B1 Mapping Research Articles

Spiral 3DREAM sequence for fast whole-brain B1 mapping.

This work demonstrates a new variant of the 3DREAM sequence for whole-brain mapping employing a three-dimensional (3D) stack-of-spirals readout. The spiral readout reduces the echo train length after the STEAM preparation in order to overcome the significant blurring in STE* images due to the decreasing STE* signal with each excitation pulse. The 3DREAM sequence rapidly acquires two contrasts to calculate whole-brain flip angle maps. In the proposed spiral 3DREAM sequence, the Cartesian readout scheme is replaced by an accelerated 3D stack-of-spirals readout with a CAIPIRINHA sampling scheme. Phantom experiments were conducted to compare flip angle maps of the spiral 3DREAM sequence to a Cartesian 3DREAM sequence, an actual flip-angle-imaging (AFI) sequence, the dual-angle method, and the Bloch-Siegert shift method. Afterwards, the results were validated in vivo acquiring flip angle maps from five subjects. Flip angle maps of the spiral 3DREAM sequences showed high agreement with the reference methods both in phantom and in vivo experiments. Blurring in STE* images and flip angle maps was reduced compared to the Cartesian 3DREAM sequence. The spiral 3DREAM sequence utilizes a fast readout minimizing the echo train length of the imaging train. This reduces blurring in STE* images as well as the total acquisition time and increases the effective resolution of maps.

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.

Quantitative ultrashort echo time MR imaging of knee osteochondral junction: An ex vivo feasibility study.

Compositional changes can occur in the osteochondral junction (OCJ) during the early stages and progressive disease evolution of knee osteoarthritis (OA). However, conventional magnetic resonance imaging (MRI) sequences are not able to image these regions efficiently because of the OCJ region's rapid signal decay. The development of new sequences able to image and quantify OCJ region is therefore highly desirable. We developed a comprehensive ultrashort echo time (UTE) MRI protocol for quantitative assessment of OCJ region in the knee joint, including UTE variable flip angle technique for T1 mapping, UTE magnetization transfer (UTE-MT) modeling for macromolecular proton fraction (MMF) mapping, UTE adiabatic T1ρ (UTE-AdiabT1ρ) sequence for T1ρ mapping, and multi-echo UTE sequence for T2* mapping. B1 mapping based on the UTE actual flip angle technique was utilized for B1 correction in T1, MMF, and T1ρ measurements. Ten normal and one abnormal cadaveric human knee joints were scanned on a 3T clinical MRI scanner to investigate the feasibility of OCJ imaging using the proposed protocol. Volumetric T1, MMF, T1ρ, and T2* maps of the OCJ, as well as the superficial and full-thickness cartilage regions, were successfully produced using the quantitative UTE imaging protocol. Significantly lower T1, T1ρ, and T2* relaxation times were observed in the OCJ region compared with those observed in both the superficial and full-thickness cartilage regions, whereas MMF showed significantly higher values in the OCJ region. In addition, all four UTE biomarkers showed substantial differences in the OCJ region between normal and abnormal knees. These results indicate that the newly developed 3D quantitative UTE imaging techniques are feasible for T1, MMF, T1ρ, and T2* mapping of knee OCJ, representative of a promising approach for the evaluation of compositional changes in early knee OA.

Fast and motion-robust saturation transfer MRI with inherent B0 correction using rosette trajectories and compressed sensing.

To implement rosette readout trajectories with compressed sensing reconstruction for fast and motion-robust CEST and magnetization transfer contrast imaging with inherent correction of B0 inhomogeneity. A pulse sequence was developed for fast saturation transfer imaging using a stack of rosette trajectories with a higher sampling density near the k-space center. Each rosette lobe was segmented into two halves to generate dual-echo images. B0 inhomogeneities were estimated using the phase difference between the images and corrected subsequently. The rosette-based imaging was evaluated in comparison to a fully sampled Cartesian trajectory and demonstrated on CEST phantoms (creatine solutions and egg white) and healthy volunteers at 3 T. Compared with the conventional Cartesian acquisition, compressed sensing reconstructed rosette images provided image quality with overall higher contrast-to-noise ratio and significantly faster readout time. Accurate B0 map estimation was achieved from the rosette acquisition with a negligible bias of 0.01 Hz between the rosette and dual-echo Cartesian gradient echo B0 maps, using the latter as ground truth. The water-saturation spectra (Z-spectra) and amide proton transfer weighted signals obtained from the rosette-based sequence were well preserved compared with the fully sampled data, both in the phantom and human studies. Fast, motion-robust, and inherent B0-corrected CEST and magnetization transfer contrast imaging using rosette trajectories could improve subject comfort and compliance, contrast-to-noise ratio, and provide inherent B0 homogeneity information. This work is expected to significantly accelerate the translation of CEST-MRI into a robust, clinically viable approach.

