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Purpose: To develop a method for unwrapping temporally undersampled and nonlinear gradient recalled echo (GRE) phase. Theory and Methods: Temporal unwrapping is performed as a sequential one step prediction of the echo phase, followed by a correction to the nearest integer wrap‐count. A spatio‐temporal extension of the 1D predictor corrector unwrapping (PCU) algorithm improves the prediction accuracy, and thereby maintains spatial continuity. The proposed method is evaluated using numerical phantom, physical phantom, and in vivo brain data at both 3 T and 9.4 T. The unwrapping performance is compared with the state‐of‐the‐art temporal and spatial unwrapping algorithms, and the spatio‐temporal iterative virtual‐echo based Nyquist sampled (iVENyS) algorithm. Results: Simulation results showed significant reduction in unwrapping errors at higher echoes compared with the state‐of‐the‐art algorithms. Similar to the iVENyS algorithm, the PCU algorithm was able to generate spatially smooth phase images for in vivo data acquired at 3 T and 9.4 T, bypassing the use of additional spatial unwrapping step. A key advantage over iVENyS algorithm is the superior performance of PCU algorithm at higher echoes. Conclusion: PCU algorithm serves as a robust phase unwrapping method for temporally undersampled and nonlinear GRE phase, particularly in the presence of high field gradients. [ABSTRACT FROM AUTHOR]

PurposeMany MRI sequences are sensitive to motion and its associated artifacts. The linearized geometric solution (LGS), a balanced steady-state free precession (bSSFP) off-resonance signal demodulation technique, is evaluated with respect to motion artifact resilience.Theory and methodsThe mechanism and extent of LGS motion artifact resilience is examined in simulated, flow phantom, and in vivo clinical imaging. Motion artifact correction capabilities are decoupled from susceptibility artifact correction when feasible to permit controlled analysis of motion artifact correction when comparing the LGS with standard and phase-cycle-averaged (complex sum) bSSFP imaging.ResultsSimulations reveal that the LGS demonstrates motion artifact reduction capabilities similar to standard clinical bSSFP imaging techniques, with slightly greater resilience in high SNR regions and for shorter-duration motion. Flow phantom experiments assert that the LGS reduces shorter-duration motion artifact error by ∼24%-65% relative to the complex sum, whereas reconstructions exhibit similar error reduction for constant motion. In vivo analysis demonstrates that in the internal auditory canal/orbits, the LGS was deemed to have less artifact in 24%/49% and similar artifact in 76%/51% of radiological assessments relative to the complex sum, and the LGS had less artifact in 97%/81% and similar artifact in 3%/16% of assessments relative to standard bSSFP. Only 2 of 63 assessments deemed the LGS inferior to either complex sum or standard bSSFP in terms of artifact reduction.ConclusionThe LGS provides sufficient bSSFP motion artifact resilience to permit robust elimination of susceptibility artifacts, inspiring its use in a wide variety of applications.

Purpose: To investigate the prospects of a multigradient‐echo (mGRE) acquisition for in vivo myelin water imaging at 0.55 T. Methods: Scans were performed on the brain of four healthy volunteers at 0.55 and 3 T, using a 3D mGRE sequence. The myelin water fraction (MWF) was calculated for both field strengths using a nonnegative least squares (NNLS) algorithm, implemented in the qMRLab suite. The quality of these maps as well as single‐voxel fits were compared visually for 0.55 and 3 T. Results: The obtained MWF values at 0.55 T are consistent with previously reported ones at higher field strengths. The MWF maps are a considerable improvement over the ones at 3 T. Example fits show that 0.55 T data is better described by an exponential model than 3 T data, making the assumed multi‐exponential model of the NNLS algorithm more accurate. Conclusion: This first assessment shows that mGRE myelin water imaging at 0.55 T is feasible and has the potential to yield better results than at higher fields. [ABSTRACT FROM AUTHOR]

Purpose: To propose a standardized comparison between state‐of‐the‐art open‐source fat‐water separation algorithms for proton density fat fraction (PDFF) and R2*$$ {R}_2^{\ast } $$ quantification using an open‐source multi‐language toolbox. Methods: Eight recent open‐source fat‐water separation algorithms were compared in silico, in vitro, and in vivo. Multi‐echo data were synthesized with varying fat‐fractions, B0 off‐resonance, SNR and TEs. Experimental evaluation was conducted using calibrated fat‐water phantoms acquired at 3T and multi‐site open‐source phantoms data. Algorithms' performances were observed on challenging in vivo datasets at 3T. Finally, reconstruction algorithms were investigated with different fat spectra to evaluate the importance of the fat model. Results: In silico and in vitro results proved most algorithms to be not sensitive to fat‐water swaps and B0$$ {\mathrm{B}}_0 $$ offsets with five or more echoes. However, two methods remained inaccurate even with seven echoes and SNR = 50, and two other algorithms' precision depended on the echo spacing scheme (p < 0.05). The remaining four algorithms provided reliable performances with limits of agreement under 2% for PDFF and 6 s−1 for R2*$$ {R}_2^{\ast } $$. The choice of fat spectrum model influenced quantification of PDFF mildly (<2% bias) and of R2*$$ {R}_2^{\ast } $$ more severely, with errors up to 20 s−1. Conclusion: In promoting standardized comparisons of MRI‐based fat and iron quantification using chemical‐shift encoded multi‐echo methods, this benchmark work has revealed some discrepancies between recent approaches for PDFF and R2*$$ {R}_2^{\ast } $$ mapping. Explicit choices and parameterization of the fat‐water algorithm appear necessary for reproducibility. This open‐source toolbox further enables the user to optimize acquisition parameters by predicting algorithms' margins of errors. [ABSTRACT FROM AUTHOR]

PurposeThe paper introduces a classical model to describe the dynamics of large spin-1/2 ensembles associated with nuclei bound in large molecule structures, commonly referred to as the semi-solid spin pool, and their magnetization transfer (MT) to spins of nuclei in water.Theory and methodsLike quantum-mechanical descriptions of spin dynamics and like the original Bloch equations, but unlike existing MT models, the proposed model is based on the algebra of angular momentum in the sense that it explicitly models the rotations induced by radiofrequency (RF) pulses. It generalizes the original Bloch model to non-exponential decays, which are, for example, observed for semi-solid spin pools. The combination of rotations with non-exponential decays is facilitated by describing the latter as Green's functions, comprised in an integro-differential equation.ResultsOur model describes the data of an inversion-recovery magnetization-transfer experiment with varying durations of the inversion pulse substantially better than established models. We made this observation for all measured data, but in particular for pulse durations smaller than 300 μs. Furthermore, we provide a linear approximation of the generalized Bloch model that reduces the simulation time by approximately a factor 15,000, enabling simulation of the spin dynamics caused by a rectangular RF-pulse in roughly 2 μs.ConclusionThe proposed theory unifies the original Bloch model, Henkelman's steady-state theory for MT, and the commonly assumed rotation induced by hard pulses (i.e., strong and infinitesimally short applications of RF-fields) and describes experimental data better than previous models.

Purpose: A significant source of artifacts in MRI are field fluctuations. Field monitoring is a new technology that allows measurement of field dynamics during a scan via "field probes," which can be used to improve image reconstruction. Ideally, probes are located within the volume where gradients produce nominally linear field patterns. However, in some situations probes must be located far from isocenter where rapid field variation can arise, leading to erroneous field‐monitoring characterizations and images. This work aimed to develop an algorithm that improves the robustness of field dynamics in these situations. Methods: The algorithm is split into three components. Component 1 calculates field dynamics one spatial order at a time, whereas the second implements a weighted least squares solution based on probe distance. Component 3 then calculates phase residuals and removes the residual phase for distant probes before recalculation. Two volunteers and a phantom were scanned on a 7T MRI using diffusion‐weighted sequences, and field monitoring was performed. Image reconstructions were informed with field dynamics calculated conventionally, and with the correction algorithm, after which in vivo images were compared qualitatively and phantom image error was quantitatively assessed. Results: The algorithm was able to correct corrupted field dynamics, resulting in image‐quality improvements. Significant artifact reduction was observed when correcting higher‐order fits. Stepwise fitting provided the most correction benefit, which was marginally improved when adding the other correction strategies. Conclusion: The proposed algorithm can mitigate effects of phase errors in field monitoring, providing improved characterization of field dynamics. [ABSTRACT FROM AUTHOR]

