Model-based iterative reconstruction for direct imaging with point spread function encoded echo planar MRI.

BACKGROUND: Echo planar imaging (EPI) is a fast measurement technique commonly used in magnetic resonance imaging (MRI), but is highly sensitive to measurement non-idealities in reconstruction. Point spread function (PSF)-encoded EPI is a multi-shot strategy which alleviates distortion, but acquisition of encodings suitable for direct distortion-free imaging prolongs scan time. In this work, a model-based iterative reconstruction (MBIR) framework is introduced for direct imaging with PSF-EPI to improve image quality and acceleration potential. METHODS: An MBIR platform was developed for accelerated PSF-EPI. The reconstruction utilizes a subspace representation, is regularized to promote local low-rankedness (LLR), and uses variable splitting for efficient iteration. Comparisons were made against standard reconstructions from prospectively accelerated PSF-EPI data and with retrospective subsampling. Exploring aggressive partial Fourier acceleration of the PSF-encoding dimension, additional comparisons were made against an extension of Homodyne to direct PSF-EPI in numerical experiments. A neuroradiologists' assessment was completed comparing images reconstructed with MBIR from retrospectively truncated data directly against images obtained with standard reconstructions from non-truncated datasets. RESULTS: Image quality results were consistently superior for MBIR relative to standard and Homodyne reconstructions. As the MBIR signal model and reconstruction allow for arbitrary sampling of the PSF space, random sampling of the PSF-encoding dimension was also demonstrated, with quantitative assessments indicating best performance achieved through nonuniform PSF sampling combined with partial Fourier. With retrospective subsampling, MBIR reconstructs high-quality images from sub-minute scan datasets. MBIR was shown to be superior in a neuroradiologists' assessment with respect to three of five performance criteria, with equivalence for the remaining two. CONCLUSIONS: A novel image reconstruction framework is introduced for direct imaging with PSF-EPI, enabling arbitrary PSF space sampling and reconstruction of diagnostic-quality images from highly accelerated PSF-encoded EPI data.

Magnetic Resonance Imaging Artifact Associated With Transcutaneous Bone Conduction Implants: Cholesteatoma and Vestibular Schwannoma Surveillance.

OBJECTIVE: To evaluate the magnetic resonance (MR) image artifact and image distortion associated with the two transcutaneous bone conduction implants currently available in the United States. STUDY DESIGN: Cadaveric study. METHODS: Two cadaveric head specimens (1 male, 1 female) were unilaterally implanted according to manufacturer guidelines and underwent MR imaging (General Electric and Siemens 1.5 T scanners) under the following device conditions: (1) no device, (2) Cochlear Osia with magnet and headwrap, (3) Cochlear Osia without magnet, and (4) MED-EL Bonebridge with magnet. Maximum metal mitigation techniques were employed in all conditions, and identical sequences were obtained. Blinded image scoring (diagnostic vs nondiagnostic image) was performed by experienced neuroradiologists according to anatomical subsites. RESULTS: All device conditions produced artifact and image distortion. The Osia with magnet produced diagnostic T1- and T2-weighted images of the ipsilateral temporal bone, however, non-echo planar imaging diffusion-weighted imaging (DWI) was nondiagnostic. The Osia without magnet scanned on the Siemens MR imaging demonstrated the least amount of artifact and was the only condition that allowed for diagnostic imaging of the ipsilateral temporal bone on DWI. The Bonebridge produced a large area of artifact and distortion with the involvement of the ipsilateral and contralateral temporal bones. CONCLUSION: In summary, of the three device conditions (Osia with magnet, Osia without magnet, and Bonebridge), Osia without magnet offered the least amount of artifact and distortion and was the only condition in which diagnostic DWI was available for the middle ear and mastoid regions on the Siemens MR imaging scanner.

Locally Low-Rank Denoising of Multi-Echo Functional MRI Data With Application in Resting-State Analysis.