3D printing of ferromagnetic passive shims for field shaping in magnetic resonance imaging

Magnetic Resonance Imaging (MRI) often encounters image quality degradation due to magnetic field inhomogeneities. Conventional passive shimming techniques involve the manual placement of discrete magnetic materials, imposing limitations on correcting complex inhomogeneities. To overcome this, we propose a novel 3D printing method utilizing binder jetting technology to enable precise deposition of a continuous range of concentrations of ferromagnetic ink. This approach grants complete control of the magnitude of the magnetic moment within the passive shim enabling tailored corrections of B0 field inhomogeneities. By optimizing the magnetic field distribution using linear programming and an in-house written Computer-Aided Design (CAD) generation software, we printed shims with promising results in generating low spherical harmonic corrections. Experimental evaluations demonstrate feasibility of these 3D printed passive shims to induce target magnetic fields corresponding to second-order spherical harmonic, as evidenced by acquired B0 maps. The electrically insulating properties of the printed shims eliminate the risk of eddy currents and heating, thus ensuring safety. The dimensional fabrication accuracy of the printed shims surpasses previous methods, enabling more precise and localized correction of subject-specific inhomogeneities. The findings highlight the potential of binder-jetted 3D printed passive shims in MRI shimming as a versatile and efficient solution for fabricating passive shims, with the potential to enhance the quality of MRI imaging while also being applicable to other types of Magnetic Resonance systems.

Lipid removal in deuterium metabolic imaging (DMI) using spatial prior knowledge

Abstract. Deuterium metabolic imaging (DMI) is a novel method to generate spatial maps depicting dynamic metabolism of deuterated substrates, such as [6,6′-2H2]-glucose, and their metabolic products, like 2H-lactate. While DMI acquisition methods are simple and robust, DMI processing still requires expert user interaction, e.g., in the removal of extracranial natural abundance 2H lipid signals that interfere with metabolism-linked 2H-lactate formation. Here we pursue the use of MRI-based spatial prior knowledge on brain and non-brain/skull locations to provide robust and objective lipid removal. Magnetic field heterogeneity was accounted for using DMI-derived surrogate B0 and B1 maps, as well as through subdivision of the skull region into smaller compartments. Adequate lipid removal with an average suppression of 90.5 ± 11.4 % is achieved on human brain in vivo without perturbation of the metabolic profile in brain voxels, thereby allowing for the generation of distinct and reliable metabolic maps for patients with brain tumors.

Phase-sensitive deep reconstruction method for rapid multiparametric MR fingerprinting and quantitative susceptibility mapping in the brain

IntroductionThis study explores the potential of Magnetic Resonance Fingerprinting (MRF) with a novel Phase-Sensitivity Deep Reconstruction Network (PS-DRONE) for simultaneous quantification of T1, T2, Proton Density, B1+, phase and quantitative susceptibility mapping (QSM). MethodsData were acquired at 3 T in vitro and in vivo using an optimized EPI-based MRF sequence. Phantom experiments were conducted using a standardized phantom for T1 and T2 maps and a custom-made agar-based gadolinium phantom for B1 and QSM maps. In vivo experiments included five healthy volunteers and one patient diagnosed with brain metastasis. PSDRONE maps were compared to reference maps obtained through standard imaging sequences. ResultsTotal scan time was 2 min for 32 slices and a resolution of [1 mm, 1 mm, 4.5 mm]. The reconstruction of T1, T2, Proton Density, B1+ and phase maps were reconstructed within 1 s. In the phantoms, PS-DRONE analysis presented accurate and strongly correlated T1 and T2 maps (r = 0.99) compared to the reference maps. B1 maps from PS-DRONE showed slightly higher values, though still correlated (r = 0.6) with the reference. QSM values showed a small bias but were strongly correlated (r = 0.99) with reference data. In the in vivo analysis, PS-DRONE-derived T1 and T2 values for gray and white matter matched reference values in healthy volunteers. PS-DRONE B1 and QSM maps showed strong correlations with reference values. ConclusionThe PS-DRONE network enables concurrent acquisition of T1, T2, PD, B1+, phase and QSM maps, within 2 min of acquisition time and 1 s of reconstruction time.

