle in clinical and research studies.

An extended phase graph-based framework for DANTE-SPACE simulations including physiological, temporal, and spatial variations.

The delay alternating with nutation for tailored excitation (DANTE)-sampling perfection with application-optimized contrasts (SPACE) sequence facilitates 3D intracranial vessel wall imaging with simultaneous suppression of blood and CSF. However, the achieved image contrast depends closely on the selected sequence parameters, and the clinical use of the sequence is limited in vivo by observed signal variations in the vessel wall, CSF, and blood. This paper introduces a comprehensive DANTE-SPACE simulation framework, with the aim of providing a better understanding of the underlying contrast mechanisms and facilitating improved parameter selection and contrast optimization. An extended phase graph formalism was developed for efficient spin ensemble simulation of the DANTE-SPACE sequence. Physiological processes such as pulsatile flow velocity variation, varying flow directions, intravoxel velocity variation, diffusion, and effects were included in the framework to represent the mechanisms behind the achieved signal levels accurately. Intravoxel velocity variation improved temporal stability and robustness against small velocity changes. Time-varying pulsatile velocity variation affected CSF simulations, introducing periods of near-zero velocity and partial rephasing. Inclusion of diffusion effects was found to substantially reduce the CSF signal. Blood flow trajectory variations had minor effects, but differences along the trajectory reduced DANTE efficiency in low- areas. Introducing low-velocity pulsatility of both CSF and vessel wall helped explain the in vivo observed signal heterogeneity in both tissue types. The presented simulation framework facilitates a more comprehensive optimization of DANTE-SPACE sequence parameters. Furthermore, the simulation framework helps to explain observed contrasts in acquired data.

Optimization of flip angle and radiofrequency pulse phase to maximize steady-state magnetization in three-dimensional missing pulse steady-state free precession.

Missing pulse (MP) steady-state free precession (SSFP) is a magnetic resonance imaging (MRI) pulse sequence that is highly tolerant to the magnetic field inhomogeneity. In this study, optimal flip angle and radiofrequency (RF) phase scheduling in three-dimensional (3D) MP-SSFP is introduced to maximize the steady-state magnetization while keeping broadband excitation to cover widely distributed frequencies generated by inhomogeneous magnetic fields. Numerical optimization based on extended phase graph (EPG) simulation was performed to maximize the MP-SSFP steady-state magnetization. To limit the specific absorption rate (SAR) associated with the broadband excitation in 3D MP-SSFP, SAR constraint was introduced in the numerical optimization. Optimized flip angle and RF phase settings were experimentally tested by introducing a linear inhomogeneous magnetic field in a range of 10-20 mT/m and using a phantom with known T1/T2 relaxation and diffusion parameters at 3 T. The experimental results were validated through comparisons with EPG simulation. Image contrasts and molecular diffusion effects were investigated in in vivo human brain imaging with 3D MP-SSFP with the optimal flip angle and RF phase settings. In the phantom measurements, the optimal flip angle and RF phase settings improved the MP-SSFP steady-state magnetization/signal-to-noise ratio by up to 41% under the fixed SAR conditions, which matched well with EPG simulation results. In vivo brain imaging with the optimal RF pulse settings provided T2-like image contrasts. Diffusion effects were relatively minor with the linear inhomogeneous field of 10-20 mT/m for white and gray matter, but cerebrospinal fluid showed conspicuous signal intensity attenuation as the linear inhomogeneous field increased. Numerical optimization achieved significant improvement in the steady-state magnetization in MP-SSFP compared with the RF pulse settings used in previous studies. The proposed flip angle and RF phase optimization is promising to improve 3D MP-SSFP image quality for MRI in inhomogeneous magnetic fields.

Pushing MP2RAGE boundaries: Ultimate time-efficient parameterization combined with exhaustive T1 synthetic contrasts.

