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PURPOSE: Inversion algorithms used to convert acquired MR elastography wave data into material property estimates often assume that the underlying materials are locally homogeneous. Here we evaluate the impact of that assumption on stiffness estimates in gray-matter regions of interest in brain MR elastography. METHODS: We describe an updated neural network inversion framework using finite-difference model–derived data to train convolutional neural network inversion algorithms. Neural network inversions trained on homogeneous simulations (homogeneous learned inversions [HLIs]) or inhomogeneous simulations (inhomogeneous learned inversions [ILIs]) are generated with a variety of kernel sizes. These inversions are evaluated in a brain MR elastography simulation experiment and in vivo in a test–retest repeatability experiment including 10 healthy volunteers. RESULTS: In simulation and in vivo, HLI and ILI with small kernels produce similar results. As kernel size increases, the assumption of homogeneity has a larger effect, and HLI and ILI stiffness estimates show larger differences. At each inversion’s optimal kernel size in simulation (7 × 7 × 7 for HLI, 11 × 11 × 11 for ILI), ILI is more sensitive to true changes in stiffness in gray-matter regions of interest in simulation. In vivo, there is no difference in the region-level repeatability of stiffness estimates between the inversions, although ILI appears to better maintain the stiffness map structure as kernel size increases, while decreasing the spatial variance in stiffness estimates. CONCLUSIONS: This study suggests that inhomogeneous inversions provide small but significant benefits even when large stiffness gradients are absent.

Objective. Interleaved reverse-gradient fMRI (RG-fMRI) with a point-spread-function (PSF) mapping-based distortion correction scheme has the potential to minimize signal loss in echo-planar-imaging (EPI). In this work, the RG-fMRI is further improved by imaging protocol optimization and application of reverse Fourier acquisition. Approach. Multi-band imaging was adapted for RG-fMRI to improve the temporal and spatial resolution. To better understand signal dropouts in forward and reverse EPIs, a simple theoretical relationship between echo shift and geometric distortion was derived and validated by the reliable measurements using PSF mapping method. After examining practical imaging protocols for RG-fMRI in three subjects on both a conventional whole-body and a high-performance compact 3 T, the results were compared and the feasibility to further improve the RG-fMRI scheme were explored. High-resolution breath-holding RG-fMRI was conducted with nine subjects on the compact 3 T and the fMRI reliability improvement in high susceptibility brain regions was demonstrated. Finally, reverse Fourier acquisition was applied to RG-fMRI, and its benefit was assessed by a simulation study based on the breath-holding RG-fMRI data. Main results. The temporal and spatial resolution of the multi-band RG-fMRI became feasible for whole-brain fMRI. Echo shift measurements from PSF mapping well estimated signal dropout effects in the EPI pair and were useful to further improve the RG-fMRI scheme. Breath-holding RG-fMRI demonstrated improved fMRI reliability in high susceptibility brain regions. Reverse partial Fourier acquisition omitting the late echoes could further improve the temporal or spatial resolution for RG-fMRI without noticeable signal degradation and spatial resolution loss. Significance. With the improved imaging scheme, RG-fMRI could reliably investigate the functional mechanisms of the human brain in the temporal and frontal areas suffering from susceptibility-induced functional sensitivity loss.

BACKGROUND A low-cryogen, compact 3T (C3T) MRI scanner with high-performance gradients capable of simultaneously achieving 80 mT/m gradient amplitude and 700 T/m/second slew rate has been in use to study research patients since March 2016 but has not been implemented in the clinical practice. PURPOSE To compare head MRI examinations obtained with the C3T system and a conventional whole-body 3T (WB3T) scanner in seven parameters across five commonly used brain imaging sequences. STUDY TYPE Prospective. SUBJECTS Thirty patients with a clinically indicated head MRI. SEQUENCE 3T; T1 FLAIR, T1 MP-RAGE, 3D T2 FLAIR, T2 FSE, and DWI. ASSESSMENT All patients tolerated the scans well. Three board-certified neuroradiologists scored the comparative quality of C3T and WB3T images in blinded fashion using a five-point Likert scale in terms of: signal-to-noise ratio, lesion conspicuity, motion artifact, gray/white matter contrast, cerebellar folia, susceptibility artifact, and overall quality. STATISTICAL TEST Left-sided, right-sided, and two-sided Wilcoxon signed rank test; Fisher's method. A P value

Purpose To address the need for a method to acquire 3D data for MR elastography (MRE) of the whole brain with substantially improved spatial resolution, high SNR, and reduced acquisition time compared with conventional methods. Methods We combined a novel 3D spiral staircase data-acquisition method with a spoiled gradient-echo pulse sequence and MRE motion-encoding gradients (MEGs). The spiral-out acquisition permitted use of longer-duration motion-encoding gradients (ie, over two full oscillatory cycles) to enhance displacement SNR, while still maintaining a reasonably short TE for good phase-SNR. Through-plane parallel imaging with low noise penalties was implemented to accelerate acquisition along the slice direction. Shared anatomical information was exploited in the deblurring procedure to further boost SNR for stiffness inversion. Results In vivo and phantom experiments demonstrated the feasibility of the proposed method in producing brain MRE results comparable to the spin-echo-based approaches, both qualitatively and quantitatively. High-resolution (2-mm isotropic) brain MRE data were acquired in 5 minutes using our method with good SNR. Joint deblurring with shared anatomical information produced SNR-enhanced images, leading to upward stiffness estimation. Conclusion A novel 3D gradient-echo-based approach has been designed and implemented, and shown to have promising potential for fast and high-resolution in vivo MRE of the whole brain.

OBJECTIVE. The Adaptive Image Receive (AIR) radiofrequency coil is an emergent technology that is lightweight and flexible and exhibits electrical characteristics that overcome many of the limitations of traditional rigid coil designs. The purpose of this study was to apply the AIR coil for whole-brain imaging and compare the performance of a prototype AIR coil array with the performance of conventional head coils. SUBJECTS AND METHODS. A phantom and 15 healthy adult participants were imaged. A prototype 16-channel head AIR coil was compared with conventional 8- and 32-channel head coils using clinically available MRI sequences. During consensus review, two board-certified neuroradiologists graded the AIR coil compared with an 8-channel coil and a 32-channel coil on a 5-point ordinal scale in multiple categories. One- and two-sided Wilcoxon signed rank tests were performed. Noise covariance matrices and geometry factor (g-factor) maps were calculated. RESULTS. The signal-to-noise ratio, structural sharpness, and overall image quality scores of the prototype 16-channel AIR coil were better than those of the 8-channel coil but were not as good as those of the 32-channel coil. Noise covariance matrices showed stable performance of the AIR coil across participants. The median g-factors for the 16-channel AIR coil were, overall, less than those of the 8-channel coil but were greater than those of the 32-channel coil. CONCLUSION. On average, the prototype 16-channel head AIR coil outperformed a conventional 8-channel head coil but did not perform as well as a conventional 32-channel head coil. This study shows the feasibility of the novel AIR coil technology for imaging the brain and provides insight for future coil design improvements.

Objective. Ultrasound attenuation coefficient estimation (ACE) has diagnostic potential for clinical applications such as quantifying fat content in the liver. Previously, we have proposed a system-independent ACE technique based on spectral normalization of different frequencies, called the reference frequency method (RFM). This technique does not require a well-calibrated reference phantom for normalization. However, this method may be vulnerable to severe reverberation clutter introduced by the body wall. The clutter superimposed on liver echoes may bias the estimation. Approach. We proposed to use robust principal component analysis, combined with wavelet-based sparsity promotion, to suppress the severe reverberation clutters. The capability to mitigate the reverberation clutters was validated through phantom and in vivo studies. Main Results. In the phantom studies with added reverberation clutters, higher normalized cross-correlation and smaller mean absolute errors were attained as compared to RFM results without the proposed method, demonstrating the capability to reconstruct tissue signals from reverberations. In a pilot patient study, the correlation between ACE and proton density fat fraction (PDFF), a measurement of liver fat by MRI as a reference standard, was investigated. The proposed method showed an improvement of the correlation (coefficient of determination, R = 0.82) as compared with the counterpart without the proposed method (R = 0.69). Significance: The proposed method showed the feasibility of suppressing the reverberation clutters, providing an important basis for the development of a robust ACE with large reverberation clutters.