Free-breathing abdominal chemical exchange saturation transfer imaging using water presaturation and respiratory gating at 3.0 T.

Free-breathing abdominal chemical exchange saturation transfer (CEST) has great potential for clinical application, but its technical implementation remains challenging. This study aimed to propose and evaluate a free-breathing abdominal CEST sequence. The proposed sequence employed respiratory gating (ResGat) to synchronize the data acquisition with respiratory motion and performed a water presaturation module before the CEST saturation to abolish the influence of respiration-induced repetition time variation. In vivo experiments were performed to compare different respiratory motion-control strategies and B0 offset correction methods, and to evaluate the effectiveness and necessity of the quasi-steady-state (QUASS) approach for correcting the influence of the water presaturation module on CEST signal. ResGat with a target expiratory phase of 0.5 resulted in a higher structural similarity index and a lower coefficient of variation on consecutively acquired CEST S0 images than breath-holding (BH) and respiratory triggering (all p < 0.05). B0 maps derived from the abdominal CEST dataset itself were more stable for B0 correction, compared with the separately acquired B0 maps by a dual-echo time scan and B0 maps derived from the water saturation shift referencing approach. Compared with BH, ResGat yielded more homogeneous magnetization transfer ratio asymmetry maps at 3.5 ppm (standard deviation: 3.96% vs. 3.19%, p = 0.036) and a lower mean squared difference between scan and rescan (27.52‱ vs. 16.82‱, p = 0.004). The QUASS approach could correct the water presaturation-induced CEST signal change, but its necessity for in vivo scanning needs further verification. The proposed free-breathing abdominal CEST sequence using ResGat had an acquisition efficiency of approximately four times that using BH. In conclusion, the proposed free-breathing abdominal CEST sequence using ResGat and water presaturation has a higher acquisition efficiency and image quality than abdominal CEST using BH.

The Minimum Admissible Detuning Efficiency of MRI Receive-Only Surface Coils.

The minimum admissible detuning efficiency (DE) of a receive coil is an essential parameter for coil designers. A receive coil with inefficient detuning leads to inhomogeneous B1 during excitation. Previously proposed criteria for quantifying the DE rely on indirect measurements and are difficult to implement. To present an alternative method to quantify the DE of receive-only surface coils. Theoretical study supported by simulations and phantom experiments. Uniform spherical (100 mm diameter) and cylindrical (66 mm diameter) phantoms. Dual repetition time B1 mapping sequence at 1.5T, and Bloch-Siegert shift B1 mapping sequence at 3.0T. One non-planar (80 × 43 mm2) and two planar (40 and 57 mm diameter) surface coils were built. Theoretical analysis was performed to determine the minimum DE required to avoid B1 distortions. Experimental B1 maps were acquired for the non-planar and planar surface coils at both 1.5T and 3.0T and visually compared with simulated B1 maps to assess the validity of the theoretical analysis. None. Based on the theoretical analysis, the proposed minimum admissible DE, defined as DEthr = 20 Log (Q) + 13 dB, depended only on the quality factor (Q) of the coil and was independent of coil area and field strength. Simulations and phantom experiments showed that when the DE was higher than this minimum threshold level, the B1 field generated by the transmission coil was not modified by the receive coil. The proposed criterion for assessing the DE is simple to measure, and does not depend on the area of the coil or on the magnetic field strength, up to 3T. Experimental and simulated B1 maps confirmed that detuning efficiencies above the theoretically derived minimal admissible DE resulted in a non-distorted B1 field. 2 TECHNICAL EFFICACY: Stage 1.

Predicting dynamic, motion-related changes in B0 field inthe brain at a 7T MRI using a subject-specific fine-trainedU-net.