Purpose: To present the validation of a new Flexible Ultra‐Short Echo time (FUSE) pulse sequence using a short‐T2 phantom. Methods: FUSE was developed to include a range of RF excitation pulses, trajectories, dimensionalities, and long‐T2 suppression techniques, enabling real‐time interchangeability of acquisition parameters. Additionally, we developed an improved 3D deblurring algorithm to correct for off‐resonance artifacts. Several experiments were conducted to validate the efficacy of FUSE, by comparing different approaches for off‐resonance artifact correction, variations in RF pulse and trajectory combinations, and long‐T2 suppression techniques. All scans were performed on a 3 T system using an in‐house short‐T2 phantom. The evaluation of results included qualitative comparisons and quantitative assessments of the SNR and contrast‐to‐noise ratio. Results: Using the capabilities of FUSE, we demonstrated that we could combine a shorter readout duration with our improved deblurring algorithm to effectively reduce off‐resonance artifacts. Among the different RF and trajectory combinations, the spiral trajectory with the regular half‐inc pulse achieves the highest SNRs. The dual‐echo subtraction technique delivers better short‐T2 contrast and superior suppression of water and agar signals, whereas the off‐resonance saturation method successfully suppresses water and lipid signals simultaneously. Conclusion: In this work, we have validated the use of our new FUSE sequence using a short T2 phantom, demonstrating that multiple UTE acquisitions can be achieved within a single sequence. This new sequence may be useful for acquiring improved UTE images and the development of UTE imaging protocols. [ABSTRACT FROM AUTHOR]

Purpose: To reduce the ambiguity between chemical shift and field inhomogeneity with flexible TE combinations by introducing a variable (field factor). Theory and Methods: The ambiguity between chemical shift and field inhomogeneity can be eliminated directly from the multiple in‐phase images acquired at different TEs; however, it is only applicable to few echo combinations. In this study, we accommodated such an implementation in flexible TE combinations by introducing a new variable (field factor). The effects of the chemical shift were removed from the field inhomogeneity in the candidate solutions, thus reducing the ambiguity problem. To validate this concept, multi‐echo MRI data acquired from various anatomies with different imaging parameters were tested. The derived fat and water images were compared with those of the state‐of‐the‐art fat–water separation algorithms. Results: Robust fat–water separation was achieved with the accurate solution of field inhomogeneity, and no apparent fat–water swap was observed. In addition to the good performance, the proposed method is applicable to various fat–water separation applications, including different sequence types and flexible TE choices. Conclusion: We propose an algorithm to reduce the ambiguity of chemical shift and field inhomogeneity and achieved robust fat–water separation in various applications. [ABSTRACT FROM AUTHOR]

PurposeTo improve hyperpolarized 13 C (HP-13 C) MRI by image denoising with a new approach, patch-based higher-order singular value decomposition (HOSVD).MethodsThe benefit of using a patch-based HOSVD method to denoise dynamic HP-13 C MR imaging data was investigated. Image quality and the accuracy of quantitative analyses following denoising were evaluated first using simulated data of [1-13 C]pyruvate and its metabolic product, [1-13 C]lactate, and compared the results to a global HOSVD method. The patch-based HOSVD method was then applied to healthy volunteer HP [1-13 C]pyruvate EPI studies. Voxel-wise kinetic modeling was performed on both non-denoised and denoised data to compare the number of voxels quantifiable based on SNR criteria and fitting error.ResultsSimulation results demonstrated an 8-fold increase in the calculated SNR of [1-13 C]pyruvate and [1-13 C]lactate with the patch-based HOSVD denoising. The voxel-wise quantification of kPL (pyruvate-to-lactate conversion rate) showed a 9-fold decrease in standard errors for the fitted kPL after denoising. The patch-based denoising performed superior to the global denoising in recovering kPL information. In volunteer data sets, [1-13 C]lactate and [13 C]bicarbonate signals became distinguishable from noise across captured time points with over a 5-fold apparent SNR gain. This resulted in >3-fold increase in the number of voxels quantifiable for mapping kPB (pyruvate-to-bicarbonate conversion rate) and whole brain coverage for mapping kPL .ConclusionsSensitivity enhancement provided by this denoising significantly improved quantification of metabolite dynamics and could benefit future studies by improving image quality, enabling higher spatial resolution, and facilitating the extraction of metabolic information for clinical research.

PurposeTo investigate the symmetry constraint in susceptibility tensor imaging.TheoryThe linear relationship between the MRI frequency shift and the magnetic susceptibility tensor is derived without constraining the tensor to be symmetric. In the asymmetric case, the system matrix is shown to be maximally rank 6. Nonetheless, relaxing the symmetry constraint may still improve tensor estimation because noise and image artifacts do not necessarily follow the constraint.MethodsGradient echo phase data are obtained from postmortem mouse brain and kidney samples. Both symmetric and asymmetric tensor reconstructions are applied to the data. The reconstructions are then used for susceptibility tensor imaging fiber tracking. Simulations with ground truth and at various noise levels are also performed. The reconstruction methods are compared qualitatively and quantitatively.ResultsCompared to regularized and unregularized symmetric reconstructions, the asymmetric reconstruction shows reduced noise and streaking artifacts, better contrast, and more complete fiber tracking. In simulation, the asymmetric reconstruction achieves better mean squared error and better angular difference in the presence of noise. Decomposing the asymmetric tensor into its symmetric and antisymmetric components confirms that the underlying susceptibility tensor is symmetric and that the main sources of asymmetry are noise and streaking artifacts.ConclusionWhereas the susceptibility tensor is symmetric, asymmetric reconstruction is more effective in suppressing noise and artifacts, resulting in more accurate estimation of the susceptibility tensor.

Purpose: Non‐Cartesian MRI with long arbitrary readout directions are susceptible to off‐resonance artifacts due to patient induced B0$$ {B}_0 $$ inhomogeneities. This results in degraded image quality with strong signal losses and blurring. Current solutions to address this issue involve correcting the off‐resonance artifacts during image reconstruction or reducing inhomogeneities through improved shimming. Theory: The recently developed SPARKLING algorithm is extended to drastically diminish off‐resonance artifacts by generating temporally smooth k‐space sampling patterns. For doing so, the cost function which is optimized in SPARKLING is modified using a temporal weighting factor. Additionally, oversampling of the center of k‐space beyond the Nyquist criteria is prevented through the use of gridded sampling in the region, enforced with affine constraints. Methods: Prospective k‐space data was acquired at 3 T on new trajectories, and we show robustness to B0$$ {\mathrm{B}}_0 $$ inhomogeneities through in silico experiments by adding ΔB0$$ \Delta {\mathrm{B}}_0 $$ through artificial degradation of system B0$$ {\mathrm{B}}_0 $$ shimming. Later on, in vivo experiments were carried out to optimize parameters of the new improvements and benchmark the gain in performance. Results: The improved trajectories allowed for the recovery of signal dropouts observed on original SPARKLING acquisitions at larger B0$$ {\mathrm{B}}_0 $$ field inhomogeneities. Furthermore, imposing gridded sampling at the center of k‐space provided improved reconstructed image quality with limited artifacts. Conclusion: These advancements allowed us for nearly 4.62×$$ 4.62\times $$ shorter scan time compared to GRAPPA‐p4x1, allowing us to reach 600 µm isotropic resolution in 3D T2∗$$ {\mathrm{T}}_2^{\ast } $$‐w imaging in just 3.3 min at 3 T with negligible degradation in image quality. [ABSTRACT FROM AUTHOR]

Purpose: An accurate field map is essential to separate fat and water signals in a dual‐echo chemical shift encoded spiral MRI scan. A rapid low‐resolution B0 map prescan is usually performed before each exam. Occasional inaccuracy in these field map estimates can lead to misclassification of the water and fat signals as well as blurring artifacts in the reconstruction. The present work proposes a self‐consistent model to evaluate residual field offsets according to the image data to improve the reconstruction quality and facilitate the scan efficiency. Theory and Methods: The proposed method compares the phase differences of the two‐echo data after correcting for fat frequency offsets. A more accurate field map is approximated according to the phase discrepancies and improved image quality. Experiments were conducted with simulated off‐resonance on a numerical phantom, five volunteer head scans, and four volunteer abdominal scans for validation. Results: The initial reconstruction of the demonstrated examples exhibit blurring artifacts and misregistration of fat and water because of the inaccuracy of the field map. The proposed method updates the field map to amend the fat and water estimation and improve image quality. Conclusions: This work presents a model to improve the quality of fat‐water imaging of the spiral MRI by estimating a better field map from the acquired data. It allows reducing the field map pre‐scans before each spiral scan under normal circumstances to increase scan efficiency. [ABSTRACT FROM AUTHOR]