OBJECTIVES The aim of this study was to perform a whole-brain analysis of alterations in brain mechanical properties due to normal pressure hydrocephalus (NPH). MATERIALS AND METHODS Magnetic resonance elastography (MRE) examinations were performed on 85 participants, including 44 cognitively unimpaired controls, 33 with NPH, and 8 who were amyloid-positive with Alzheimer clinical syndrome. A custom neural network inversion was used to estimate stiffness and damping ratio from patches of displacement data, accounting for edges by training the network to estimate the mechanical properties in the presence of missing data. This learned inversion was first compared with a standard analytical approach in simulation experiments and then applied to the in vivo MRE measurements. The effect of NPH on the mechanical properties was then assessed by voxel-wise modeling of the stiffness and damping ratio maps. Finally, a pattern analysis was performed on each individual's mechanical property maps by computing the correlation between each person's maps with the expected NPH effect. These features were used to fit a classifier and assess diagnostic accuracy. RESULTS The voxel-wise analysis of the in vivo mechanical property maps revealed a unique pattern in participants with NPH, including a concentric pattern of stiffening near the dural surface and softening near the ventricles, as well as decreased damping ratio predominantly in superior regions of the white matter (family-wise error corrected P < 0.05 at cluster level). The pattern of viscoelastic changes in each participant predicted NPH status in this cohort, separating participants with NPH from the control and the amyloid-positive with Alzheimer clinical syndrome groups, with areas under the receiver operating characteristic curve of 0.999 and 1, respectively. CONCLUSIONS This study provides motivation for further development of the neural network inversion framework and demonstrates the potential of MRE as a novel tool to diagnose NPH and provide a window into its pathogenesis.

ObjectiveThis study investigates a locally low-rank (LLR) denoising algorithm applied to source images from a clinical task-based functional MRI (fMRI) exam before post-processing for improving statistical confidence of task-based activation maps.MethodsTask-based motor and language fMRI was obtained in eleven healthy volunteers under an IRB approved protocol. LLR denoising was then applied to raw complex-valued image data before fMRI processing. Activation maps generated from conventional non-denoised (control) data were compared with maps derived from LLR-denoised image data. Four board-certified neuroradiologists completed consensus assessment of activation maps; region-specific and aggregate motor and language consensus thresholds were then compared with nonparametric statistical tests. Additional evaluation included retrospective truncation of exam data without and with LLR denoising; a ROI-based analysis tracked t-statistics and temporal SNR (tSNR) as scan durations decreased. A test-retest assessment was performed; retest data were matched with initial test data and compared for one subject.ResultsfMRI activation maps generated from LLR-denoised data predominantly exhibited statistically significant ( p = 4.88×10–4to p = 0.042; one p = 0.062) increases in consensus t-statistic thresholds for motor and language activation maps. Following data truncation, LLR data showed task-specific increases in t-statistics and tSNR respectively exceeding 20 and 50% compared to control. LLR denoising enabled truncation of exam durations while preserving cluster volumes at fixed thresholds. Test-retest showed variable activation with LLR data thresholded higher in matching initial test data.ConclusionLLR denoising affords robust increases in t-statistics on fMRI activation maps compared to routine processing, and offers potential for reduced scan duration while preserving map quality.

Objective The quality of all clinical MRI is dependent on B0 homogeneity, which is optimized during the shimming part of a prescan or preparatory phase before image acquisition. The purpose of this study was to assess shimming techniques clinically employed for breast MRI across our practice, and to determine factors that correlate with higher image quality for contrast-enhanced breast MRI at 1.5T. Methods One hundred consecutive female patients were retrospectively collected with Institutional Review Board approval. Shimming-related parameters, including shim-box placement and shimming gradient offsets were extracted from prior contrast-enhanced 3D fat-suppressed T1-weighted gradient echo image acquisitions. Three breast radiologists evaluated these images for fat saturation, breast density, overall image quality, and artifacts. Technologist experience was also evaluated for variability of shimming. Generalized linear mixed models were used to compare acquisition parameters between fat saturation. P < 0.05 was considered as statistical significance. Results The percentage of soft tissue inside the field of view (FOV) (ie, Tissue/FOV) in the good fat-saturation group (0.37 ± 0.06) was significantly lower (P < 0.01) than that in the poor fat-saturation group (0.39 ± 0.06). Other shimming-related parameters were found not significantly affecting the fat-saturation outcomes. Technologists with more experience tended to have less variable shimming performance than junior technologists did. Conclusions The quality of clinical MRI and especially breast MRI is highly dependent on shimming. Decreasing Tissue/FOV was associated with good image quality (good fat saturation). Optimization of shimming may require manual shimming or higher-order field-correction strategies.

Background Distortion-free, high-resolution diffusion imaging using DIADEM (Distortion-free Imaging: A Double Encoding Method), proposed recently, has great potential for clinical applications. However, it can suffer from prolonged scan times and its reliability for quantitative diffusion imaging has not been evaluated. Purpose To investigate the clinical feasibility of DIADEM-based high-resolution diffusion imaging on a novel compact 3T (C3T) by evaluating the reliability of quantitative diffusion measurements and utilizing both the high-performance gradients (80 mT/m, 700 T/m/s) and the sequence optimization with the navigator acquisition window reduction and simultaneous multislice (multiband) imaging. Study type Prospective feasibility study. Phantom/subjects Diffusion quality control phantom scans to evaluate the reliability of quantitative diffusion measurements; 36 normal control scans for B0 -field mapping; six healthy and two patient subject scans with a brain tumor for comparisons of diffusion and anatomical imaging. Field strength/sequence 3T; the standard single-shot echo-planar-imaging (EPI), multishot DIADEM diffusion, and anatomical (2D-FSE [fast-spin-echo], 2D-FLAIR [fluid-attenuated-inversion-recovery], and 3D-MPRAGE [magnetization prepared rapid acquisition gradient echo]) imaging. Assessment The scan time reduction, the reliability of quantitative diffusion measurements, and the clinical efficacy for high-resolution diffusion imaging in healthy control and brain tumor volunteers. Statistical test Bland-Altman analysis. Results The scan time for high in-plane (0.86 mm2 ) resolution, distortion-free, and whole brain diffusion imaging were reduced from 10 to 5 minutes with the sequence optimizations. All of the mean apparent diffusion coefficient (ADC) values in phantom were within the 95% confidence interval in the Bland-Altman plot. The proposed acquisition with a total off-resonance coverage of 597.2 Hz wider than the expected bandwidth of 500 Hz in human brain could yield a distortion-free image without foldover artifacts. Compared with EPI, therefore, this approach allowed direct image matching with the anatomical images and enabled improved delineation of the tumor boundaries. Data conclusion The proposed high-resolution diffusion imaging approach is clinically feasible on C3T due to a combination of hardware and sequence improvements. Level of evidence 3 TECHNICAL EFFICACY: Stage 1 J. Magn. Reson. Imaging 2020;51:296-310.

BACKGROUND AND PURPOSE Neurodegeneration of the substantia nigra in Lewy body disease is associated with iron deposition, which increases the magnetic susceptibility of the substantia nigra on MRI. Our objective was to measure iron deposition in the substantia nigra in patients with probable dementia with Lewy bodies (pDLB) and patients who are at risk for pDLB by quantitative susceptibility mapping (QSM). METHODS Participants included pDLB (n = 36), mild cognitive impairment with at least one core feature of DLB (MCI-LB; n = 15), idiopathic rapid eye movement sleep behavior disorder (iRBD; n = 11), and an age-and gender-matched clinically unimpaired control group (n = 102). QSM was derived from multi-echo 3D gradient recalled echo MRI at 3T, and groups were compared on mean susceptibility values of the substantia nigra and its relation to parkinsonism severity. RESULTS Patients with pDLB had higher susceptibility in the substantia nigra compared to controls (p< 0.001) and MCI-LB (p = 0.043). The susceptibility of substantia nigra showed an increasing trend from controls to iRBD and MCI-LB, and to pDLB (p< 0.001). Parkinsonism severity was not associated with the mean susceptibility in the substantia nigra in the patient groups. CONCLUSIONS Our data suggested that QSM is sensitive to the increased magnetic susceptibility due to higher iron content in the substantia nigra in pDLB. The trend of increasing susceptibility from controls to iRBD and MCI-LB, and to pDLB suggests that iron deposition in the substantia nigra starts to increase as early as the prodromal stage in DLB and continues to increase as the disease progresses, independent of parkinsonism severity.