Subject movement during the MR examination is inevitable and causes not only image artifacts but also deteriorates the homogeneity of the main magnetic field (B0 ), which is a prerequisite for high quality data. Thus, characterization of changes to B0 , for example induced by patient movement, is important for MR applications that are prone to B0 inhomogeneities. We propose a deep learning based method to predict such changes within the brain from the change of the head position to facilitate retrospective or even real-time correction. A 3D U-net was trained on in vivo gradient-echo brain 7T MRI data. The input consisted of B0 maps and anatomical images at an initial position, and anatomical images at a different head position (obtained by applying a rigid-body transformation on the initial anatomical image). The output consisted of B0 maps at the new head positions. We further fine-trained the network weights to each subject by measuring a limited number of head positions of the given subject, and trained the U-net with these data. Our approach was compared to established dynamic B0 field mapping via interleaved navigators, which suffer from limited spatial resolution and the need for undesirable sequence modifications. Qualitative and quantitative comparison showed similar performance between an interleaved navigator-equivalent method and proposed method. It is feasible to predict B0 maps from rigid subject movement and, when combined with external tracking hardware, this information could be used to improve the quality of MR acquisitions without the use of navigators.

Simultaneous Arterial and Venous Imaging Using 3D Quantitative Parameter Mapping.

To increase the number of images that can be acquired in MR examinations using quantitative parameters, we developed a method for obtaining arterial and venous images with mapping of proton density (PD), RF inhomogeneity (B1), longitudinal relaxation time (T1), apparent transverse relaxation time (T2*), and magnetic susceptibility through calculation, all with the same spatial resolution. The proposed method uses partially RF-spoiled gradient echo sequences to obtain 3D images of a subject with multiple scan parameters. The PD, B1, T1, T2*, and magnetic susceptibility maps are estimated using the quantification method we previously developed. Arterial images are obtained by adding images using optimized weights to emphasize the arteries. A morphology filter is used to obtain venous images from the magnetic susceptibility maps. For evaluation, images obtained from four out of five healthy volunteers were used to optimize the weights used in the arterial-image calculation, and the optimized weights were applied to the images from the fifth volunteer to obtain an arterial image. Arterial images of the five volunteers were calculated using the leave-one-out method, and the contrast between the arterial and background regions defined using the reference time-of-flight (TOF) method was evaluated using the area under the receiver operation characteristic curve (AUC). The contrast between venous and background regions defined by a reference quantitative susceptibility mapping (QSM) method was also evaluated for the venous image. The AUC to discriminate blood vessels and background using the proposed method was 0.905 for the arterial image and 0.920 for the venous image. The results indicate that the arterial images and venous images have high signal intensity at the same region as determined from the reference TOF and QSM methods, demonstrating the possibility of acquiring vasculature images with quantitative parameter mapping through calculation in an integrated manner.

In vivo lymph node CEST-Dixon MRI in breast cancer patients with metastatic lymph node involvement.

Axillary lymph nodes (LNs) often present a reservoir for metastatic breast cancer, yet metastatic LN involvement cannot be discerned definitively using diagnostic imaging. This study investigated whether in vivo CEST may discriminate LNs with versus without metastatic involvement. 3T MRI was performed in patients with breast cancer before clinically-indicated mastectomy or lumpectomy with LN removal, after which LN metastasic involvement was determined using histological evaluation. Non-contrast anatomical imaging, as well as B0 and B1 field maps, were acquired in sequence with three-point CEST-Dixon (3D turbo-gradient-echo; factor = 25; TR/TE1/ΔTE = 851/1.35/1.1 ms; spatial-resolution = 2.5 × 2.5 × 6 mm; slices = 10; four sinc-gauss pulses with duty-cycle = 0.5, total saturation duration = 701.7 ms; B1 = 1.5 μT; saturation offsets = -5.5 to +5.5 ppm; stepsize = 0.2 ppm; scan duration = 6 min 30 s). The mean z-spectrum from LNs with (n = 20) versus without (n = 22) metastatic involvement were analyzed and a Wilcoxon rank-sum test (significance: p < 0.05) was applied to evaluate differences in B0, B1 , and magnetization transfer ratio (MTR) in differing spectral regions of known proton exchange (nuclear Overhauser effect [NOE], amide, amine, and hydroxyl) between cohorts. No difference in axillary B1 (p = 0.634) or B0 (p = 0.689) was observed between cohorts. Elevated MTR was observed for the NOE (-1.7 ppm; MTR = 0.285 ± 0.075 vs. 0.248 ± 0.039; p = 0.048), amine (+2.5 ppm; MTR = 0.284 ± 0.067 vs. 0.234 ± 0.31; p = 0.005), and hydroxyl (+1 ppm; MTR = 0.394 ± 0.075 vs. 0.329 ± 0.055; p = 0.002) protons in LNs from participants with versus without metastatic involvement. Findings are consistent with a unique metastatic LN microenvironment detectable by CEST-Dixon and suggest that CEST MRI may have potential for mapping LN metastasis non-invasively in vivo.