PurposeTo use fiducial markers containing manganese 55 to rapidly localize carbon 13 (13 C) RF coils for correcting images for B1 variation.MethodsHollow high-density polyethylene spheres were filled with 3M sodium permanganate and affixed to a rectangular 13 C-tuned RF coil. The relative positions of the markers and coil conductors were mapped using CT. Marker positions were measured by MRI using a series of 1D projections and automated peak detection. Once the coil location was determined, coil sensitivity was estimated using a quasi-static calculation. Simulations were performed to determine the minimum number of projections required for robust localization. Phantom experiments were used to confirm the accuracy of marker localization as well as the calculated coil sensitivity. Finally, in vivo validation was performed using hyperpolarized 13 C pyruvate in a rat model.ResultsIn simulations, our algorithm was accurate in determining marker positions when at least 6 projections were used (RMSE 1.4 ± 0.9 mm). These estimates were verified in phantom experiments, where markers locations were determined with an RMS accuracy of 1.3 mm. A minimum SNR of 4 was required for automated detection to perform accurately. Computed coil sensitivity had a median error of 17% when taken over the entire measured area and 5.7% over a central region. In a rat, correction for nonuniform reception and flip angle was able to normalize the signals arising from asymmetrically positioned kidneys.ConclusionManganese 55 fiducial markers are an inexpensive and reliable method for rapidly localizing 13 C RF coils and correcting 13 C images for B1 variation without user intervention.

PURPOSE: Structure-guided total variation is a recently introduced prior that allows reconstruction of images using knowledge of the location and orientation of edges in a reference image. In this work, we demonstrate the advantages of a variant of structure-guided total variation known as directional total variation (DTV), over traditional total variation (TV), in the context of compressed-sensing reconstruction and super-resolution. METHODS: We compared TV and DTV in retrospectively undersampled ex vivo diffusion tensor imaging and diffusion spectrum imaging data from healthy, sham, and hypertrophic rat hearts. RESULTS: In compressed sensing at an undersampling factor of 8, the RMS error of mean diffusivity and fractional anisotropy relative to the fully sampled ground truth were 44% and 20% lower in DTV compared with TV. In super-resolution, these values were 29% and 14%, respectively. Similarly, we observed improvements in helix angle, transverse angle, sheetlet elevation, and sheetlet azimuth. The RMS error of the diffusion kurtosis in the undersampled data relative to the ground truth was uniformly lower (22% on average) with DTV compared to TV. CONCLUSION: Acquiring one fully sampled non-diffusion-weighted image and 10 diffusion-weighted images at 8× undersampling would result in an 80% net reduction in data needed. We demonstrate efficacy of the DTV algorithm over TV in reducing data sampling requirements, which can be translated into higher apparent resolution and potentially shorter scan times. This method would be equally applicable in diffusion MRI applications outside the heart.

PurposeTo develop a deep learning-based method for knee menisci segmentation in 3D ultrashort echo time (UTE) cones MR imaging, and to automatically determine MR relaxation times, namely the T1, T1ρ , and T2∗ parameters, which can be used to assess knee osteoarthritis (OA).MethodsWhole knee joint imaging was performed using 3D UTE cones sequences to collect data from 61 human subjects. Regions of interest (ROIs) were outlined by 2 experienced radiologists based on subtracted T1ρ -weighted MR images. Transfer learning was applied to develop 2D attention U-Net convolutional neural networks for the menisci segmentation based on each radiologist's ROIs separately. Dice scores were calculated to assess segmentation performance. Next, the T1, T1ρ , T2∗ relaxations, and ROI areas were determined for the manual and automatic segmentations, then compared.ResultsThe models developed using ROIs provided by 2 radiologists achieved high Dice scores of 0.860 and 0.833, while the radiologists' manual segmentations achieved a Dice score of 0.820. Linear correlation coefficients for the T1, T1ρ , and T2∗ relaxations calculated using the automatic and manual segmentations ranged between 0.90 and 0.97, and there were no associated differences between the estimated average meniscal relaxation parameters. The deep learning models achieved segmentation performance equivalent to the inter-observer variability of 2 radiologists.ConclusionThe proposed deep learning-based approach can be used to efficiently generate automatic segmentations and determine meniscal relaxations times. The method has the potential to help radiologists with the assessment of meniscal diseases, such as OA.

PurposeDirect myelin imaging can improve the characterization of myelin-related diseases such as multiple sclerosis. In this study, we explore a novel method to directly image myelin using inversion recovery-prepared hybrid encoding (IR-HE) UTE MRI.MethodsThe IR-HE sequence uses an adiabatic inversion pulse to suppress the long T2 white matter signal, followed by 3D dual-echo HE utilizing both single point imaging and radial frequency encoding, for which the subtraction image between 2 echoes reveals the myelin signal with high contrast. To reduce scan time, it is common to obtain multiple spokes per IR. Here, we invented a novel method to improve the HE, adapted for the multi-spoke IR imaging-termed interleaved HE-for which single point imaging encoding is interleaved between radial frequency encodings near nulling point to allow more efficient IR-signal suppression. To evaluate the proposed approach, a computer simulation, myelin phantom experiment, an ex vivo experiment with a cadaveric multiple sclerosis brain, and an in vivo experiment with 8 healthy volunteers and 13 multiple sclerosis patients were performed.ResultsThe computer simulation showed that IR-interleaved HE allows for improved contrast of myelin signal with reduced imaging artifacts. The myelin phantom experiment showed IR-interleaved HE allows direct imaging of myelin lipid with excellent suppression of water signal. In the ex vivo and in vivo experiments, the proposed method demonstrated highly specific imaging of myelin in white matter of the brain.ConclusionIR-interleaved HE allows for time-efficient, high-contrast direct myelin imaging and can detect demyelinated lesions in multiple sclerosis patients.

PurposeTo design a soft-hard composite pulse for fat suppression and water excitation in ultrashort echo time (UTE) imaging with minimal short T2 signal attenuation.MethodsThe composite pulse contains a narrow bandwidth soft pulse centered on the fat peak with a small negative flip angle (-α) and a short rectangular pulse with a small positive flip angle (α). The fat magnetization experiences both tipping-down and -back with an identical flip angle and thus returns to the equilibrium state, leaving only the excited water magnetization. Bloch simulations, as well as knee, tibia, and ankle UTE imaging studies, were performed to investigate the effectiveness of fat suppression and corresponding water signal attenuation. A conventional fat saturation (FatSat) module was used for comparison. Signal suppression ratio (SSR), defined as the ratio of signal difference between non-fat-suppression and fat-suppression images over the non-fat-suppression signal, was introduced to evaluate the efficiency of the composite pulse.ResultsNumerical simulations demonstrate that the soft-hard pulse has little saturation effect on short T2 water signals. Knee, tibia, and ankle UTE imaging results suggest that comparable fat suppression can be achieved with the soft-hard pulse and the FatSat module. However, much less water saturation is induced by the soft-hard pulse, especially for short T2 tissues, with SSRs reduced from 71.8 ± 6.9% to 5.8 ± 4.4% for meniscus, from 68.7 ± 5.5% to 7.7 ± 7.6% for bone, and from 62.9 ± 12.0% to 4.8 ± 3.2% for the Achilles tendon.ConclusionThe soft-hard composite pulse can suppress fat signals in UTE imaging with little signal attenuation on short T2 tissues.