OBJECTIVES: Locally low-rank (LLR) denoising of functional magnetic resonance imaging (fMRI) time series image data is extended to multi-echo (ME) data. The proposed method extends the capabilities of non-physiologic noise suppression beyond single-echo applications with a dedicated ME algorithm. MATERIALS AND METHODS: Following an institutional review board (IRB) approved protocol, resting-state fMRI data were acquired in 7 healthy subjects. A compact 3T scanner enabled whole-brain acquisition of multiband ME fMRI data at high spatial resolution (1.4 × 1.4 × 2.8 mm 3 ) with a 1810 ms repetition time (TR). Image data were denoised with ME-LLR preceding functional processing. The results of connectivity maps generated from denoised data were compared with maps generated with equivalent processing of non-denoised images. To assess ME-LLR as a method to reduce scan time, comparisons were made between maps computed from image data with full and retrospectively truncated durations. Assessments were completed with seed-based connectivity analyses using echo-combined image data. In a feasibility assessment, nondenoised and denoised full-duration echo-combined data were equivalently processed with independent component analysis (ICA) and compared. RESULTS: ME-LLR denoising yielded strengthened resting-state network connectivity maps after nuisance regression and seed-based connectivity analysis. In assessing ME-LLR as a scan reduction mechanism, maps generated from denoised data at half scan time showed comparable quality with maps generated from full-duration, non-denoised data, at both single subject and group levels. ME-LLR substantially increased temporal signal-to-noise ratio (tSNR) for image data respective to each individual echo and for image data after nuisance regression. Among echo-specific image volumes, increases in tSNR yielded by ME-LLR were most pronounced for image data with the longest echo time and thereby lowest SNR. ICA showed resting-state networks consistently identified between non-denoised and denoised data, with clearer demarcation of networks for ME-LLR. CONCLUSIONS: ME-LLR is demonstrated to suppress non-physiologic noise, enhance functional connectivity map quality, and could potentially facilitate scan time reduction in ME-fMRI.

Evaluation of a compact 3 T MRI scanner for patients with implanted devices.

Access to high-quality MR exams is severely limited for patients with some implanted devices due to labeled MR safety conditions, but small-bore systems can overcome this limitation. For example, a compact 3 T MR scanner (C3T) with high-performance gradients can acquire exams of the head, extremities, and infants. Because of its reduced bore size and the patient being advanced only partially into the bore, the associated electromagnetic (EM) fields drop off rapidly caudal to the head, compared to whole-body systems. Therefore, some patients with MR conditional implanted devices can safely receive 3 T brain exams on the C3T using its strong gradients and a multiple-channel receive coil, while a corresponding exam on whole-body MR is precluded. The purpose of this study is to evaluate the performance of a small-bore scanner for subjects with MR conditional spinal or sacral nerve stimulators, or abandoned cardiac implantable electronic device (CIED) leads. The spatial dependence of specific absorption rate (SAR) on the C3T was compared to whole-body scanners. A device assessment tool was developed and applied to evaluate MR safety individually on the C3T for 12 subjects with implanted devices or abandoned CIED leads. Once MR safety was established, the subjects received a C3T brain exam along with their clinical, 1.5 T exam. The resulting images were graded by three board-certified neuroradiologists. The C3T exams were well-tolerated with no adverse events, and significantly outperformed the whole-body 1.5 T exams in terms of overall image quality.

Improved Resting-State Functional MRI Using Multi-Echo Echo-Planar Imaging on a Compact 3T MRI Scanner with High-Performance Gradients.