High resolution simulation and measurement demonstrate oscillatory spatiotemporal B0 fluctuations across the human cardiac cycle.

Functional cardiac MRI scans employing balanced steady-state free precession sequences suffer from dark band artifacts in the myocardium due to B0 inhomogeneity. We recently introduced a novel method for the theoretical derivation of B0 distributions in the human heart. This study aims to simulate the B0 distributions in the heart across the cardiac cycle using structural MR images and validate the simulations via in vivo measured cardiac phase-specific B0 maps on the same subjects at 3T. Cardiac phase-specific B0 field maps were acquired from eight healthy subjects at 3T. B0 conditions were simulated based on tissue masks created from the cardiac-phase specific structural images from the in vivo B0 map scan and anatomical images from a thoracic MRI scan, adopting our recently published approach. The simulations and in vivo measurements were compared by calculating the spatial correlation of their B0 distributions and temporal correlation of the derived spherical harmonic coefficients throughout the cardiac cycle. The spatial comparison of B0 maps between the simulation and in vivo measurement indicates an overall average correlation coefficient of 0.91 across the cardiac cycle in all subjects. Both groups show consistent high-level B0 patterns. Temporal variations of B0 conditions exhibit sinusoidal characteristics and are strongly correlated between simulation and in vivo. Theoretical simulations employing regional anatomical features were validated by direct in vivo B0 mapping in the same subjects. The spatial B0 condition throughout the cardiac cycle exhibits oscillatory characteristics due to structural distortions of cardiac motion.

A preparation pulse for fast steady state approach in Actual Flip angle Imaging.

Actual Flip angle Imaging (AFI) is a sequence used for B1 mapping, also embedded in the Variable flip angle with AFI for simultaneous estimation of T1 , B1 and equilibrium magnetization. To investigate the design of a preparation module for AFI to allow a fast approach to steady state (SS) without requiring the use of dummyacquisitions. The features of a preparation module with a B1 insensitive adiabatic pulse, spoiler gradients, and a recovery time were studied with simulations and validated via experiments and acquired with different k-space traveling strategies. The robustness of the flip angle of the preparation pulse on the acquired signal isstudied. When a 90° adiabatic pulse is used, the forthcoming can be expressed as a function of repetition times and AFI flip angle only as , where n represents the ratio between the two repetition times of AFI. The robustness of the method is demonstrated by showing that using the values further away from 90° still allows for a faster approach to SS than the use of dummypulses. The preparation module is particularly advantageous for low flip angles, as well as for AFI sequences that sample the center of the k-space early in the sequence, such as centric ordering acquisitions, and for ultrafast EPI-based AFI methods, thus allowing to reduce scanner overheadtime.

Deep learning-based local SAR prediction using B1 maps and structural MRI of the head for parallel transmission at 7 T.