Purpose: The goal of this study was to apply a fast data‐driven optimization algorithm, called bias‐accelerated subset selection, for MR brain T1ρ mapping to generate optimized sampling patterns (SPs) for compressed sensing reconstruction of brain 3D‐T1ρ MRI. Methods: Five healthy volunteers were recruited, and fully sampled Cartesian 3D‐T1ρ MRIs were obtained. Variable density (VD) and Poisson disc (PD) undersampling was used as the input to SP optimization process. The reconstruction used 3 compressed sensing methods: spatiotemporal finite differences, low‐rank plus sparse with spatial finite differences, and low rank. The performance of images and T1ρ maps using PD‐SP and VD‐SP and their optimized sampling patterns (PD‐OSP and VD‐OSP) were compared to the fully sampled reference using normalized root mean square error (NRMSE). Results: The VD‐OSP with spatiotemporal finite differences reconstruction (NRMSE = 0.078) and the PD‐OSP with spatiotemporal finite differences reconstruction (NRMSE = 0.079) at the highest acceleration factors (AF = 30) showed the largest improvement compared to the respective nonoptimized SPs (VD NRMSE = 0.087 and PD NRMSE = 0.149). Prospective undersampling was tested at AF = 4, with VD‐OSP NRMSE = 0.057 versus PD‐OSP NRMSE = 0.060, with optimized sampling performing better that input PD or VD sampling. For brain T1ρ mapping, the VD‐OSP with low rank reconstruction for AFs <10 and VD‐OSP with spatiotemporal finite differences for AFs >10 perform better. Conclusions: The study demonstrated that the appropriate use of data‐driven optimized sampling and suitable compressed sensing reconstruction technique can be employed to potentially accelerate 3D T1ρ mapping for brain imaging applications. [ABSTRACT FROM AUTHOR]

Purpose: To enhance image quality of flow‐compensated diffusion‐weighted liver MRI data by increasing the lesion conspicuity and reducing the cardiac pulsation artifact using postprocessing algorithms. Methods: Diffusion‐weighted image data of 40 patients with liver lesions had been acquired at 1.5 T. These data were postprocessed with 5 different algorithms (weighted averaging, p‐mean, percentile, outlier exclusion, and exception set). Four image properties of the postprocessed data were evaluated for optimizing the algorithm parameters. These properties were the lesion to tissue contrast‐to‐noise ratio (CNR), the reduction of the cardiac pulsation artifact, the data consistency, and the vessel darkness. They were combined into a total quality score (Qtotal,$$ {Q}_{\mathrm{total}}, $$ set to 1 for the trace‐weighted reference image), which was used to rate the image quality objectively. Results: The weighted averaging algorithm performed best according to the total quality score (Qtotal=1.111±0.067$$ {Q}_{\mathrm{total}}=1.111\pm 0.067 $$). The further ranking was outlier exclusion algorithm (Qtotal=1.086±0.061$$ {Q}_{\mathrm{total}}=1.086\pm 0.061 $$), p‐mean algorithm (Qtotal=1.045±0.049$$ {Q}_{\mathrm{total}}=1.045\pm 0.049 $$), percentile algorithm (Qtotal=1.012±0.049$$ {Q}_{\mathrm{total}}=1.012\pm 0.049 $$), and exception set algorithm (Qtotal=0.957±0.027$$ {Q}_{\mathrm{total}}=0.957\pm 0.027 $$). All optimized algorithms except for the exception set algorithm corrected the pulsation artifact and increased the lesion CNR. Changes in Qtotal$$ {Q}_{\mathrm{total}} $$ were significant for all optimized algorithms except for the percentile algorithm. Liver ADC was significantly reduced (except for the exception set algorithm), particularly in the left lobe. Conclusion: Postprocessing algorithms should be used for flow‐compensated liver DWI. The proposed weighted averaging algorithm seems to be suited best to increase the image quality of artifact‐corrupted flow‐compensated diffusion‐weighted liver data. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to find a relation between the number of channels and the computational burden for specific absorption rate (SAR) calculation using virtual observation point‐based SAR compression. Methods: Eleven different arrays of rectangular loops covering a cylinder of fixed size around the head of an anatomically correct voxel model were simulated. The resulting Q‐matrices were compressed with 2 different compression algorithms, with the overestimation fixed to a certain fraction of worst‐case SAR, median SAR, or minimum SAR. The latter 2 were calculated from 1e6 normalized random excitation vectors. Results: The number of virtual observation points increased with the number of channels to the power of 2.3–3.7, depending on the compression algorithm when holding the relative error fixed. Together with the increase in the size of the Q‐matrices (and therefore the size of the virtual observation points), the total increase in computational burden with the number of channels was to the power of 4.3–5.7. Conclusion: The computational cost emphasizes the need to use the best possible compression algorithms when moving to high channel counts. [ABSTRACT FROM AUTHOR]

PurposeRapid chemical exchange can affect SNR and pH measurement accuracy for hyperpolarized pH imaging with [13 C]bicarbonate. The purpose of this work was to investigate chemical exchange effects on hyperpolarized imaging sequences to identify optimal sequence parameters for high SNR and pH accuracy.MethodsSimulations were performed under varying rates of bicarbonate-CO2 chemical exchange to analyze exchange effects on pH quantification accuracy and SNR under different sampling schemes. Four pulse sequences, including 1 new technique, a multiple-excitation 2D EPI (multi-EPI) sequence, were compared in phantoms using hyperpolarized [13 C]bicarbonate, varying parameters such as tip angles, repetition time, order of metabolite excitation, and refocusing pulse design. In vivo hyperpolarized bicarbonate-CO2 exchange measurements were made in transgenic murine prostate tumors to select in vivo imaging parameters.ResultsModeling of bicarbonate-CO2 exchange identified a multiple-excitation scheme for increasing CO2 SNR by up to a factor of 2.7. When implemented in phantom imaging experiments, these sampling schemes were confirmed to yield high pH accuracy and SNR gains. Based on measured bicarbonate-CO2 exchange in vivo, a 47% CO2 SNR gain is predicted.ConclusionThe novel multi-EPI pulse sequence can boost CO2 imaging signal in hyperpolarized 13 C bicarbonate imaging while introducing minimal pH bias, helping to surmount a major hurdle in hyperpolarized pH imaging.

PurposeTo investigate tricomponent analysis of human cortical bone using a multipeak fat signal model with 3D ultrashort TE Cones sequences on a clinical 3T scanner.MethodsTricomponent fitting of bound water, pore water, and fat content using a multipeak fat spectra model was proposed for 3D ultrashort TE imaging of cortical bone. Three-dimensional ultrashort TE Cones acquisitions combined with tricomponent analysis were used to investigate bound and pore water T2∗ and fractions, as well as fat T2∗ and fraction in cortical bone. Feasibility studies were performed on 9 human cortical bone specimens with regions of interest selected from the endosteum to the periosteum in 4 circumferential regions. Microcomputed tomography studies were performed to measure bone porosity and bone mineral density for comparison and validation of the bound and pore water analyses.ResultsThe oscillation of the signal decay was well-fitted with the proposed tricomponent model. The sum of the pore water and fat fractions from tricomponent analysis showed a high correlation with microcomputed tomography porosity (R = 0.74, P < 0.01). Estimated bound-water fraction also demonstrated a high correlation with bone mineral density (R = 0.70, P < 0.01).ConclusionTricomponent analysis significantly improves the estimation of bound-water and pore-water fractions in human cortical bone.

PurposeTo investigate the effect of stretching sampling window on quantitative 3D ultrashort TE (UTE) imaging of cortical bone at 3 T.MethodsTen bovine cortical bone and 17 human tibial midshaft samples were imaged with a 3T clinical MRI scanner using an 8-channel knee coil. Quantitative 3D UTE imaging biomarkers, including T1 , T2∗ , magnetization transfer ratio and magnetization transfer modeling, were performed using radial or spiral Cones sampling trajectories with various durations. Errors in UTE-MRI biomarkers as a function of sampling time were evaluated using radial sampling as a reference standard.ResultsFor both bovine and human cortical bone samples, no significant differences were observed for all UTE biomarkers (single-component T2∗ , bicomponent T2∗ and relative fractions, T1 , magnetization transfer ratio, and magnetization transfer modeling of macromolecular fraction) for spiral sampling windows of 992 µs to 1600 µs compared with a radial sampling window of 688 µs.ConclusionThe total scan time can be reduced by 76% with quantification errors less than 5%. Quantitative UTE-MRI techniques can be greatly accelerated using longer sampling windows without significant quantification errors.

PurposeDelayed enhancement imaging is an essential component of cardiac MRI, which is used widely for the evaluation of myocardial scar and viability. The selection of an optimal inversion time (TI) or null point (TINP ) to suppress the background myocardial signal is required. The purpose of this study was to assess the feasibility of automated selection of TINP using a convolutional neural network (CNN). We hypothesized that a CNN may use spatial and temporal imaging characteristics from an inversion-recovery scout to select TINP , without the aid of a human observer.MethodsWe retrospectively collected 425 clinically acquired cardiac MRI exams performed at 1.5 T that included inversion-recovery scout acquisitions. We developed a VGG19 classifier ensembled with long short-term memory to identify the TINP . We compared the performance of the ensemble CNN in predicting TINP against ground truth, using linear regression analysis. Ground truth was defined as the expert physician annotation of the optimal TI. In a backtrack approach, saliency maps were generated to interpret the classification outcome and to increase the model's transparency.ResultsPrediction of TINP from our ensemble VGG19 long short-term memory closely matched with expert annotation (ρ = 0.88). Ninety-four percent of the predicted TINP were within ±36 ms, and 83% were at or after expert TI selection.ConclusionIn this study, we show that a CNN is capable of automated prediction of myocardial TI from an inversion-recovery experiment. Merging the spatial and temporal characteristics of the VGG-19 and long short-term-memory CNN structures appears to be sufficient to predict myocardial TI from TI scout.