MP2RAGE parameter optimization is redefined to allow more time-efficient MR acquisitions, whereas the T1 -based synthetic imaging framework is used to obtain on-demand T1 -weighted contrasts. Our aim was to validate this concept on healthy volunteers and patients with multiple sclerosis, using plug-and-play parallel-transmission brain imaging at 7 T. A "time-efficient" MP2RAGE sequence was designed with optimized parameters including TI and TR set as small as possible. Extended phase graph formalism was used to set flip-angle values to maximize the gray-to-white-matter contrast-to-noise ratio (CNR). Several synthetic contrasts (UNI, EDGE, FGATIR, FLAWSMIN , FLAWSHCO ) were generated online based on the acquired T1 maps. Experimental validation was performed on 4 healthy volunteers at various spatial resolutions. Clinical applicability was evaluated on 6 patients with multiple sclerosis, scanned with both time-efficient and conventional MP2RAGE parameterizations. The proposed time-efficient MP2RAGE protocols reduced acquisition time by 40%, 30%, and 19% for brain imaging at (1 mm)3 , (0.80 mm)3 and (0.65 mm)3 , respectively, when compared with conventional parameterizations. They also provided all synthetic contrasts and comparable contrast-to-noise ratio on UNI images. The flexibility in parameter selection allowed us to obtain a whole-brain (0.45 mm)3 acquisition in 19 min 56 s. On patients with multiple sclerosis, a (0.67 mm)3 time-efficient acquisition enhanced cortical lesion visualization compared with a conventional (0.80 mm)3 protocol, while decreasing the scan time by 15%. The proposed optimization, associated with T1 -based synthetic contrasts, enabled substantial decrease of the acquisition time or higher spatial resolution scans for a given time budget, while generating all typical brain contrasts derived from MP2RAGE.

Stochastic-offset-enhanced restricted slice excitation and 180° refocusing designs with spatially non-linear ΔB0 shim array fields.

Developing a general framework with a novel stochastic offset strategy for the design of optimized RF pulses and time-varying spatially non-linear ΔB0 shim array fields for restricted slice excitation and refocusing with refined magnetization profiles within the intervals of the fixed voxels. Our framework uses the decomposition property of the Bloch equations to enable joint design of RF-pulses and shim array fields for restricted slice excitation and refocusing with auto-differentiation optimization. Bloch simulations are performed independently on orthogonal basis vectors, Mx, My, and Mz, which enables designs for arbitrary initial magnetizations. Requirements for refocusing pulse designs are derived from the extended phase graph formalism obviating time-consuming sub-voxel isochromatic simulations to model the effects of crusher gradients. To refine resultant slice-profiles because of voxelwise optimization functions, we propose an algorithm that stochastically offsets spatial points at which loss is computed during optimization. We first applied our proposed design framework to standard slice-selective excitation and refocusing pulses in the absence of non-linear ΔB0 shim array fields and compared them against pulses designed with Shinnar-Le Roux algorithm. Next, we demonstrated our technique in a simulated setup of fetal brain imaging in pregnancy for restricted-slice excitation and refocusing of the fetal brain. Our proposed framework for optimizing RF pulse and time-varying spatially non-linear ΔB0 shim array fields achieve high fidelity restricted-slice excitation and refocusing for fetal MRI, which could enable zoomed fast-spin-echo-MRI and other applications.

Improved gray-white matter contrast using magnetization prepared fast imaging with steady-state free precession (MP-FISP) brain imaging at 0.55 T.

To improve the gray/white matter contrast of magnetization prepared rapid gradient echo (MP-RAGE) MRI at 0.55 T by optimizing the acquisition and sequence kernel parameters. A segmented magnetization prepared rapid gradient echo prototype sequence was implemented with (MP-RAGE*) and without (MP-FISP*) radiofrequency spoiling. Optimized parameters were derived with the assistance of an extended phase graph signal simulation as a function of the relaxation times, the flip angle, the delay times, and the effective inversion time using segmentation. The resulting protocols were compared to the MP-RAGE product sequence offered by the vendor in terms of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). A tissue segmentation reproducibility study was performed on three volunteers for the product MP-RAGE and the MP-FISP*. The MP-RAGE simulation reproduced the parameters already used in the product MP-RAGE on the scanner. An average CNR improvement of 15% for the custom MP-RAGE* over the product MP-RAGE and additional 22% for the MP-FISP* over the MP-RAGE* were observed, which is in accordance with the simulation results. The total improvement, averaged over all volunteers and regions, was 41%. The reproducibility study did not yield a significant difference between MP-RAGE and MP-FISP*. We presented some easy-to-implement adjustments to the MP-RAGE sequence at 0.55 T, which can lead to an overall average improvement of 41% in CNR.