To predict subject-specific local specific absorption rate (SAR) distributions of the human head for parallel transmission (pTx) systems at 7 T. Electromagnetic energy deposition in tissues is nonuniform at 7 T, and interference patterns due to individual channels of pTx systems may result in increased local SAR values, which can only be estimated with very high safety margins. We proposed, designed, and demonstrated a multichannel 3D convolutional neural network (CNN) architecture to predict local SAR maps as well as peak-spatial SAR (ps-SAR) levels. We hypothesized that utilizing a three-channel 3D CNN, in which each channel is fed by a map, a phase-reversed map, and an MR image, would improve prediction accuracies and decrease uncertainties in the predictions. We generated 10 new head-neck body models, along with 389 3D pTx MRI data having different RF shim settings, with their B1 and local SAR maps to support efforts in this field. The proposed three-channel 3D CNN predicted ps-SAR10g levels with an average overestimation error of 20%, which was better than the virtual observation points-based estimation error (i.e., 152% average overestimation). The proposed method decreased prediction uncertainties over 20% (i.e., 22.5%-17.7%) compared to other methods. A safety factor of 1.20 would be enough to avoid underestimations for the dataset generated in this work. Multichannel 3D CNN networks can be promising in predicting local SAR values and perform predictions within a second, making them clinically useful as an alternative to virtual observation points-based methods.

B1 mapping using pre-learned subspaces for quantitative brain imaging.

To develop a machine learning-based method for estimation of both transmitter and receiver B1 fields desired for correction of the B1 inhomogeneity effects in quantitative brain imaging. A subspace model-based machine learning method was proposed for estimation of B1t and B1r fields. Probabilistic subspace models were used to capture scan-dependent variations in the B1 fields; the subspace basis and coefficient distributions were learned from pre-scanned training data. Estimation of the B1 fields for new experimental data was achieved by solving a linear optimization problem with prior distribution constraints. We evaluated the performance of the proposed method for B1 inhomogeneity correction in quantitative brain imaging scenarios, including T1 and proton density (PD) mapping from variable-flip-angle spoiled gradient-echo (SPGR) data as well as neurometabolic mapping from MRSI data, using phantom, healthy subject and brain tumor patient data. In both phantom and healthy subject data, the proposed method produced high-quality B1 maps. B1 correction on SPGR data using the estimated B1 maps produced significantly improved T1 and PD maps. In brain tumor patients, the proposed method produced more accurate and robust B1 estimation and correction results than conventional methods. The B1 maps were also applied to MRSI data from tumor patients and produced improved neurometabolite maps, with better separation between pathological and normal tissues. This work presents a novel method to estimate B1 variations using probabilistic subspace models and machine learning. The proposed method may make correction of B1 inhomogeneity effects more robust in practical applications.

Optimized interferometric encoding of presaturated TurboFLASH B1 mapping for parallel transmission MRI at 7 T: Preliminary application for quantitative T1 mapping in the spinal cord.

The acquisition of accurate B1 maps is critical for parallel transmit techniques (pTx). The presaturated turboFLASH (satTFL) method has been widely used in combination with interferometric encoding to provide robust and fast B1 maps. However, typical encodings, mostly evaluated on brain, do not necessarily fit all coils and organs. In this work, we evaluated and improved the accuracy of the satTFL for cervical spine at 7 T, proposing a novel interferometric encoding optimization. The benefits of such improvements were investigated in an exploratory study of quantitative T1 mapping with pTx-MP2RAGE. Global optimization of interferometric encoding was implemented by simulating the ability of the satTFL to reconstruct B1 maps, with varying encoding and inclusion of complex noise, inside a region of interest covering the cervical spine. The performance of satTFL before and after optimization was compared to actual flip angle imaging. Optimized and non-optimized B1 maps were then used to calculate pTx pulses for MP2RAGE T1 mapping. Interferometric encoding optimization resulted in satTFL closer to actual flip angle imaging, with substantial gain of signal in regions where non-optimized satTFL could fail. T1 maps measured with non-adiabatic pTx pulses were closer to standard non-pTx results (which used adiabatic pulses) when using optimized-satTFL, with substantially lower specific absorption rate. Optimization of the satTFL interferometric encoding improves B1 maps in the spinal cord, in particular in low SNR regions. A linear correction of the satTFL was additionally shown to be required. The method was successfully used for quantitative phantom and in vivo T1 mapping, showing improved results compared to non-optimized satTFL thanks to improved pTx-pulse generation.

Open source code for the generation of digital reference objects for dynamic contrast-enhanced MRI analysis software validation.