PurposeTo develop a dynamic contrast-enhanced (DCE) MRI method capable of high spatiotemporal resolution, 3D carotid coverage, and T1-based quantification of contrast agent concentration for the assessment of carotid atherosclerosis using a newly developed Multitasking technique.Methods5D imaging with 3 spatial dimensions, 1 T1 recovery dimension, and 1 DCE time dimension was performed using MR Multitasking based on low-rank tensor modeling, which allows direct T1 quantification with high spatiotemporal resolution (0.7 mm isotropic and 595 ms, respectively). Saturation recovery preparations followed by 3D segmented fast low angle shot readouts were implemented with Gaussian-density random 3D Cartesian sampling. A bulk motion removal scheme was developed to improve image quality. The proposed protocol was tested in phantom and human studies. In vivo scans were performed on 14 healthy subjects and 7 patients with carotid atherosclerosis. Kinetic parameters including area under the concentration versus time curve (AUC), vp , Ktrans , and ve were evaluated for each case.ResultsPhantom experiments showed that T1 measurements using the proposed protocol were in good agreement with reference value ( R 2 = 0.96 ). In vivo studies demonstrated that AUC, vp , and Ktrans in the patient group were significantly higher than in the control group (0.63 ± 0.13 versus 0.42 ± 0.12, P < 0.001; 0.14 ± 0.05 versus 0.11 ± 0.03, P = 0.034; and 0.13 ± 0.04 versus 0.08 ± 0.02, P < 0.001, respectively). Results from repeated subjects showed good interscan reproducibility (intraclass correlation coefficient: vp , 0.83; Ktrans , 0.87; ve , 0.92; AUC, 0.94).ConclusionMultitasking DCE is a promising approach for quantitatively assessing the vascularity properties of the carotid vessel wall.

PurposeIn this study, we explore the feasibility of a new imaging scheme for quantitative susceptibility mapping (QSM): continuous single-point imaging (CSPI), which uses a pure phase encoding strategy to achieve true phase imaging and improve QSM accuracy.MethodsThe proposed CSPI is a modification of conventional SPI to allow acquisition of multiple echoes in a single scan. Immediately following a phase encoding gradient, the free induction decay is continuously sampled with extremely high temporal resolution to obtain k-space data at a fixed spatial frequency (i.e., at a fixed k-space coordinate). By having near-0 readout duration, CSPI results in a true snapshot of the transverse magnetization at each TE. Additionally, parallel imaging with autocalibration is utilized to reduce scan time, and an optional temporal averaging strategy is presented to improve signal-to-noise ratio for objects with low proton density or short T2* decay. The reconstructed CSPI images were input to a QSM framework based on morphology enabled dipole inversion.ResultIn an experiment performed using iron phantoms, susceptibility estimated using CSPI showed high linearity (R2 = 0.9948) with iron concentration. Additionally, reconstructed CSPI phase images showed much reduced ringing artifact compared with phase images obtained using a frequency encoding strategy. In an ex vivo experiment performed using human tibia samples, estimated susceptibilities ranged from -1.6 to -2.1 ppm, in agreement with values reported in the literature (ranging from -1.2 to -2.2 ppm).ConclusionWe have demonstrated the feasibility of using CSPI to obtain true phase images for QSM.

PurposeTo measure T1 relaxations for the major tissues in whole knee joints on a clinical 3T scanner.MethodsThe 3D UTE-Cones actual flip angle imaging (AFI) method was used to map the transmission radiofrequency field (B1 ) in both short and long T2 tissues, which was then used to correct the 3D UTE-Cones variable flip angle (VFA) fitting to generate accurate T1 maps. Numerical simulation was carried out to investigate the accuracy of T1 measurement for a range of T2 values, excitation pulse durations, and B1 errors. Then, the 3D UTE-Cones AFI-VFA method was applied to healthy volunteers (N = 16) to quantify the T1 of knee tissues including cartilage, meniscus, quadriceps tendon, patellar tendon, anterior cruciate ligament (ACL), posterior cruciate ligament (PCL), marrow, and muscles at 3T.ResultsNumerical simulation showed that the 3D UTE-Cones AFI-VFA technique can provide accurate T1 measurements (error

PurposeAcquisition timing and B1 calibration are two key factors that affect the quality and accuracy of hyperpolarized 13 C MRI. The goal of this project was to develop a new approach using regional bolus tracking to trigger Bloch-Siegert B1 mapping and real-time B1 calibration based on regional B1 measurements, followed by dynamic imaging of hyperpolarized 13 C metabolites in vivo.MethodsThe proposed approach was implemented on a system which allows real-time data processing and real-time control on the sequence. Real-time center frequency calibration upon the bolus arrival was also added. The feasibility of applying the proposed framework for in vivo hyperpolarized 13 C imaging was tested on healthy rats, tumor-bearing mice and a healthy volunteer on a clinical 3T scanner following hyperpolarized [1-13 C]pyruvate injection. Multichannel receive coils were used in the human study.ResultsAutomatic acquisition timing based on either regional bolus peak or bolus arrival was achieved with the proposed framework. Reduced blurring artifacts in real-time reconstructed images were observed with real-time center frequency calibration. Real-time computed B1 scaling factors agreed with real-time acquired B1 maps. Flip angle correction using B1 maps results in a more consistent quantification of metabolic activity (i.e, pyruvate-to-lactate conversion, kPL ). Experiment recordings are provided to demonstrate the real-time actions during the experiment.ConclusionsThe proposed method was successfully demonstrated on animals and a human volunteer, and is anticipated to improve the efficient use of the hyperpolarized signal as well as the accuracy and robustness of hyperpolarized 13 C imaging.

PurposeAcquisition timing and B1 calibration are two key factors that affect the quality and accuracy of hyperpolarized 13 C MRI. The goal of this project was to develop a new approach using regional bolus tracking to trigger Bloch-Siegert B1 mapping and real-time B1 calibration based on regional B1 measurements, followed by dynamic imaging of hyperpolarized 13 C metabolites in vivo.MethodsThe proposed approach was implemented on a system which allows real-time data processing and real-time control on the sequence. Real-time center frequency calibration upon the bolus arrival was also added. The feasibility of applying the proposed framework for in vivo hyperpolarized 13 C imaging was tested on healthy rats, tumor-bearing mice and a healthy volunteer on a clinical 3T scanner following hyperpolarized [1-13 C]pyruvate injection. Multichannel receive coils were used in the human study.ResultsAutomatic acquisition timing based on either regional bolus peak or bolus arrival was achieved with the proposed framework. Reduced blurring artifacts in real-time reconstructed images were observed with real-time center frequency calibration. Real-time computed B1 scaling factors agreed with real-time acquired B1 maps. Flip angle correction using B1 maps results in a more consistent quantification of metabolic activity (i.e, pyruvate-to-lactate conversion, kPL ). Experiment recordings are provided to demonstrate the real-time actions during the experiment.ConclusionsThe proposed method was successfully demonstrated on animals and a human volunteer, and is anticipated to improve the efficient use of the hyperpolarized signal as well as the accuracy and robustness of hyperpolarized 13 C imaging.