In blood-oxygen-level-dependent (BOLD)-based resting-state functional (RS-fMRI) studies, usage of multi-echo echo-planar-imaging (ME-EPI) is limited due to unacceptable late echo times when high spatial resolution is used. Equipped with high-performance gradients, the compact 3T MRI system (C3T) enables a three-echo whole-brain ME-EPI protocol with smaller than 2.5 mm isotropic voxel and shorter than 1 s repetition time, as required in landmark fMRI studies. The performance of the ME-EPI was comprehensively evaluated with signal variance reduction and region-of-interest-, seed- and independent-component-analysis-based functional connectivity analyses and compared with a counterpart of single-echo EPI with the shortest TR possible. Through the multi-echo combination, the thermal noise level is reduced. Functional connectivity, as well as signal intensity, are recovered in the medial orbital sulcus and anterior transverse collateral sulcus in ME-EPI. It is demonstrated that ME-EPI provides superior sensitivity and accuracy for detecting functional connectivity and/or brain networks in comparison with single-echo EPI. In conclusion, the high-performance gradient enabled high-spatial-temporal resolution ME-EPI would be the method of choice for RS-fMRI study on the C3T.

Technical note: Improved differentiation of calcification from hemosiderin using paramagnetic- and diamagnetic-specific magnetic resonance susceptibility weighted imaging (p-SWI, d-SWI).

INTRODUCTION: Differentiation of calcification and calcium-containing tissue from blood products remains challenging using magnetic resonance imaging (MRI). We developed a novel post-processing algorithm which creates both paramagnetic- and diamagnetic-specific SWI images generated from T2* weighted images using distinct "positive" and "negative" phase masks. METHODS: 10 patients who had undergone clinical MRI scanning of the brain with a rapid echo planar based T2*-weighted EPI-GRE pulse sequence with evidence for either hemosiderin and/or calcifications were retrospectively identified. Complex raw k-space data from individual imaging coils were then extracted, reconstructed, and appropriately combined to produce magnitude and phase images using a phase preserving method. The final reconstructed images included the T2* EPI-GRE magnitude images, p-SWI and d-SWI images. Filtered phase images were also available for review. Correlation with CT scans and MR imaging appearance over time corroborated the composition of the voxels. RESULTS: Differential "blooming" of diamagnetic and paramagnetic foci was readily identified on the corresponding p-SWI and d-SWI images and provided fast and reliable visual differentiation of diamagnetic from paramagnetic susceptibility effects by ascertaining which of the two images depicted the greatest "blooming" effect. Correlation with the available filtered phase maps was not necessary for differentiation of paramagnetic from diamagnetic image components. CONCLUSION: Clinical interpretation of SWI images can be further enhanced by creating specific p-SWI and d-SWI image pairs which contain greater visual information than the combination of standard p-SWI images and phase image.

Minimizing susceptibility-induced BOLD sensitivity loss in multi-band accelerated fMRI using point spread function mapping and gradient reversal.

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.

Enhanced clinical task-based fMRI metrics through locally low-rank denoising of complex-valued data.

OBJECTIVE: This 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. METHODS: Task-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. RESULTS: fMRI activation maps generated from LLR-denoised data predominantly exhibited statistically significant (p = 4.88×10-4 to 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. CONCLUSION: LLR 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.

Model-based image reconstruction with wavelet sparsity regularization for through-plane resolution restoration in T2 -weighted spin-echo prostate MRI.

PURPOSE: The purpose is to develop a model-based image-reconstruction method using wavelet sparsity regularization for maintaining restoration of through-plane resolution but with improved retention of SNR versus linear reconstruction using Tikhonov (TK) regularization in high through-plane resolution (1 mm) T2 -weighted spin-echo (T2SE) images of the prostate. METHODS: A wavelet sparsity (WS)-regularized image reconstruction was developed that takes as input a set of ≈80 overlapped 3-mm-thick slices acquired using a T2SE multislice scan and typically 30 coil elements. After testing in contrast and resolution phantoms and calibration in 6 subjects, the WS reconstruction was evaluated in 16 consecutive prostate T2SE MRI exams. Results reconstructed with nominal 1-mm thickness were compared with those from the TK reconstruction with the same raw data. Results were evaluated radiologically. The ratio of magnitude of prostate signal to periprostatic muscle signal was used to assess the presence of noise reduction. Technical performance was also compared with a commercial 3D-T2SE sequence. RESULTS: The new WS reconstruction was assessed as superior statistically to TK for overall SNR, contrast, and multiple evaluation criteria related to sharpness while retaining the high (1 mm) through-plane resolution. Wavelet sparsity tended to provide improved overall diagnostic quality versus TK, but not significantly so. In all 16 studies, the prostate-to-muscle signal ratio increased. CONCLUSIONS: Model-based WS-regularized reconstruction consistently provides improved SNR in high (1 mm) through-plane resolution images of prostate T2SE MRI versus linear reconstruction using TK regularization.