Improved gradient performance in an MRI system reduces distortion in echo planar imaging (EPI), which has been a key imaging method for functional studies. A lightweight, low-cryogen compact 3T MRI scanner (C3T) is capable of achieving 80 mT m−1 gradient amplitude with 700 T m−1 s−1 slew rate, in comparison with a conventional whole-body 3T MRI scanner (WB3T, 50 mT m−1 with 200 T m−1 s−1). We investigated benefits of the high-performance gradients in a high-spatial-resolution (1.5 mm isotropic) functional MRI study. Reduced echo spacing in the EPI pulse sequence inherently leads to less severe geometric distortion, which provided higher accuracy than with WB3T for registration between EPI and anatomical images. The cortical coverage of C3T datasets was improved by more accurate signal depiction (i.e. less dropout or pile-up). Resting-state functional analysis results showed that greater magnitude and extent in functional connectivity (FC) for the C3T than the WB3T when the selected seed region is susceptible to distortions, while the FC matrix for well-known brain networks showed little difference between the two scanners. This shows that the improved quality in EPI is particularly valuable for studying certain brain regions typically obscured by severe distortion.

Ultrasound localization microscopy (ULM) has been proposed to image microvasculature beyond the ultrasound diffraction limit. Although ULM can attain microvascular images with a sub-diffraction resolution, long data acquisition time and processing time are the critical limitations. Deep learning-based ULM (deep-ULM) has been proposed to mitigate these limitations. However, microbubble (MB) localization used in deep-ULMs is currently based on spatial information without the use of temporal information. The highly spatiotemporally coherent MB signals provide a strong feature that can be used to differentiate MB signals from background artifacts. In this study, a deep neural network was employed and trained with spatiotemporal ultrasound datasets to better identify the MB signals by leveraging both the spatial and temporal information of the MB signals. Training, validation and testing datasets were acquired from MB suspension to mimic the realistic intensity-varying and moving MB signals. The performance of the proposed network was first demonstrated in the chicken embryo chorioallantoic membrane dataset with an optical microscopic image as the reference standard. Substantial improvement in spatial resolution was shown for the reconstructed super-resolved images compared with power Doppler images. The full-width-half-maximum (FWHM) of a microvessel was improved from 133 μm to 35 μm, which is smaller than the ultrasound wavelength (73 μm). The proposed method was further tested in an in vivo human liver data. Results showed the reconstructed super-resolved images could resolve a microvessel of nearly 170 μm (FWHM). Adjacent microvessels with a distance of 670 μm, which cannot be resolved with power Doppler imaging, can be well-separated with the proposed method. Improved contrast ratios using the proposed method were shown compared with that of the conventional deep-ULM method. Additionally, the processing time to reconstruct a high-resolution ultrasound frame with an image size of 1024 × 512 pixels was around 16 ms, comparable to state-of-the-art deep-ULMs.

Purpose To develop a novel magnetic resonance elastography (MRE) acquisition using a hybrid radial EPI readout scheme (TURBINE), and to demonstrate its feasibility to obtain wave images and stiffness maps in a phantom and in vivo brain. Method The proposed 3D TURBINE-MRE is based on a spoiled gradient-echo MRE sequence with the EPI readout radially rotating about the phase-encoding axis to sample a full 3D k-space. A polyvinyl chloride phantom and 6 volunteers were scanned on a compact 3T GE scanner with a 32-channel head coil at 80 Hz and 60 Hz external vibration, respectively. For comparison, a standard 2D, multislice, spin-echo (SE) EPI-MRE acquisition was also performed with the same motion encoding and resolution. The TURBINE-MRE images were off-line reconstructed with iterative SENSE algorithm. The regional ROI analysis was performed on the 6 volunteers, and the median stiffness values were compared between SE-EPI-MRE and TURBINE-MRE. Results The 3D wave-field images and the generated stiffness maps were comparable between TURBINE-MRE and standard SE-EPI-MRE for the phantom and the volunteers. The Bland-Altman plot showed no significant difference in the median regional stiffness values between the two methods. The stiffness measured with the 2 methods had a strong linear relationship with a Pearson correlation coefficient of 0.943. Conclusion We demonstrated the feasibility of the new TURBINE-MRE sequence for acquiring the desired 3D wave-field data and stiffness maps in a phantom and in-vivo brains. This pilot study encourages further exploration of TURBINE-MRE for functional MRE, free-breathing abdominal MRE, and cardiac MRE applications.

Singular value decomposition-based clutter filters can robustly reject tissue clutter, allowing for detection of slow blood flow in imaging microvasculature. However, to identify microvessels, high ultrasound frequency must be used to increase the spatial resolution at the expense of shorter depth of penetration. Deconvolution using Tikhonov regularization is an imaging processing method widely used to improve spatial resolution. The ringing artifact of Tikhonov regularization, though, can produce image artifacts such as non-existent microvessels, which degrade image quality. Therefore, a deconvolution method using total variation is proposed in this study to improve spatial resolution and mitigate the ringing artifact. Performance of the proposed method was evaluated using chicken embryo brain, ex ovo chicken embryo chorioallantoic membrane and tumor data. Results revealed that the reconstructed power Doppler (PD) images are substantially improved in spatial resolution compared with original PD images: the full width half-maximum (FWHM) of the cross-sectional profile of a microvessel was improved from 132 to 83 μm. Two neighboring microvessels that were 154 μm apart were better separated using the proposed method than conventional PD imaging. Additionally, 223 FWHMs measured from the cross-sectional profiles of 223 vessels were used to determine the improvement in FWHM with the proposed method statistically. The mean ± standard deviation of the FWHM without and with the proposed method was 233.19 ± 85.08 and 172.31 ± 75.11 μm, respectively; the maximum FWHM without and with the proposed method was 693.01 and 668.69 μm; and the minimum FWHM without and with the proposed method was 73.92 and 45.74 μm. There were statistically significant differences between FWHMs with and without the proposed method according to the rank-sum test, p < 0.0001. The contrast-to-noise ratio improved from 1.06 to 4.03 dB with use of the proposed method. We also compared the proposed method with Tikhonov regularization using ex ovo chicken embryo chorioallantoic membrane data. We found that the proposed method outperformed Tikhonov regularization as false microvessels appeared using the Tikhonov regularization but not with the proposed method. These results indicate that the proposed method is capable of providing more robust PD images with higher spatial resolution and higher contrast-to-noise ratio.

Background Gradient nonlinearity (GNL) leads to biased apparent diffusion coefficients (ADCs) in diffusion-weighted imaging. A gradient nonlinearity correction (GNLC) method has been developed for whole body systems, but is yet to be tested for the new compact 3T (C3T) scanner, which exhibits more complex GNL due to its asymmetrical design. Purpose To assess the improvement of ADC quantification with GNLC for the C3T scanner. Study type Phantom measurements and retrospective analysis of patient data. Phantom/subjects A diffusion quality control phantom with vials containing 0-30% polyvinylpyrrolidone in water was used. For in vivo data, 12 patient exams were analyzed (median age, 33). Field strength/sequence Imaging was performed on the C3T and two commercial 3T scanners. A clinical DWI (repetition time [TR] = 10,000 msec, echo time [TE] = minimum, b = 1000 s/mm2 ) sequence was used for phantom imaging and 10 patient cases and a clinical DTI (TR = 6000-10,000 msec, TE = minimum, b = 1000 s/mm2 ) sequence was used for two patient cases. Assessment The 0% vial was measured along three orthogonal axes, and at two different temperatures. The ADC for each concentration was compared between the C3T and two whole-body scanners. Cerebrospinal fluid and white matter ADCs were quantified for each patient and compared to values in literature. Statistical tests Paired t-test and two-way analysis of variance (ANOVA). Results For all PVP concentrations, the corrected ADC was within 2.5% of the reference ADC. On average, the ADC of cerebrospinal fluid and white matter post-GNLC were within 1% and 6%, respectively, of values reported in the literature and were significantly different from the uncorrected data (P Data conclusion This study demonstrated that GNL effects were more severe for the C3T due to the asymmetric gradient design, but our implementation of a GNLC compensated for these effects, resulting in ADC values that are in good agreement with values from the literature. Level of evidence 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:1498-1507.