PurposeTo develop a 3D adiabatic T1ρ prepared ultrashort echo time cones (3D AdiabT1ρ UTE-Cones) sequence for whole knee imaging on a clinical 3T scanner.MethodsA train of adiabatic full passage pulses were used for spin locking, followed by time-efficient multispoke UTE acquisition to detect signals from both short and long T2 tissues in the whole knee joint. A modified signal model was proposed for multispoke UTE data fitting. The feasibility of this 3D AdiabT1ρ UTE-Cones technique was demonstrated through numerical simulation, phantom, and ex vivo knee sample studies. The 3D AdiabT1ρ UTE-Cones technique was then applied to 6 in vivo knee joints of healthy volunteers to measure T1ρ values of quadriceps tendon, patellar tendon, anterior cruciate ligament (ACL), posterior cruciate ligament (PCL), meniscus, patellar cartilage, and muscle.ResultsNumerical simulation, phantom and ex vivo knee sample studies demonstrated the feasibility of whole knee imaging using the proposed multispoke 3D AdiabT1ρ UTE-Cones sequence. The healthy volunteer knee study demonstrated an averaged T1ρ of 13.9 ± 0.7 ms for the quadriceps tendon, 9.7 ± 0.8 ms for the patellar tendon, 34.9 ± 2.8 ms for the ACL, 21.6 ± 1.4 ms for the PCL, 22.5 ± 1.9 ms for the meniscus, 44.5 ± 2.4 ms for the patellar cartilage, and 43.2 ± 1.1 ms for the muscle.ConclusionThe 3D AdiabT1ρ UTE-Cones sequence allows volumetric T1ρ assessment of both short and long T2 tissues in the knee joint on a clinical 3T scanner.

PurposeTo develop an accurate T1 measurement method for short T2 tissues using a combination of a 3-dimensional ultrashort echo time cones actual flip angle imaging technique and a variable repetition time technique (3D UTE-Cones AFI-VTR) on a clinical 3T scanner.MethodsFirst, the longitudinal magnetization mapping function of the excitation pulse was obtained with the 3D UTE-Cones AFI method, which provided information about excitation efficiency and B1 inhomogeneity. Then, the derived mapping function was substituted into the VTR fitting to generate accurate T1 maps. Numerical simulation and phantom studies were carried out to compare the AFI-VTR method with a B1 -uncorrected VTR method, a B1 -uncorrected variable flip angle (VFA) method, and a B1 -corrected VFA method. Finally, the 3D UTE-Cones AFI-VTR method was applied to bovine bone samples (N = 6) and healthy volunteers (N = 3) to quantify the T1 of cortical bone.ResultsNumerical simulation and phantom studies showed that the 3D UTE-Cones AFI-VTR technique provides more accurate measurement of the T1 of short T2 tissues than the B1 -uncorrected VTR and VFA methods or the B1 -corrected VFA method. The proposed 3D UTE-Cones AFI-VTR method showed a mean T1 of 240 ± 25 ms for bovine cortical bone and 218 ± 10 ms for the tibial midshaft of human volunteers, respectively, at 3 T.ConclusionThe 3D UTE-Cones AFI-VTR method can provide accurate T1 measurements of short T2 tissues such as cortical bone. Magn Reson Med 80:598-608, 2018. © 2018 International Society for Magnetic Resonance in Medicine.

PurposeTo develop a rapid segmentation-free method to visualize and compute wall shear stress (WSS) throughout the aorta using 4D Flow MRI data. WSS is the drag force-per-area the vessel endothelium exerts on luminal blood; abnormal levels of WSS are associated with cardiovascular pathologies. Previous methods for computing WSS are bottlenecked by labor-intensive manual segmentation of vessel boundaries. A rapid automated segmentation-free method for computing WSS is presented.Theory and methodsShear stress is the dot-product of the viscous stress tensor and the inward normal vector. The inward normal vectors are approximated as the gradient of fluid speed at every voxel. Subsequently, a 4D map of shear stress is computed as the partial derivatives of velocity with respect to the inward normal vectors. We highlight the shear stress near the wall by fusing visualization with edge-emphasized anatomical data.ResultsAs a proof-of-concept, four cases with aortic pathologies are presented. Visualization allows for rapid localization of pathologic WSS. Subsequent analysis of these pathological regions enables quantification of WSS. Average WSS during peak systole measures approximately 50-60 cPa in nonpathological regions of the aorta and is elevated in regions of stenosis, coarctation, and dissection. WSS is reduced in regions of aneurysm.ConclusionA volumetric technique for calculation and visualization of WSS from 4D Flow MRI data is presented. Traditional labor-intensive methods for WSS rely on explicit manual segmentation of vessel boundaries before visualization. This automated volumetric strategy for visualization and quantification of WSS may facilitate its clinical translation.

PurposeTo achieve motion robust high resolution 3D free-breathing pulmonary MRI utilizing a novel dynamic 3D image navigator derived directly from imaging data.MethodsFive-minute free-breathing scans were acquired with a 3D ultrashort echo time (UTE) sequence with 1.25 mm isotropic resolution. From this data, dynamic 3D self-navigating images were reconstructed under locally low rank (LLR) constraints and used for motion compensation with one of two methods: a soft-gating technique to penalize the respiratory motion induced data inconsistency, and a respiratory motion-resolved technique to provide images of all respiratory motion states.ResultsRespiratory motion estimation derived from the proposed dynamic 3D self-navigator of 7.5 mm isotropic reconstruction resolution and a temporal resolution of 300 ms was successful for estimating complex respiratory motion patterns. This estimation improved image quality compared to respiratory belt and DC-based navigators. Respiratory motion compensation with soft-gating and respiratory motion-resolved techniques provided good image quality from highly undersampled data in volunteers and clinical patients.ConclusionAn optimized 3D UTE sequence combined with the proposed reconstruction methods can provide high-resolution motion robust pulmonary MRI. Feasibility was shown in patients who had irregular breathing patterns in which our approach could depict clinically relevant pulmonary pathologies. Magn Reson Med 79:2954-2967, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

PurposeTo investigate high contrast imaging of short T2 tissues with a three-dimensional double adiabatic inversion recovery prepared ultrashort echo time Cones (3D DIR-UTE-Cones) sequence.MethodsThe sequence used two sequential adiabatic inversion pulses to suppress signals from long T2 tissues, followed by multispoke UTE acquisition to detect signals from short T2 tissues. The two adiabatic inversion pulses are identical with a center frequency located at the water peak, but the spectral width is broad enough to cover both water and fat frequencies. The feasibility of this technique was demonstrated through numerical simulation and phantom studies. Finally, DIR-UTE-Cones was applied to three healthy volunteers to image cortical bone, patellar tendon, and Achilles tendon. T2* was also measured via single-component exponential fitting.ResultsNumerical simulation suggests that the DIR technique provides perfect nulling of muscle and fat as well as efficient suppression of other long T2 tissues with T1 values between fat and water or those above water. Excellent image contrast can be achieved with DIR-UTE-Cones for the short T2 tissues, with fitted T2* values of 0.28-0.38 ms for cortical bone, 0.56 ± 0.07 ms for the patella tendon, and 0.45 ± 0.06 ms for the Achilles tendon, respectively.ConclusionThe 3D DIR-UTE-Cones sequence provides robust suppression of long T2 tissues and allows selective imaging as well as T2* measurement of short T2 tissues such as cortical bone, patellar tendon, and the Achilles tendon. Magn Reson Med 79:2555-2563, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

PurposeTo investigate quantitative 2D ultrashort echo time magnetization transfer (UTE-MT) imaging in ex vivo bovine cortical bone and in vivo human tibial cortical bone.MethodsData were acquired from five fresh bovine cortical bone samples and five healthy volunteer tibial cortical bones using a 2D UTE-MT sequence on a clinical 3T scanner. The 2D UTE-MT sequence used four or five MT powers with five frequency offsets. Results were analyzed with a two-pool quantitative MT model, providing measurements of macromolecular fraction (f), macromolecular proton transverse relaxation times (T2m ), proton exchange rates from water/macromolecular to the macromolecular/water pool (RM0m /RM0w ), and spin-lattice relaxation rate of water pool (R1w ). A sequential air-drying study for a small bovine cortical bone chip was used to investigate whether above MT modeling parameters were sensitive to the water loss.ResultsMean fresh bovine cortical bone values for f, T2m , R1w , RM0m , and RM0w were 59.9 ± 7.3%, 14.6 ± 0.3 μs, 9.9 ± 2.4 s-1 , 17.9 ± 3.6 s-1 , and 11.8 ± 2.0 s-1 , respectively. Mean in vivo human cortical bone values for f, T2m , R1w , RM0m and RM0w were 54.5 ± 4.9%, 15.4 ± 0.6 μs, 8.9 ± 1.1 s-1 , 11.5 ± 3.5 s-1 , and 9.5 ± 1.9 s-1 , respectively. The sequential air-drying study shows that f, RM0m , and R1w were increased with longer drying time.ConclusionUTE-MT two-pool modeling provides novel and useful quantitative information for cortical bone. Magn Reson Med 79:1941-1949, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

PurposeTo evaluate the echo dependence of 3D ultrashort echo time (TE) quantitative susceptibility mapping (3D UTE-QSM) and effective transverse relaxation rate ( R2*) measurement in the setting of high concentrations of iron oxide nanoparticles.MethodsA phantom study with iron concentrations ranging from 2 to 22 mM was performed using a 3D UTE Cones sequence. Simultaneous QSM processing with morphology-enabled dipole inversion (MEDI) and R2* single exponential fitting was conducted offline with the acquired 3D UTE data. The dependence of UTE-QSM and R2* on echo spacing (ΔTE) and first TE (TE1 ) was investigated.ResultsA linear relationship was observed between UTE-QSM measurement and iron concentration up to 22 mM only, with the minimal TE1 of 0.032 ms and ΔTE of less than 0.1 ms. A linear relationship was observed between R2* and iron concentration up to 22 mM only when TE1 was less than 0.132 ms and ΔTE was less than 1.2 ms. UTE-QSM with MEDI processing showed strong dependence on ΔTE and TE1 , especially at high iron concentrations.ConclusionUTE-QSM is more sensitive than R2* measurement to TE selection. Both an ultrashort TE1 and a small ΔTE are needed to achieve accurate QSM for high iron concentrations. Magn Reson Med 79:2315-2322, 2018. © 2018 International Society for Magnetic Resonance in Medicine.