IMPROVING ACCURACY AND REPEATABILITY OF T2 MAPPING IN THE OAI DATA THROUGH EXTEND PHASE GRAPH MODELING

IMPROVING ACCURACY AND REPEATABILITY OF T2 MAPPING IN THE OAI DATA THROUGH EXTEND PHASE GRAPH MODELING

Optimized flip angle schemes for the split acquisition offast spin-echo signals (SPLICE) sequence and application to diffusion-weighted imaging.

The diffusion-weighted SPLICE (split acquisition of fast spin-echo signals) sequence employs split-echo rapid acquisition with relaxation enhancement (RARE) readout to provide images almost free of geometric distortions. However, due to the varying T -weighting during k-space traversal, SPLICE suffers from blurring. This work extends a method for controlling the spatial point spread function (PSF) while optimizing the signal-to-noise ratio (SNR) achieved by adjusting the flip angles in the refocusing pulse train of SPLICE. An algorithm based on extended phase graph (EPG) simulations optimizes the flip angles by maximizing SNR for a flexibly chosen predefined target PSF that describes the desired k-space density weighting and spatial resolution. An optimized flip angle scheme and a corresponding post-processing correction filter which together achieve the target PSF was tested by healthy subject brain imaging using a clinical 1.5 T scanner. Brain images showed a clear and consistent improvement over those obtained with a standard constant flip angle scheme. SNR was increased and apparent diffusion coefficient estimates were more accurate. For a modified Hann k-space weighting example, considerable benefits resulted from acquisition weighting by flip angle control. The presented flexible method for optimizing SPLICE flip angle schemes offers improved MR image quality of geometrically accurate diffusion-weighted images that makes the sequence a strong candidate for radiotherapy planning or stereotactic surgery.

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

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. 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. 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. 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.

Rapid 3D absolute B1 + mapping using a sandwiched train presaturated TurboFLASH sequence at 7 T for the brain and heart.

To shorten the acquisition time of magnetization-prepared absolute transmit field (B1 + ) mapping known as presaturation TurboFLASH, or satTFL, to enable single breath-hold whole-heart 3D B1 + mapping. SatTFL is modified to remove the delay between the reference and prepared images (typically 5 T1 ), with matching transmit configurations for excitation and preparation RF pulses. The new method, called Sandwich,is evaluated as a 3D sequence, measuring whole-brain and gated whole-heart B1 + maps in a single breath-hold. We evaluate the sensitivity to B1 + and T1 using numerical Bloch, extended phase graph, and Monte Carlo simulations. Phantom and in vivo images were acquired in both the brain and heart using an 8-channel transmit 7 Tesla MRI system to support the simulations. A segmented satTFL with a short readout train was used as a reference. The method significantly reduces acquisition times of 3D measurements from 360 s to 20 s, in the brain, while simultaneously reducing bias in the measured B1 + due to T1 and magnetization history. The mean coefficient of variation was reduced by 81% for T1 s of 0.5-3s compared to conventional satTFL. In vivo, the reproducibility coefficient for flip angles in the range 0-130° was 4.5° for satTFL and 4.7° for our scheme, significantly smaller than for a short TR satTFL sequence, which was 12°. The 3D sequence measured B1 + maps of the whole thorax in 26 heartbeats. Our adaptations enable faster B1 + mapping, with minimal T1 sensitivity and lower sensitivity to magnetization history, enabling single breath-hold whole-heart absolute B1 + mapping.