Purpose To introduce newly developed MR elastography (MRE)-based dual-saturation imaging and dual-sensitivity motion encoding schemes to directly measure in vivo skull-brain motion, and to study the skull-brain coupling in volunteers with these approaches. Methods Six volunteers were scanned with a high-performance compact 3T-MRI scanner. The skull-brain MRE images were obtained with a dual-saturation imaging where the skull and brain motion were acquired with fat- and water-suppression scans, respectively. A dual-sensitivity motion encoding scheme was applied to estimate the heavily wrapped phase in skull by the simultaneous acquisition of both low- and high-sensitivity phase during a single MRE exam. The low-sensitivity phase was used to guide unwrapping of the high-sensitivity phase. The amplitude and temporal phase delay of the rigid-body motion between the skull and brain was measured, and the skull-brain interface was visualized by slip interface imaging (SII). Results Both skull and brain motion can be successfully acquired and unwrapped. The skull-brain motion analysis demonstrated the motion transmission from the skull to the brain is attenuated in amplitude and delayed. However, this attenuation (%) and delay (rad) were considerably greater with rotation (59 ± 7%, 0.68 ± 0.14 rad) than with translation (92 ± 5%, 0.04 ± 0.02 rad). With SII the skull-brain slip interface was not completely evident, and the slip pattern was spatially heterogeneous. Conclusion This study provides a framework for acquiring in vivo voxel-based skull and brain displacement using MRE that can be used to characterize the skull-brain coupling system for understanding of mechanical brain protection mechanisms, which has potential to facilitate risk management for future injury.

Purpose To build and evaluate a small-footprint, lightweight, high-performance 3T MRI scanner for advanced brain imaging with image quality that is equal to or better than conventional whole-body clinical 3T MRI scanners, while achieving substantial reductions in installation costs. Methods A conduction-cooled magnet was developed that uses less than 12 liters of liquid helium in a gas-charged sealed system, and standard NbTi wire, and weighs approximately 2000 kg. A 42-cm inner-diameter gradient coil with asymmetric transverse axes was developed to provide patient access for head and extremity exams, while minimizing magnet-gradient interactions that adversely affect image quality. The gradient coil was designed to achieve simultaneous operation of 80-mT/m peak gradient amplitude at a slew rate of 700 T/m/s on each gradient axis using readily available 1-MVA gradient drivers. Results In a comparison of anatomical imaging in 16 patients using T2 -weighted 3D fluid-attenuated inversion recovery (FLAIR) between the compact 3T and whole-body 3T, image quality was assessed as equivalent to or better across several metrics. The ability to fully use a high slew rate of 700 T/m/s simultaneously with 80-mT/m maximum gradient amplitude resulted in improvements in image quality across EPI, DWI, and anatomical imaging of the brain. Conclusions The compact 3T MRI system has been in continuous operation at the Mayo Clinic since March 2016. To date, over 200 patient studies have been completed, including 96 comparison studies with a clinical 3T whole-body MRI. The increased gradient performance has reliably resulted in consistently improved image quality.

Purpose Dixon-based fat suppression has recently gained interest for dynamic contrast-enhanced MRI, but multi-echo techniques require longer scan times and reduce temporal resolution compared to single-echo alternatives without fat suppression. The purpose of this work is to demonstrate accelerated single-echo Dixon imaging with high spatial and temporal resolution. Theory and methods Real-valued water and fat images can be obtained from a single measurement if the shared initial phase and that due to ΔB0 are assumed known a priori. An expression for simultaneous sensitivity encoding (SENSE) unfolding and fat-water separation is derived for the general undersampling case, and simplified under the special case of uniform Cartesian undersampling. In vivo experiments were performed in extremities and brain with SENSE acceleration factors of up to R = 8. Results Single-echo Dixon reconstruction of highly undersampled data was successfully demonstrated. Dynamic contrast-enhanced water and fat images provided high spatial and temporal resolution dynamic images with image update times shorter than previous single-echo Dixon work. Conclusion Time-resolved contrast-enhanced MRI with single-echo Dixon fat suppression shows high image quality, improved vessel delineation, and reduced sensitivity to motion when compared to time-subtraction methods.

PURPOSE To implement a reduced field of view (rFOV) technique for cardiac MR elastography (MRE) and to demonstrate the improvement in image quality of both magnitude images and post-processed MRE stiffness maps compared to the conventional full field of view (full-FOV) acquisition. METHODS With Institutional Review Board approval, 17 healthy volunteers underwent both full-FOV and rFOV cardiac MRE scans using 140-Hz vibrations. Two cardiac radiologists blindly compared the magnitude images and stiffness maps and graded the images based on several image quality attributes using a 5-point ordinal scale. Fisher's combined probability test was performed to assess the overall evaluation. The octahedral shear strain-based signal-to-noise ratio (OSS-SNR) and median stiffness over the left ventricular myocardium were also compared. RESULTS One volunteer was excluded because of an inconsistent imaging resolution during the exam. In the remaining 16 volunteers (9 males, 7 females), the rFOV scans outperformed the full-FOV scans in terms of subjective image quality and ghosting artifacts in the magnitude images and stiffness maps, as well as the overall preference. The quantitative measurements showed that rFOV had significantly higher OSS-SNR (median: 1.4 [95% confidence interval (CI): 1.2-1.5] vs. 2.1 [95% CI: 1.8-2.4]), P

Purpose To investigate the feasibility of using artificial neural networks to estimate stiffness from MR elastography (MRE) data. Methods Artificial neural networks were fit using model-based training patterns to estimate stiffness from images of displacement using a patch size of ∼1 cm in each dimension. These neural network inversions (NNIs) were then evaluated in a set of simulation experiments designed to investigate the effects of wave interference and noise on NNI accuracy. NNI was also tested in vivo, comparing NNI results against currently used methods. Results In 4 simulation experiments, NNI performed as well or better than direct inversion (DI) for predicting the known stiffness of the data. Summary NNI results were also shown to be significantly correlated with DI results in the liver (R2 = 0.974) and in the brain (R2 = 0.915), and also correlated with established biological effects including fibrosis stage in the liver and age in the brain. Finally, repeatability error was lower in the brain using NNI compared to DI, and voxel-wise modeling using NNI stiffness maps detected larger effects than using DI maps with similar levels of smoothing. Conclusion Artificial neural networks represent a new approach to inversion of MRE data. Summary results from NNI and DI are highly correlated and both are capable of detecting biologically relevant signals. Preliminary evidence suggests that NNI stiffness estimates may be more resistant to noise than an algebraic DI approach. Taken together, these results merit future investigation into NNIs to improve the estimation of stiffness in small regions. Magn Reson Med 80:351-360, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