PurposeTo measure the Reynolds stress tensor using 4D flow MRI, and to evaluate its contribution to computed pressure maps.MethodsA method to assess both velocity and Reynolds stress using 4D flow MRI is presented and evaluated. The Reynolds stress is compared by cross-sectional integrals of the Reynolds stress invariants. Pressure maps are computed using the pressure Poisson equation-both including and neglecting the Reynolds stress.ResultGood agreement is seen for Reynolds stress between computational fluid dynamics, simulated MRI, and MRI experiment. The Reynolds stress can significantly influence the computed pressure loss for simulated (eg, -0.52% vs -15.34% error; P

PurposeTo evaluate the importance of strain-correcting stimulated echo acquisition mode echo-planar imaging cardiac diffusion tensor imaging.MethodsHealthy pigs (n = 11) were successfully scanned with a 3D cine displacement-encoded imaging with stimulated echoes and a monopolar-stimulated echo-planar imaging diffusion tensor imaging sequence at 3 T during diastasis, peak systole, and strain sweet spots in a midventricular short-axis slice. The same diffusion tensor imaging sequence was repeated ex vivo after arresting the hearts in either a relaxed (KCl-induced) or contracted (BaCl2 -induced) state. The displacement-encoded imaging with stimulated echoes data were used to strain-correct the in vivo cardiac diffusion tensor imaging in diastole and systole. The orientation of the primary (helix angles) and secondary (E2A) diffusion eigenvectors was compared with and without strain correction and to the strain-free ex vivo data.ResultsStrain correction reduces systolic E2A significantly when compared without strain correction and ex vivo (median absolute E2A = 34.3° versus E2A = 57.1° (P = 0.01), E2A = 60.5° (P = 0.006), respectively). The systolic distribution of E2A without strain correction is closer to the contracted ex vivo distribution than with strain correction, root mean square deviation of 0.027 versus 0.038.ConclusionsThe current strain-correction model amplifies the contribution of microscopic strain to diffusion resulting in an overcorrection of E2A. Results show that a new model that considers cellular rearrangement is required. Magn Reson Med 79:2205-2215, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

PurposeTo evaluate the echo dependence of 3D ultrashort echo time (TE) quantitative susceptibility mapping (3D UTE-QSM) and effective transverse relaxation rate ( R2*) measurement in the setting of high concentrations of iron oxide nanoparticles.MethodsA phantom study with iron concentrations ranging from 2 to 22 mM was performed using a 3D UTE Cones sequence. Simultaneous QSM processing with morphology-enabled dipole inversion (MEDI) and R2* single exponential fitting was conducted offline with the acquired 3D UTE data. The dependence of UTE-QSM and R2* on echo spacing (ΔTE) and first TE (TE1 ) was investigated.ResultsA linear relationship was observed between UTE-QSM measurement and iron concentration up to 22 mM only, with the minimal TE1 of 0.032 ms and ΔTE of less than 0.1 ms. A linear relationship was observed between R2* and iron concentration up to 22 mM only when TE1 was less than 0.132 ms and ΔTE was less than 1.2 ms. UTE-QSM with MEDI processing showed strong dependence on ΔTE and TE1 , especially at high iron concentrations.ConclusionUTE-QSM is more sensitive than R2* measurement to TE selection. Both an ultrashort TE1 and a small ΔTE are needed to achieve accurate QSM for high iron concentrations. Magn Reson Med 79:2315-2322, 2018. © 2018 International Society for Magnetic Resonance in Medicine.

PurposeTo accelerate the quantitative ultrashort echo time imaging using a time-efficient 3D multispoke Cones sequence with magnetization transfer (3D UTE-Cones-MT) and signal modeling.Theory and methodsA 3D UTE-Cones-MT acquisition scheme with multispoke per MT preparation and a modified rectangular pulse (RP) approximation was developed for two-pool MT modeling of macromolecular and water components including their relative fractions, relaxation times and exchange rates. Numerical simulation and cadaveric specimens, including human Achilles tendon and bovine cortical bone, were investigated using a clinical 3T scanner.ResultsNumerical simulation showed that the modified RP model provided accurate estimation of MT parameters when multispokes were acquired per MT preparation. For the experiment with the Achilles tendon and cortical bone samples, the macromolecular fractions were 20.4 ± 2.0% and 59.4 ± 5.3%, respectively.ConclusionThe 3D multispoke UTE-Cones-MT sequence can be used for fast volumetric assessment of macromolecular and water components in short T2 tissues. Magn Reson Med 79:692-700, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

PurposeThis work presents an approach to mapping the entire lung's proton density and T1 within a single breath-hold and analyzes the apparent T1 when exciting with a spin echo generating pulse in comparison to a standard gradient echo acquisition.MethodsAn inversion-recovery SNAPSHOT-FLASH sequence with a stack-of-stars k-space readout with a golden angle increment was modified to use a spin echo generating radiofrequency-pulse for excitation. Data of five volunteers were acquired on a 3T scanner and image reconstruction was performed by an iterative algorithm adopted from MR-Fingerprinting.ResultsThe feasibility of acquiring quantitative maps of the entire lung with a resolution of 5 × 5 × 10 mm within 7.5 s is demonstrated. It is shown that the proposed spin echo forming radiofrequency-pulse increases the apparent proton density compared to a rectangular pulse. Further, the apparent T1 is reduced in the spin echo case compared to the gradient echo sequence.ConclusionThe proposed spin echo based method results in T1 maps that are comparable to the ones that were acquired with ultra-short echo time sequences elsewhere. The T1 shortening is believed to originate from increased signal contributions of the extra vascular compartment, which has a short T2∗ and T1 . Magn Reson Med 79:960-967, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

PURPOSE:To evaluate a technique for simultaneous quantitative T2 and apparent diffusion coefficient (ADC) mapping in the heart (T2 +ADC) using spin echo (SE) diffusion-weighted imaging (DWI). THEORY AND METHODS:T2 maps from T2 +ADC were compared with single-echo SE in phantoms and with T2 -prepared (T2 -prep) balanced steady-state free precession (bSSFP) in healthy volunteers. ADC maps from T2 +ADC were compared with conventional DWI in phantoms and in vivo. T2 +ADC was also demonstrated in a patient with acute myocardial infarction (MI). RESULTS:Phantom T2 values from T2 +ADC were closer to a single-echo SE reference than T2 -prep bSSFP (-2.3 ± 6.0% vs 22.2 ± 16.3%; P

PurposeTo design and evaluate eddy current-nulled convex optimized diffusion encoding (EN-CODE) gradient waveforms for efficient diffusion tensor imaging (DTI) that is free of eddy current-induced image distortions.MethodsThe EN-CODE framework was used to generate diffusion-encoding waveforms that are eddy current-compensated. The EN-CODE DTI waveform was compared with the existing eddy current-nulled twice refocused spin echo (TRSE) sequence as well as monopolar (MONO) and non-eddy current-compensated CODE in terms of echo time (TE) and image distortions. Comparisons were made in simulations, phantom experiments, and neuro imaging in 10 healthy volunteers.ResultsThe EN-CODE sequence achieved eddy current compensation with a significantly shorter TE than TRSE (78 versus 96 ms) and a slightly shorter TE than MONO (78 versus 80 ms). Intravoxel signal variance was lower in phantoms with EN-CODE than with MONO (13.6 ± 11.6 versus 37.4 ± 25.8) and not different from TRSE (15.1 ± 11.6), indicating good robustness to eddy current-induced image distortions. Mean fractional anisotropy values in brain edges were also significantly lower with EN-CODE than with MONO (0.16 ± 0.01 versus 0.24 ± 0.02, P