Myelin water fraction mapping from multiple echo spin echoes and an independent B1+ map

PurposeMyelin water fraction (MWF) is often obtained from a multiple echo spin echo (MESE) sequence using multi‐component T2 fitting with non‐negative least squares. This process fits many unknowns including B1 + to produce a T2 spectrum for each voxel. Presented is an alternative using a rapid B1 + mapping sequence to supply B1 + for the MWF fitting procedure.MethodsEffects of B1 + errors on MWF calculations were modeled for 2D and 3D MESE using Bloch and extended phase graph simulations, respectively. Variations in SNR and relative refocusing widths were tested. Human brain experiments at 3 T used 2D MESE and an independent B1 + map. MWF maps were produced with the standard approach and with the use of the independent B1 + map. Differences in B1 + and mean MWF in specific brain regions were compared.ResultsFor 2D MESE, MWF with the standard method was strongly affected by B1 + misestimations arising from limited SNR and response asymmetry around 180°, which decreased with increasing relative refocusing width. Using an independent B1 + map increased mean MWF and decreased coefficient of variation. Notable differences in vivo in 2D MESE were in areas of high B1 + such as thalamus and splenium where mean MWF increased by 88% and 31%, respectively (P < 0.001). Simulations also demonstrated the advantages of this approach for 3D MESE when SNR is <500.ConclusionFor 2D MESE, because of increased complexity of decay curves and limited SNR, supplying B1 + improves MWF results in peripheral and central brain regions where flip angles differ substantially from 180°.

T2 quantification in brain using 3D fast spin‐echo imaging with long echo trains

PurposeThree‐dimensional fast spin‐echo (FSE) sequences commonly use very long echo trains (>64 echoes) and severely reduced refocusing angles. They are increasingly used in brain exams due to high, isotropic resolution and reasonable scan time when using long trains and short interecho spacing. In this study, T 2 quantification in 3D FSE is investigated to achieve increased resolution when comparing with established 2D (proton‐density dual‐echo and multi‐echo spin‐echo) methods.MethodsThe FSE sequence design was explored to use long echo trains while minimizing T 2 fitting error and maintaining typical proton density and T 2‐weighted contrasts. Constant and variable flip angle trains were investigated using extended phase graph and Bloch equation simulations. Optimized parameters were analyzed in phantom experiments and validated in vivo in comparison to 2D methods for eight regions of interest in brain, including deep gray‐matter structures and white‐matter tracts.ResultsPhantom and healthy in vivo brain T 2 measurements showed that optimized variable echo‐train 3D FSE performs similarly to previous 2D methods, while achieving three‐fold‐higher slice resolution, evident visually in the 3D T 2 maps. Optimization resulted in better T 2 fitting and compared well with standard multi‐echo spin echo (within the 8‐ms confidence limits defined based on Bland‐Altman analysis).Conclusion T 2 mapping using 3D FSE with long echo trains and variable refocusing angles provides T 2 accuracy in agreement with 2D methods with additional high‐resolution benefits, allowing isotropic views while avoiding incidental magnetization transfer effects. Consequently, optimized 3D sequences should be considered when choosing T 2 mapping methods for high anatomic detail.

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.

A multi-inversion-recovery magnetic resonance fingerprinting for multi-compartment water mapping

PurposeThis study aimed at introducing short-T1/T2 compartment to MR fingerprinting (MRF) at 3 T. Water that is bound to myelin macromolecules have significantly shorter T1 and T2 than free water and can be distinguished from free water by multi-compartment analysis. MethodsWe developed a new multi-inversion-recovery (mIR) water mapping-MRF based on an unbalanced steady-state coherent sequence (FISP). mIR pulses with an interval of 400 or 500 repetition times (TRs) were inserted into the conventional FISP MRF sequence. Data from our proposed mIR MRF was used to quantify different compartments, including myelin water, gray matter free water, and white matter free water, of brain water by virtue of the iterative non-negative least square (NNLS) with reweighting. Three healthy volunteers were scanned with mIR MRF on a clinical 3 T MRI. ResultsUsing an extended phase graph simulation, we found that our proposed mIR scheme with four IR pulses allowed differentiation between short and long T1/T2 components. For in vivo experiments, we achieved the quantification of myelin water, gray matter water, and white matter water at an image resolution of 1.17 × 1.17 × 5 mm3/pixel. As compared to the conventional MRF technique with single IR, our proposed mIR improved the detection of myelin water content. In addition, mIR MRF using spiral-in/out trajectory provided a higher signal level compared with that with spiral-out trajectory. Myelin water quantification using mIR MRF with 4 IR and 5 IR pulses were qualitatively similar. Meanwhile, 5 IR MRF showed fewer artifacts in myelin water detection. ConclusionWe developed a new mIR MRF sequence for the rapid quantification of brain water compartments.