The MRI community is using quantitative mapping techniques to complement qualitative imaging. For quantitative imaging to reach its full potential, it is necessary to analyze measurements across systems and longitudinally. Clinical use of quantitative imaging can be facilitated through adoption and use of a standard system phantom, a calibration/standard reference object, to assess the performance of an MRI machine. The International Society of Magnetic Resonance in Medicine AdHoc Committee on Standards for Quantitative Magnetic Resonance was established in February 2007 to facilitate the expansion of MRI as a mainstream modality for multi-institutional measurements, including, among other things, multicenter trials. The goal of the Standards for Quantitative Magnetic Resonance committee was to provide a framework to ensure that quantitative measures derived from MR data are comparable over time, between subjects, between sites, and between vendors. This paper, written by members of the Standards for Quantitative Magnetic Resonance committee, reviews standardization attempts and then details the need, requirements, and implementation plan for a standard system phantom for quantitative MRI. In addition, application-specific phantoms and implementation of quantitative MRI are reviewed. Magn Reson Med 79:48-61, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Purpose To investigate the effect of the asymmetric gradient concomitant fields (CF) with zeroth and first-order spatial dependence on fast/turbo spin-echo acquisitions, and to demonstrate the effectiveness of their real-time compensation. Methods After briefly reviewing the CF produced by asymmetric gradients, the effects of the additional zeroth and first-order CFs on these systems are investigated using extended-phase graph simulations. Phantom and in vivo experiments are performed to corroborate the simulation. Experiments are performed before and after the real-time compensations using frequency tracking and gradient pre-emphasis to demonstrate their effectiveness in correcting the additional CFs. The interaction between the CFs and prescan-based correction to compensate for eddy currents is also investigated. Results It is demonstrated that, unlike the second-order CFs on conventional gradients, the additional zeroth/first-order CFs on asymmetric gradients cause substantial signal loss and dark banding in fast spin-echo acquisitions within a typical brain-scan field of view. They can confound the prescan correction for eddy currents and degrade image quality. Performing real-time compensation successfully eliminates the artifacts. Conclusions We demonstrate that the zeroth/first-order CFs specific to asymmetric gradients can cause substantial artifacts, including signal loss and dark bands for brain imaging. These effects can be corrected using real-time compensation. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Purpose Imaging gradients result in the generation of concomitant fields, or Maxwell fields, which are of increasing importance at higher gradient amplitudes. These time-varying fields cause additional phase accumulation, which must be compensated for to avoid image artifacts. In the case of gradient systems employing symmetric design, the concomitant fields are well described with second-order spatial variation. Gradient systems employing asymmetric design additionally generate concomitant fields with global (zeroth-order or B0) and linear (first-order) spatial dependence. Methods This work demonstrates a general solution to eliminate the zeroth-order concomitant field by applying the correct B0 frequency shift in real time to counteract the concomitant fields. Results are demonstrated for phase contrast, spiral, echo-planar imaging (EPI), and fast spin-echo imaging. Results A global phase offset is reduced in the phase-contrast exam, and blurring is virtually eliminated in spiral images. The bulk image shift in the phase-encode direction is compensated for in EPI, whereas signal loss, ghosting, and blurring are corrected in the fast-spin echo images. Conclusion A user-transparent method to compensate the zeroth-order concomitant field term by center frequency shifting is proposed and implemented. This solution allows all the existing pulse sequences—both product and research—to be retained without any modifications. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

To assess whether acquisition with 32 receiver coils rather than the vendor-recommended 12 coils provides significantly improved performance in 3D dynamic contrast-enhanced MRI (DCE-MRI) of the prostate.The study was approved by the institutional review board and was compliant with HIPAA. 50 consecutive male patients in whom prostate MRI was clinically indicated were prospectively imaged in March 2015 with an accelerated DCE-MRI sequence in which image reconstruction was performed using 12 and 32 coil elements. The two reconstructions were compared quantitatively and qualitatively. The first was done using signal-to-noise ratio (SNR) and g-factor analysis to assess sensitivity to acceleration. The second was done using a five-point scale by two experienced radiologists using criteria of perceived SNR, artifact, sharpness, and overall preference. Significance was assessed with the Wilcoxon signed rank test. Extension to T2-weighted spin-echo and diffusion sequences was assessed in phantom studies.Reconstruction using 32 vs. 12 coil elements provided improved performance in DCE-MRI based on intrinsic SNR (18% higher) and g-factor statistics (14% higher), with a median 32% higher overall SNR within the prostate volume over all subjects. Reconstruction using 32 coils was qualitatively rated significantly improved (p0.001) vs. 12 coils on the basis of perceived SNR and radiologist preference and equivalent for sharpness and artifact. Phantom studies suggested the improvement in intrinsic SNR could extend to T2-weighted spin-echo and diffusion sequences.Reconstruction of 3D accelerated DCE-MRI studies of the prostate using 32 independent receiver coils provides improved overall performance vs. using 12 coils.

Purpose The homeostasis of intracranial pressure (ICP) is of paramount importance for maintaining normal brain function. A noninvasive technique capable of making direct measurements of ICP currently does not exist. MR elastography (MRE) is capable of noninvasively measuring brain tissue stiffness in vivo, and may act as a surrogate to measure ICP. The objective of this study was to investigate the impact of changing ICP on brain stiffness using MRE in a swine model. Methods Baseline MRE measurements were obtained, and then catheters were surgically placed into the left and right lateral ventricles of three animals. ICP was systematically increased over the range of 0 to 55 millimeters mercury (mmHg), and stiffness measurements were made using brain MRE at vibration frequencies of 60 hertz (Hz), 90 Hz, 120 Hz, and 150 Hz. Results A significant linear correlation between stiffness and ICP in the cross-subject comparison was observed for all tested vibrational frequencies (P ≤ 0.01). The 120 Hz (0.030 ± 0.004 kilopascal (kPa)/mmHg, P

Purpose The stiffness of a myocardial infarct affects the left ventricular pump function and remodeling. Magnetic resonance elastography (MRE) is a noninvasive imaging technique for measuring soft-tissue stiffness in vivo. The purpose of this study was to investigate the feasibility of assessing in vivo regional myocardial stiffness with high-frequency 3D cardiac MRE in a porcine model of myocardial infarction, and compare the results with ex vivo uniaxial tensile testing. Methods Myocardial infarct was induced in a porcine model by embolizing the left circumflex artery. Fourteen days postinfarction, MRE imaging was performed in diastole using an echocardiogram-gated spin-echo echo-planar-imaging sequence with 140-Hz vibrations and 3D MRE processing. The MRE stiffness and tensile modulus from uniaxial testing were compared between the remote and infarcted myocardium. Results Myocardial infarcts showed increased in vivo MRE stiffness compared with remote myocardium (4.6 ± 0.7 kPa versus 3.0 ± 0.6 kPa, P = 0.02) within the same pig. Ex vivo uniaxial mechanical testing confirmed the in vivo MRE results, showing that myocardial infarcts were stiffer than remote myocardium (650 ± 80 kPa versus 110 ± 20 kPa, P = 0.01). Conclusions These results demonstrate the feasibility of assessing in vivo regional myocardial stiffness with high-frequency 3D cardiac MRE. Magn Reson Med, 2017. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Purpose To evaluate if cardiac magnetic resonance elastography (MRE) can measure increased stiffness in patients with cardiac amyloidosis. Myocardial tissue stiffness plays an important role in cardiac function. A noninvasive quantitative imaging technique capable of measuring myocardial stiffness could aid in disease diagnosis, therapy monitoring, and disease prognostic strategies. We recently developed a high-frequency cardiac MRE technique capable of making noninvasive stiffness measurements. Materials and Methods In all, 16 volunteers and 22 patients with cardiac amyloidosis were enrolled in this study after Institutional Review Board approval and obtaining formal written consent. All subjects were imaged head-first in the supine position in a 1.5T closed-bore MR imager. 3D MRE was performed using 5 mm isotropic resolution oblique short-axis slices and a vibration frequency of 140 Hz to obtain global quantitative in vivo left ventricular stiffness measurements. The median stiffness was compared between the two cohorts. An octahedral shear strain signal-to-noise ratio (OSS-SNR) threshold of 1.17 was used to exclude exams with insufficient motion amplitude. Results Five volunteers and six patients had to be excluded from the study because they fell below the 1.17 OSS-SNR threshold. The myocardial stiffness of cardiac amyloid patients (median: 11.4 kPa, min: 9.2, max: 15.7) was significantly higher (P = 0.0008) than normal controls (median: 8.2 kPa, min: 7.2, max: 11.8). Conclusion This study demonstrates the feasibility of 3D high-frequency cardiac MRE as a contrast-agent-free diagnostic imaging technique for cardiac amyloidosis. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1361–1367.