Dynamic contrast-enhanced MR images can be analyzed through the application of a wide range of kinetic models. This process is prone to variability and a lack of standardization that can affect the measured metrics. There is a need for customized digital reference objects (DROs) for the validation of DCE-MRI software packages that undertake kinetic model analysis. DROs are currently available only for a small subset of the kinetic models commonly applied to DCE-MRI data. This work aimed to address this gap. Code was written in the MATLAB programming environment to generate customizable DROs. This modular code allows the insertion of a plug-in to describe the kinetic model to be tested. We input our generated DROs into three commercial and open-source analysis packages and assessed the agreement of kinetic model parameter values output with the 'ground-truth' values used in the DRO generation. For the five kinetic models tested, the concordance correlation coefficient values were >98%, indicating excellent agreement of the results with 'ground-truth'. Testing our DROs on three independent software packages produced concordant results, strongly suggesting our DRO generation code is correct. This implies that our DROs can be used to validate other third party software for the kinetic model analysis of DCE-MRI data. This work extends published work of others to allow customized generation of test objects for any applied kinetic model and allows the incorporation of B1 mapping into the DRO for application at higher field strengths.

Motion-resolved fat-fraction mapping with whole-heart free-running multiecho GRE and pilot tone.

To develop a free-running 3D radial whole-heart multiecho gradient echo (ME-GRE) framework for cardiac- and respiratory-motion-resolved fat fraction (FF) quantification. (NTE = 8) readouts optimized for water-fat separation and quantification were integrated within a continuous non-electrocardiogram-triggered free-breathing 3D radial GRE acquisition. Motion resolution was achieved with pilot tone (PT) navigation, and the extracted cardiac and respiratory signals were compared to those obtained with self-gating (SG). After extra-dimensional golden-angle radial sparse parallel-based image reconstruction, FF, R2 *, and B0 maps, as well as fat and water images were generated with a maximum-likelihood fitting algorithm. The framework was tested in a fat-water phantom and in 10 healthy volunteers at 1.5 T using NTE = 4 and NTE = 8 echoes. The separated images and maps were compared with a standard free-breathing electrocardiogram (ECG)-triggered acquisition. The method was validated in vivo, and physiological motion was resolved over all collected echoes. Across volunteers, PT provided respiratory and cardiac signals in agreement (r = 0.91 and r = 0.72) with SG of the first echo, and a higher correlation to the ECG (0.1% of missed triggers for PT vs. 5.9% for SG). The framework enabled pericardial fat imaging and quantification throughout the cardiac cycle, revealing a decrease in FF at end-systole by 11.4% ± 3.1% across volunteers (p < 0.0001). Motion-resolved end-diastolic 3D FF maps showed good correlation with ECG-triggered measurements (FF bias of -1.06%). A significant difference in free-running FF measured with NTE = 4 and NTE = 8 was found (p < 0.0001 in sub-cutaneous fat and p < 0.01 in pericardial fat). Free-running fat fraction mapping was validated at 1.5 T, enabling ME-GRE-based fat quantification with NTE = 8 echoes in 6:15 min.

Multislice B1 Mapping Method Using Magnetic Resonance Composite Spin Echo Sequences and Simultaneous Echo Refocusing

Radiofrequency (RF) transmit field (B1) mapping is a promising method in mitigating the B1 inhomogeneity in various magnetic resonance imaging (MRI) applications. Although several phase- or magnitude-based B1 mapping methods have been proposed, these methods often require complex modeling, long acquisition time, or specialized MRI sequences. A recently introduced simultaneous echo refocusing (SER) technique can be applied in the B1 mapping method to extend the three-dimensional (3D) spatial coverage only without long data acquisition. Therefore, in this study, a multislice B1 mapping method using composite spin echo sequences and SER techniques is proposed to obtain more accurate B1 mapping with short data acquisition time. To evaluate the performance of the proposed B1 mapping method, computational simulations were performed and compared with Morrell’s method, double angle method, and Yarnykh’s method. These results showed that the angle-to-noise ratio of the proposed B1 mapping method has wider B1 range compared to that of other B1 mapping methods. In addition, the proposed B1 mapping methods were compared to the multislice iterative signal intensity mapping method in both phantom and in vivo human experiments, and there was no remarkable difference between the two methods regarding the flip angle distribution in these experiments. Based on these results, this study demonstrated that the proposed B1 mapping method is suitable for accurately measuring B1 propagation under the condition providing reduced scan time and wider 3D coverage of B1 mapping by applying composite RF pulse and SER techniques into the phase-sensitive method.