PURPOSE:To evaluate a technique for simultaneous quantitative T2 and apparent diffusion coefficient (ADC) mapping in the heart (T2 +ADC) using spin echo (SE) diffusion-weighted imaging (DWI). THEORY AND METHODS:T2 maps from T2 +ADC were compared with single-echo SE in phantoms and with T2 -prepared (T2 -prep) balanced steady-state free precession (bSSFP) in healthy volunteers. ADC maps from T2 +ADC were compared with conventional DWI in phantoms and in vivo. T2 +ADC was also demonstrated in a patient with acute myocardial infarction (MI). RESULTS:Phantom T2 values from T2 +ADC were closer to a single-echo SE reference than T2 -prep bSSFP (-2.3 ± 6.0% vs 22.2 ± 16.3%; P

PurposeTo develop quantitative susceptibility mapping (QSM) of bone using an ultrashort echo time (UTE) gradient echo (GRE) sequence for signal acquisition and a bone-specific effective transverse relaxation rate ( R2*) to model water-fat MR signals for field mapping.MethodsThree-dimensional radial UTE data (echo times ≥ 40 μs) was acquired on a 3 Tesla scanner and fitted with a bone-specific signal model to map the chemical species and susceptibility field. Experiments were performed ex vivo on a porcine hoof and in vivo on healthy human subjects (n = 7). For water-fat separation, a bone-specific model assigning R2* decay mostly to water was compared with the standard models that assigned the same decay for both fat and water. In the ex vivo experiment, bone QSM was correlated with CT.ResultsCompared with standard models, the bone-specific R2* method significantly reduced errors in the fat fraction within the cortical bone in all tested data sets, leading to reduced artifacts in QSM. Good correlation was found between bone CT and QSM values in the porcine hoof (R2  = 0.77). Bone QSM was successfully generated in all subjects.ConclusionsThe QSM of bone is feasible using UTE with a conventional echo time GRE acquisition and a bone-specific R2* signal model. Magn Reson Med 79:121-128, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

PurposeThe diagnostic gold standard for nonalcoholic fatty liver disease is an invasive biopsy. Noninvasive Cartesian MRI fat quantification remains limited to a breath-hold (BH). In this work, a novel free-breathing 3D stack-of-radial (FB radial) liver fat quantification technique is developed and evaluated in a preliminary study.MethodsPhantoms and healthy subjects (n = 11) were imaged at 3 Tesla. The proton-density fat fraction (PDFF) determined using FB radial (with and without scan acceleration) was compared to BH single-voxel MR spectroscopy (SVS) and BH 3D Cartesian MRI using linear regression (correlation coefficient ρ and concordance coefficient ρc ) and Bland-Altman analysis.ResultsIn phantoms, PDFF showed significant correlation (ρ > 0.998, ρc  > 0.995) and absolute mean differences  0.999, ρc  > 0.998) and absolute mean differences  0.986, ρc  > 0.985) and absolute mean differences  0.996, ρc  > 0.995) and absolute mean differences

PurposeTo develop quantitative susceptibility mapping (QSM) of bone using an ultrashort echo time (UTE) gradient echo (GRE) sequence for signal acquisition and a bone-specific effective transverse relaxation rate ( R2*) to model water-fat MR signals for field mapping.MethodsThree-dimensional radial UTE data (echo times ≥ 40 μs) was acquired on a 3 Tesla scanner and fitted with a bone-specific signal model to map the chemical species and susceptibility field. Experiments were performed ex vivo on a porcine hoof and in vivo on healthy human subjects (n = 7). For water-fat separation, a bone-specific model assigning R2* decay mostly to water was compared with the standard models that assigned the same decay for both fat and water. In the ex vivo experiment, bone QSM was correlated with CT.ResultsCompared with standard models, the bone-specific R2* method significantly reduced errors in the fat fraction within the cortical bone in all tested data sets, leading to reduced artifacts in QSM. Good correlation was found between bone CT and QSM values in the porcine hoof (R2  = 0.77). Bone QSM was successfully generated in all subjects.ConclusionsThe QSM of bone is feasible using UTE with a conventional echo time GRE acquisition and a bone-specific R2* signal model. Magn Reson Med 79:121-128, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

PurposeThis study aims to accurately segment the right ventricle (RV) from cardiac MRI using a fully automatic learning-based method.MethodsThe proposed method uses deep learning algorithms, i.e., convolutional neural networks and stacked autoencoders, for automatic detection and initial segmentation of the RV chamber. The initial segmentation is then combined with the deformable models to improve the accuracy and robustness of the process. We trained our algorithm using 16 cardiac MRI datasets of the MICCAI 2012 RV Segmentation Challenge database and validated our technique using the rest of the dataset (32 subjects).ResultsAn average Dice metric of 82.5% along with an average Hausdorff distance of 7.85 mm were achieved for all the studied subjects. Furthermore, a high correlation and level of agreement with the ground truth contours for end-diastolic volume (0.98), end-systolic volume (0.99), and ejection fraction (0.93) were observed.ConclusionOur results show that deep learning algorithms can be effectively used for automatic segmentation of the RV. Computed quantitative metrics of our method outperformed that of the existing techniques participated in the MICCAI 2012 challenge, as reported by the challenge organizers. Magn Reson Med 78:2439-2448, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

PurposeTo evaluate the magnetic susceptibility properties of different anatomical structures within the knee joint using quantitative susceptibility mapping (QSM).MethodsA collagen tissue model was simulated and ex vivo animal cartilage experiments were conducted at 9.4 Tesla (T) to evaluate the B0 orientation-dependent magnetic susceptibility contrast observed in cartilage. Furthermore, nine volunteers (six healthy subjects without knee pain history and three patients with known knee injury, between 29 and 58 years old) were scanned using gradient-echo acquisitions on a high-field 7T MR scanner. Susceptibility values of different tissues were quantified and diseased cartilage and meniscus were compared against that of healthy volunteers.ResultsSimulation and ex vivo animal cartilage experiments demonstrated that collagen fibrils exhibit an anisotropic susceptibility. A gradual change of magnetic susceptibility was observed in the articular cartilage from the superficial zone to the deep zone, forming a multilayer ultrastructure consistent with anisotropy of collagen fibrils. Meniscal tears caused a clear reduction of susceptibility contrast between the injured meniscus and surrounding cartilage illustrated by a loss of the sharp boundaries between the two. Moreover, QSM showed more dramatic contrast in the focal degenerated articular cartilage than R2* mapping.ConclusionThe arrangement of the collagen fibrils is significant, and likely the most dominant source of magnetic susceptibility anisotropy. Quantitative susceptibility mapping offers a means to characterize magnetic susceptibility properties of tissues in the knee joint. It is sensitive to collagen damage or degeneration and may be useful for evaluating the status of knee diseases, such as meniscal tears and cartilage disease. Magn Reson Med 78:1933-1943, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

PurposeTo compare the accuracy and precision of four different T1 estimation algorithms for modified Look-Locker inversion recovery (MOLLI).MethodsFour T1 estimation algorithms, including the original fit, inversion group (IG) fit, instantaneous signal loss simulation (InSiL), and Bloch equation simulation with slice profile correction (BLESSPC) were studied. T1 estimation accuracy, precision, reproducibility, and sensitivity to heart rate (HR), flip angle (FA), and acquisition scheme (AcS) variations were compared in simulation, phantom, and volunteer studies.ResultsT1 estimation accuracy of IG (-2.4% ± 3.9%) and original fit (-3.2% ± 1.4%) were worse than BLESSPC (0.2% ± 1.5%) and InSiL (-0.7% ± 2.1%). The original fit had the best precision for T1 from 409-1884 ms for the same FA (0.67% ± 0.16% versus 0.90% ± 0.23% using IG, 0.78% ± 0.11% using InSiL, 0.77% ± 0.12% using BLESSPC). BLESSPC generated the most consistent in vivo T1 values over different FAs and AcS, and the T1 estimation reproducibility was similar (P > 0.3) among the four methods when FA = 35°. When using FA = 50°, the reproducibility was significantly improved only when using BLESSPC (1.6% ± 0.9 versus 2.6% ± 1.9%, P