Purpose The purpose of this work is to derive and demonstrate constrained-phase dual-echo Dixon imaging within a maximum likelihood framework solved with a regularized graph-cuts-guided optimization. Theory and Methods Dual-echo Dixon reconstruction is fundamentally underdetermined; however, adopting a constrained-phase signal model reduces the number of unknowns and the nonlinear problem can be solved under a maximum likelihood framework. Period shifts in the field map (manifesting as fat/water signal swaps) must also be corrected. Here, a regularized cost function promotes a smooth field map and is solved with a graph-cuts-guided greedy binary optimization. The reconstruction shown here is compared to two other prevalent Dixon reconstructions in experimental phantom and human studies. Results Reconstructed images of the water and fat signal are shown for a phantom study, and in vivo studies of foot/ankle, pelvis, and CE-MRA of the thighs. The method shown here compared favorably with the other two methods. Large field inhomogeneities on the order of 20 ppm were resolved, thereby avoiding the fat and water signal swaps present in images reconstructed with the other methods. Conclusion Constrained-phase dual-echo Dixon imaging solved with a regularized graph-cuts-guided optimization has been derived and demonstrated to successfully separate water and fat images in the presence of large magnetic field inhomogeneities. Magn Reson Med 78:2203–2215, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Due to engineering limitations, the spatial encoding gradient fields in conventional magnetic resonance imaging cannot be perfectly linear and always contain higher-order, nonlinear components. If ignored during image reconstruction, gradient nonlinearity (GNL) manifests as image geometric distortion. Given an estimate of the GNL field, this distortion can be corrected to a degree proportional to the accuracy of the field estimate. The GNL of a gradient system is typically characterized using a spherical harmonic polynomial model with model coefficients obtained from electromagnetic simulation. Conventional whole-body gradient systems are symmetric in design; typically, only odd-order terms up to the 5th-order are required for GNL modeling. Recently, a high-performance, asymmetric gradient system was developed, which exhibits more complex GNL that requires higher-order terms including both odd- and even-orders for accurate modeling. This work characterizes the GNL of this system using an iterative calibration method and a fiducial phantom used in ADNI (Alzheimer’s Disease Neuroimaging Initiative). The phantom was scanned at different locations inside the 26-cm diameter-spherical-volume of this gradient, and the positions of fiducials in the phantom were estimated. An iterative calibration procedure was utilized to identify the model coefficients that minimize the mean-squared-error between the true fiducial positions and the positions estimated from images corrected using these coefficients. To examine the effect of higher-order and even-order terms, this calibration was performed using spherical harmonic polynomial of different orders up to the 10th-order including even- and odd-order terms, or odd-order only. The results showed that the model coefficients of this gradient can be successfully estimated. The residual root-mean-squared-error after correction using up to the 10th-order coefficients was reduced to 0.36 mm, yielding spatial accuracy comparable to conventional whole-body gradients. The even-order terms were necessary for accurate GNL modeling. In addition, the calibrated coefficients improved image geometric accuracy compared with the simulation-based coefficients.

Non-Cartesian MRI acquisition has demonstrated various advantages in many clinical applications. The shells trajectory is a 3D non-Cartesian MRI acquisition technique that samples the k-space using a series of concentric shells to achieve efficient 3D isotropic acquisition. Partial Fourier acquisition is an acceleration technique that is widely used in Cartesian MRI. It exploits the conjugate symmetry of k-space measurement to reduce the number of k-space samples compared to full-k-space acquisition, without loss of spatial resolution. For a Cartesian MRI acquisition, the direction of partial Fourier acceleration is aligned either with the phase encoded or frequency encoded direction. In those cases, the underlying image matrix can be reconstructed from the undersampled k-space data using a non-iterative, homodyne reconstruction framework. However, designing a non-Cartesian acquisition trajectory that is compatible with non-iterative homodyne reconstruction is not nearly as straightforward as in the Cartesian case. One reason is the non-iterative homodyne reconstruction requires (slightly over) half of the k-space to be fully sampled. Since the direction of partial Fourier acceleration varies throughout the acquisition in the non-Cartesian trajectory, directly applying the same partial Fourier acquisition pattern (as in Cartesian acquisitions) to a non-Cartesian trajectory does not necessarily yield a continuous, physically-achievable trajectory. In this work, we develop an asymmetric shells trajectory with fully-automated trajectory and gradient waveform design to achieve partial Fourier acquisition for the shells trajectory. We then demonstrate a non-iterative image reconstruction framework for the proposed trajectory. Phantom and in vivo brain scans based on spoiled gradient echo (SPGR) shells and magnetization-prepared shells (MP-shells) were performed to test the proposed trajectory design and reconstruction method. Our phantom and in vivo results demonstrate that the proposed partial Fourier shells trajectory maintains the desirable image contrast and high sampling efficiency from the fully sampled shells, while further reducing data acquisition time.

Purpose To develop a gradient pre-emphasis scheme that prospectively counteracts the effects of the first-order concomitant fields for any arbitrary gradient waveform played on asymmetric gradient systems, and to demonstrate the effectiveness of this approach using a real-time implementation on a compact gradient system. Methods After reviewing the first-order concomitant fields that are present on asymmetric gradients, we developed a generalized gradient pre-emphasis model assuming arbitrary gradient waveforms to counteract their effects. A numerically straightforward, easily implemented approximate solution to this pre-emphasis problem was derived that was compatible with the current hardware infrastructure of conventional MRI scanners for eddy current compensation. The proposed method was implemented on the gradient driver subsystem, and its real-time use was tested using a series of phantom and in vivo data acquired from two-dimensional Cartesian phase-difference, echo-planar imaging, and spiral acquisitions. Results The phantom and in vivo results demonstrated that unless accounted for, first-order concomitant fields introduce considerable phase estimation error into the measured data and result in images with spatially dependent blurring/distortion. The resulting artifacts were effectively prevented using the proposed gradient pre-emphasis. Conclusion We have developed an efficient and effective gradient pre-emphasis framework to counteract the effects of first-order concomitant fields of asymmetric gradient systems. Magn Reson Med 77:2250–2262, 2017. © 2016 International Society for Magnetic Resonance in Medicine

Magnetic resonance elastography (MRE) is a rapidly growing noninvasive imaging technique for measuring tissue mechanical properties in vivo. Previous studies have compared two-dimensional MRE measurements with material properties from dynamic mechanical analysis (DMA) devices that were limited in frequency range. Advanced DMA technology now allows broad frequency range testing, and three-dimensional (3D) MRE is increasingly common. The purpose of this study was to compare 3D MRE stiffness measurements with those of DMA over a wide range of frequencies and shear stiffnesses.3D MRE and DMA were performed on eight different polyvinyl chloride samples over 20-205 Hz with stiffness between 3 and 23 kPa. Driving frequencies were chosen to create 1.1, 2.2, 3.3, 4.4, 5.5, and 6.6 effective wavelengths across the diameter of the cylindrical phantoms. Wave images were analyzed using direct inversion and local frequency estimation algorithm with the curl operator and compared with DMA measurements at each corresponding frequency. Samples with sufficient spatial resolution and with an octahedral shear strain signal-to-noise ratio > 3 were compared.Consistency between the two techniques was measured with the intraclass correlation coefficient (ICC) and was excellent with an overall ICC of 0.99.3D MRE and DMA showed excellent consistency over a wide range of frequencies and stiffnesses. Magn Reson Med 77:1184-1192, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Purpose To test the hypothesis that removing the assumption of material homogeneity will improve the spatial accuracy of stiffness estimates made by Magnetic Resonance Elastography (MRE). Methods An artificial neural network was trained using synthetic wave data computed using a coupled harmonic oscillator model. Material properties were allowed to vary in a piecewise smooth pattern. This neural network inversion (Inhomogeneous Learned Inversion (ILI)) was compared against a previous homogeneous neural network inversion (Homogeneous Learned Inversion (HLI)) and conventional direct inversion (DI) in simulation, phantom, and in-vivo experiments. Results In simulation experiments, ILI was more accurate than HLI and DI in predicting the stiffness of an inclusion in noise-free, low-noise, and high-noise data. In the phantom experiment, ILI delineated inclusions ≤ 2.25 cm in diameter more clearly than HLI and DI, and provided a higher contrast-to-noise ratio for all inclusions. In a series of stiff brain tumors, ILI shows sharper stiffness transitions at the edges of tumors than the other inversions evaluated. Conclusion ILI is an artificial neural network based framework for MRE inversion that does not assume homogeneity in material stiffness. Preliminary results suggest that it provides more accurate stiffness estimates and better contrast in small inclusions and at large stiffness gradients than existing algorithms that assume local homogeneity. These results support the need for continued exploration of learning-based approaches to MRE inversion, particularly for applications where high resolution is required.

