Citations

BackgroundA 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.PurposeTo 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 TypeProspective.SubjectsThirty patients with a clinically indicated head MRI.Sequence 3T; T1 FLAIR, T1 MP‐RAGE, 3D T2 FLAIR, T2 FSE, and DWI.AssessmentAll 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 TestLeft‐sided, right‐sided, and two‐sided Wilcoxon signed rank test; Fisher's method. A P value <0.05 was considered statistically significant.ResultsThe C3T system performed better than the WB3T in virtually all comparisons, except for motion artifacts for the T1 FLAIR and T1 MP‐RAGE sequences, where the WB3T system was deemed better. When combining all sequences together, the C3T system outperformed the WB3T system in all image quality parameters evaluated, except for motion artifact (P = 0.13).Data ConclusionThe C3T scanner provided better overall image quality for all sequences, and performed better in all individual categories, except for motion artifact on the T1 FLAIR and T1 MP‐RAGE.Level of Evidence2Technical Efficacy Stage1

PurposeTo 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.MethodsWe 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.ResultsIn 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.ConclusionA 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.

ABSTRACT 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.

Abstract 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 μ m to 35 μ m, which is smaller than the ultrasound wavelength (73 μ m). 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 μ m (FWHM). Adjacent microvessels with a distance of 670 μ m, 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.

PurposeTo 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.MethodThe 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.ResultsThe 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.ConclusionWe 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.

ObjectivesThe 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 MethodsMagnetic 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.ResultsThe 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 correctedP< 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.ConclusionsThis 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.

PurposeTo demonstrate the feasibility of pseudo‐continuous arterial‐spin–labeled (pCASL) imaging with 3D fast‐spin‐echo stack‐of‐spirals on a compact 3T scanner (C3T), to perform trajectory correction for eddy‐current–induced deviations in the spiral readout of pCASL imaging, and to assess the correction effect on perfusion‐related images with high‐performance gradients (80 mT/m, 700T/m/s) of the C3T.MethodsTo track eddy‐current–induced artifacts with Archimedean spiral readout, the spiral readout in pCASL imaging was performed with 5 different peak gradient slew rate (Smax) values ranging from 70 to 500 T/m/s. The trajectory for each Smax was measured using a dynamic field camera and applied in a density‐compensated gridding image reconstruction in addition to the nominal trajectory. The effect of the trajectory correction was assessed with perfusion‐weighted (ΔM) images and proton‐density–weighted images as well as cerebral blood flow (CBF) maps, obtained from 10 healthy volunteers.ResultsBlurring artifact on ΔM images was mitigated by the trajectory correction. CBF values on the left and right calcarine cortices showed no significant difference after correction. Also, the signal‐to‐noise ratio of ΔM images improved, on average, by 7.6% after correction (P < .001). The greatest improvement of 12.1% on ΔM images was achieved with a spiral readout using Smax of 300~400 T/m/s.ConclusionEddy currents can cause spiral trajectory deviation, which leads to deformation of the CBF map even in cases of low value Smax. The trajectory correction for spiral‐readout–based pCASL produces more reliable results for perfusion imaging. These results suggest that pCASL is feasible on C3T with high‐performance gradients.

Abstract 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 &lt; 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 &lt; 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.