Purpose To describe an efficient numerical optimization technique using non-linear least squares to estimate perfusion parameters for the Tofts and extended Tofts models from dynamic contrast enhanced (DCE) MRI data and apply the technique to prostate cancer. Methods Parameters were estimated by fitting the two Tofts-based perfusion models to the acquired data via non-linear least squares. We apply Variable Projection (VP) to convert the fitting problem from a multi-dimensional to a one-dimensional line search to improve computational efficiency and robustness. Using simulation and DCE-MRI studies in twenty patients with suspected prostate cancer, the VP-based solver was compared against the traditional Levenberg-Marquardt (LM) strategy for accuracy, noise amplification, robustness to converge, and computation time. Results The simulation demonstrated that VP and LM were both accurate in that the medians closely matched assumed values across typical signal to noise ratio (SNR) levels for both Tofts models. VP and LM showed similar noise sensitivity. Studies using the patient data showed that the VP method reliably converged and matched results from LM with approximate 3 × and 2 × reductions in computation time for the standard (two-parameter) and extended (three-parameter) Tofts models. While LM failed to converge in 14% of the patient data, VP converged in the ideal 100%. Conclusion The VP-based method for non-linear least squares estimation of perfusion parameters for prostate MRI is equivalent in accuracy and robustness to noise, while being more reliably (100%) convergent and computationally about 3 × (TM) and 2 × (ETM) faster than the LM-based method.

Purpose To describe how integrated gradient nonlinearity (GNL) correction can be used within noniterative partial Fourier (homodyne) and parallel (SENSE and GRAPPA) MR image reconstruction strategies, and demonstrate that performing GNL correction during, rather than after, these routines mitigates the image blurring and resolution loss caused by postreconstruction image domain based GNL correction. Methods Starting from partial Fourier and parallel magnetic resonance imaging signal models that explicitly account for GNL, noniterative image reconstruction strategies for each accelerated acquisition technique are derived under the same core mathematical assumptions as their standard counterparts. A series of phantom and in vivo experiments on retrospectively undersampled data were performed to investigate the spatial resolution benefit of integrated GNL correction over conventional postreconstruction correction. Results Phantom and in vivo results demonstrate that the integrated GNL correction reduces the image blurring introduced by the conventional GNL correction, while still correcting GNL-induced coarse-scale geometrical distortion. Images generated from undersampled data using the proposed integrated GNL strategies offer superior depiction of fine image detail, for example, phantom resolution inserts and anatomical tissue boundaries. Conclusion Noniterative partial Fourier and parallel imaging reconstruction methods with integrated GNL correction reduce the resolution loss that occurs during conventional postreconstruction GNL correction while preserving the computational efficiency of standard reconstruction techniques. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.

PURPOSE To develop a fully automated trajectory and gradient waveform design for the non-Cartesian shells acquisition, and to develop a magnetization-prepared (MP) shells acquisition to achieve an efficient three-dimensional acquisition with improved gray-to-white brain matter contrast. METHODS After reviewing the shells k-space trajectory, a novel, fully automated trajectory design is developed that allows for gradient waveforms to be automatically generated for specified acquisition parameters. Designs for two types of shells are introduced, including fully sampled and undersampled/accelerated shells. Using those designs, an MP-Shells acquisition is developed by adjusting the acquisition order of shells interleaves to synchronize the center of k-space sampling with the peak of desired gray-to-white matter contrast. The feasibility of the proposed design and MP-Shells is demonstrated using simulation, phantom, and volunteer subject experiments, and the performance of MP-Shells is compared with a clinical Cartesian magnetization-prepared rapid gradient echo acquisition. RESULTS Initial experiments show that MP-Shells produces excellent image quality with higher data acquisition efficiency and improved gray-to-white matter contrast-to-noise ratio (by 36%) compared with the conventional Cartesian magnetization-prepared rapid gradient echo acquisition. CONCLUSION We demonstrated the feasibility of a three-dimensional MP-Shells acquisition and an automated trajectory design to achieve an efficient acquisition with improved gray-to-white matter contrast. Magn Reson Med 79:2024-2035, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Purpose To describe a model-based reconstruction strategy for routine magnetic resonance imaging that accounts for gradient nonlinearity (GNL) during rather than after transformation to the image domain, and demonstrate that this approach reduces the spatial resolution loss that occurs during strictly image-domain GNL-correction. Methods After reviewing conventional GNL-correction methods, we propose a generic signal model for GNL-affected magnetic resonance imaging acquisitions, discuss how it incorporates into contemporary image reconstruction platforms, and describe efficient nonuniform fast Fourier transform-based computational routines for these. The impact of GNL-correction on spatial resolution by the conventional and proposed approaches is investigated on phantom data acquired at varying offsets from gradient isocenter, as well as on fully sampled and (retrospectively) undersampled in vivo acquisitions. Results Phantom results demonstrate that resolution loss that occurs during GNL-correction is significantly less for the proposed strategy than for the standard approach at distances >10 cm from isocenter with a 35 cm field-of-view gradient coil. The in vivo results suggest that the proposed strategy better preserves fine anatomical detail than retrospective GNL-correction while offering comparable geometric correction. Conclusion Accounting for GNL during image reconstruction allows geometric distortion to be corrected with less spatial resolution loss than is typically observed with the conventional image domain correction strategy. Magn Reson Med 74:1019–1031, 2015. © 2014 Wiley Periodicals, Inc.

Purpose The purpose of this work is to compare the behavior of the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in contrast-enhanced MR angiography with background suppression performed by either a Dixon-type or subtraction-type method. Theory and Methods Theoretical expressions for the SNR and CNR for both background suppression techniques were derived. The theoretical Dixon:subtraction SNR and CNR ratios were compared to empirical ratios measured from phantom and in vivo studies for Dixon techniques utilizing one, two, and three echoes. Specifically, the SNR and CNR ratios were compared as the concentration of contrast material in the blood changed. Results Empirical measurements of the SNR and CNR ratios compared favorably with the ratios predicted by theory. As the contrast concentration was reduced, the SNR advantage of the Dixon techniques increased asymptotically. In the ideal case, the SNR improvement over subtraction contrast-enhanced MR angiography was at least twofold for one- and two-echo Dixon techniques and at least a factor of for the three-echo Dixon technique. Conclusion Expressions showing a contrast concentration-dependent SNR and CNR improvement of at least a factor of two when Dixon-type contrast-enhanced MR angiography is used in place of subtraction-type contrast-enhanced MR angiography were derived and validated with phantom and in vivo experiments. Magn Reson Med 74:81–92, 2015. © 2014 Wiley Periodicals, Inc.

Purpose Spatial position accuracy in magnetic resonance imaging (MRI) is an important concern for a variety of applications, including radiation therapy planning, surgical planning, and longitudinal studies of morphologic changes to study neurodegenerative diseases. Spatial accuracy is strongly influenced by gradient linearity. This work presents a method for characterizing the gradient non-linearity fields on a per-system basis, and using this information to provide improved and higher-order (9th vs. 5th) spherical harmonic coefficients for better spatial accuracy in MRI. Methods A large fiducial phantom containing 5229 water-filled spheres in a grid pattern is scanned with the MR system, and the positions all the fiducials are measured and compared to the corresponding ground truth fiducial positions as reported from a computed tomography (CT) scan of the object. Systematic errors from off-resonance (i.e., B0) effects are minimized with the use of increased receiver bandwidth (± 125 kHz) and two acquisitions with reversed readout gradient polarity. The spherical harmonic coefficients are estimated using an iterative process, and can be subsequently used to correct for gradient non-linearity. Test-retest stability was assessed with five repeated measurements on a single scanner, and cross-scanner variation on four different, identically-configured 3 T wide-bore systems. Results A decrease in the root-mean-square error (RMSE) over a 50 cm diameter spherical volume from 1.80 mm to 0.77 mm is reported here in the case of replacing the vendor's standard 5th order spherical harmonic coefficients with custom fitted 9th order coefficients, and from 1.5 mm to 1 mm by extending custom fitted 5th order correction to the 9th order. Minimum RMSE varied between scanners, but was stable with repeated measurements in the same scanner. Conclusions The results suggest that the proposed methods may be used on a per-system basis to more accurately calibrate MR gradient non-linearity coefficients when compared to vendor standard corrections.

Purpose To describe and evaluate the method we refer to as “vascular masking” for improving signal-to-noise ratio (SNR) retention in sensitivity encoding (SENSE)-accelerated contrast-enhanced magnetic resonance angiography (CE-MRA). Materials and Methods Vascular masking is a technique that restricts the SENSE unfolding of an accelerated subtraction angiogram to the voxels within the field of view known to have enhancing signal. This is a more restricted voxel set than that identified with conventional masking, which excludes only voxels in the air around the object. Thus, improved retention of SNR is expected. Evaluation was done in phantom and in vivo studies by comparing SNR and the g-factor in results reconstructed using vascular versus conventional masking. A radiological evaluation was also performed comparing conventional and vascular masking in R = 8 accelerated CE-MRA studies of the thighs (n = 21) and calves (n = 13). Results Images reconstructed with vascular masking showed a significant reduction in g-factor and improved retention of SNR versus those reconstructed with conventional masking. In the radiological evaluation, vascular masking consistently provided reduced background noise, improved luminal signal smoothness, and better small vessel conspicuity. Conclusion Vascular masking provides improved SNR retention and improved depiction of the vasculature in accelerated, subtraction 3D CE-MRA of the thighs and calves. J. Magn. Reson. Imaging 2014;39:1161–1170. © 2013 Wiley Periodicals, Inc.

Quantitative estimation of T1 is a challenging but important task inherent to many clinical applications. The most commonly used paradigm for estimating T1 in vivo involves performing a sequence of spoiled gradient-recalled echo acquisitions at different flip angles, followed by fitting of an exponential model to the data. Although there has been substantial work comparing different fitting methods, there has been little discussion on how these methods should be applied for data acquired using multichannel receivers. In this note, we demonstrate that the manner in which multichannel data is handled can have a substantial impact on T1 estimation performance and should be considered equally as important as choice of flip angles or fitting strategy.

CAPR is a SENSE-type parallel 3DFT acquisition paradigm for 4D contrast-enhanced magnetic resonance angiography (CE-MRA) that has been demonstrated capable of providing high spatial and temporal resolution, diagnostic-quality images at very high acceleration rates. However, CAPR images are typically reconstructed online using Tikhonov regularization and partial Fourier methods, which are prone to exhibit noise amplification and undersampling artifacts when operating at very high acceleration rates. In this work, a sparsity-driven offline reconstruction framework for CAPR is developed and demonstrated to consistently provide improvements over the currently-employed reconstruction strategy against these ill-effects. Moreover, the proposed reconstruction strategy requires no changes to the existing CAPR acquisition protocol, and an efficient numerical optimization and hardware system are described that allow for a 256×160×80 volume CE-MRA volume to be reconstructed from an 8-channel data set in less than two minutes.

Magnetic resonance elastography (MRE) is increasingly being applied to thin or small structures in which wave propagation is dominated by waveguide effects, which can substantially bias stiffness results with common processing approaches. The purpose of this work was to investigate the importance of such biases and artifacts on MRE inversion results in: (i) various idealized 2D and 3D geometries with one or more dimensions that are small relative to the shear wavelength; and (ii) a realistic cardiac geometry. Finite element models were created using simple 2D geometries as well as a simplified and a realistic 3D cardiac geometry, and simulated displacements acquired by MRE from harmonic excitations from 60 to 220 Hz across a range of frequencies. The displacement wave fields were inverted with direct inversion of the Helmholtz equation with and without the application of bandpass filtering and/ or the curl operator to the displacement field. In all geometries considered, and at all frequencies considered, strong biases and artifacts were present in inversion results when the curl operator was not applied. Bandpass filtering without the curl was not sufficient to yield accurate recovery. In the 3D geometries, strong biases and artifacts were present in 2D inversions even when the curl was applied, while only 3D inversions with application of the curl yielded accurate recovery of the complex shear modulus. These results establish that taking the curl of the wave field and performing a full 3D inversion are both necessary steps for accurate estimation of the shear modulus both in simple thin-walled or small structures and in a realistic cardiac geometry when using simple inversions that neglect the hydrostatic pressure term. In practice, sufficient wave amplitude, signal-to-noise ratio, and resolution will be required to achieve accurate results.

Purpose Noninvasive stiffness imaging techniques (elastography) can image myocardial tissue biomechanics in vivo. For cardiac MR elastography (MRE) techniques, the optimal vibration frequency for in vivo experiments is unknown. Furthermore, the accuracy of cardiac MRE has never been evaluated in a geometrically accurate phantom. Therefore, the purpose of this study was to determine the necessary driving frequency to obtain accurate three-dimensional (3D) cardiac MRE stiffness estimates in a geometrically accurate diastolic cardiac phantom and to determine the optimal vibration frequency that can be introduced in healthy volunteers. Methods The 3D cardiac MRE was performed on eight healthy volunteers using 80 Hz, 100 Hz, 140 Hz, 180 Hz, and 220 Hz vibration frequencies. These frequencies were tested in a geometrically accurate diastolic heart phantom and compared with dynamic mechanical analysis (DMA). Results The 3D Cardiac MRE was shown to be feasible in volunteers at frequencies as high as 180 Hz. MRE and DMA agreed within 5% at frequencies greater than 180 Hz in the cardiac phantom. However, octahedral shear strain signal to noise ratios and myocardial coverage was shown to be highest at a frequency of 140 Hz across all subjects. Conclusion This study motivates future evaluation of high-frequency 3D MRE in patient populations. Magn Reson Med, 2016. © 2016 Wiley Periodicals, Inc.

The application of sparsity-driven reconstruction methods to MRI to date has largely focused on situations where high-contrast features (e.g., gadolinium-enhanced vessels) are of primary interest. In clinical practice, however, low contrast features such as subtle lesions are often of equal or greater interest. Using an American College of Radiology MR quality assurance phantom and test, we describe a novel framework for systematically and automatically evaluating the low-contrast object detectability performance of different undersampled image reconstruction methods. This platform is used to evaluate three such methods, two based on classic Tikhonov regularization and one sparsity-driven method based on l1-norm minimization (which is commonly used in compressive sensing, also known as compressed sensing, applications), across a wide range of sampling rates and parameterizations. Both the automated evaluation system and a manual evaluation of anatomical images with numerically-generated low contrast inserts demonstrate that sparse reconstructions exhibit superior low-contrast object detectability performance compared to both Tikhonov-regularized reconstructions. The implications of this result, and potential applications of both the described low-contrast object detectability platform and generalizations of it are then discussed. Magn Reson Med, 2011. © 2011 Wiley-Liss, Inc.

Compressive sensing (CS) describes how sparse signals can be accurately reconstructed from many fewer samples than required by the Nyquist criterion. Since MRI scan duration is proportional to the number of acquired samples, CS has been gaining significant attention in MRI. However, the computationally intensive nature of CS reconstructions has precluded their use in routine clinical practice. In this work, we investigate how different throughput-oriented architectures can benefit one CS algorithm and what levels of acceleration are feasible on different modern platforms. We demonstrate that a CUDA-based code running on an NVIDIA Tesla C2050 GPU can reconstruct a 256 × 160 × 80 volume from an 8-channel acquisition in 19 seconds, which is in itself a significant improvement over the state of the art. We then show that Intel's Knights Ferry can perform the same 3D MRI reconstruction in only 12 seconds, bringing CS methods even closer to clinical viability.