Impact of material homogeneity assumption on cortical stiffness estimates by MR elastography.

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.

Curvelet Transform-Based Sparsity Promoting Algorithm for Fast Ultrasound Localization Microscopy.

Ultrasound localization microscopy (ULM) based on microbubble (MB) localization was recently introduced to overcome the resolution limit of conventional ultrasound. However, ULM is currently challenged by the requirement for long data acquisition times to accumulate adequate MB events to fully reconstruct vasculature. In this study, we present a curvelet transform-based sparsity promoting (CTSP) algorithm that improves ULM imaging speed by recovering missing MB localization signal from data with very short acquisition times. CTSP was first validated in a simulated microvessel model, followed by the chicken embryo chorioallantoic membrane (CAM), and finally, in the mouse brain. In the simulated microvessel study, CTSP robustly recovered the vessel model to achieve an 86.94% vessel filling percentage from a corrupted image with only 4.78% of the true vessel pixels. In the chicken embryo CAM study, CTSP effectively recovered the missing MB signal within the vasculature, leading to marked improvement in ULM imaging quality with a very short data acquisition. Taking the optical image as reference, the vessel filling percentage increased from 2.7% to 42.2% using 50ms of data acquisition after applying CTSP. CTSP used 80% less time to achieve the same 90% maximum saturation level as compared with conventional MB localization. We also applied CTSP on the microvessel flow speed maps and found that CTSP was able to use only 1.6s of microbubble data to recover flow speed images that have similar qualities as those constructed using 33.6s of data. In the mouse brain study, CTSP was able to reconstruct the majority of the cerebral vasculature using 1-2s of data acquisition. Additionally, CTSP only needed 3.2s of microbubble data to generate flow velocity maps that are comparable to those using 129.6s of data. These results suggest that CTSP can facilitate fast and robust ULM imaging especially under the circumstances of inadequate microbubble localizations.

Reverberation clutter signal suppression in ultrasound attenuation estimation using wavelet-based robust principal component analysis.

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 andin vivostudies.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.

Left-Right Intensity Asymmetries Vary Depending on Scanner Model for FLAIR and T1 Weighted MRI Images.

BACKGROUND: Localized regions of left-right image intensity asymmetry (LRIA) were incidentally observed on T2 -weighted (T2 -w) and T1 -weighted (T1 -w) diagnostic magnetic resonance imaging (MRI) images. Suspicion of herpes encephalitis resulted in unnecessary follow-up imaging. A nonbiological imaging artifact that can lead to diagnostic uncertainty was identified. PURPOSE: To investigate whether systematic LRIA exist for a range of scanner models and to determine if LRIA can introduce diagnostic uncertainty. STUDY TYPE: A retrospective study using the Alzheimer's Disease Neuroimaging Initiative (ADNI) data base. SUBJECTS: One thousand seven hundred fifty-three (median age: 72, males/females: 878/875) unique participants with longitudinal data were included. FIELD STRENGTH: 3T. SEQUENCES: T1 -w three-dimensional inversion-recovery spoiled gradient-echo (IR-SPGR) or magnetization-prepared rapid gradient-echo (MP-RAGE) and T2 -w fluid-attenuated inversion recovery (FLAIR) long tau fast spin echo inversion recovery (LT-FSE-IR). Only General Electric, Philips, and Siemens' product sequences were used. ASSESSMENT: LRIA was calculated as the left-right percent difference with respect to the mean intensity from automated anatomical atlas segmented regions. Three neuroradiologists with 37 (**), 32 (**), and 3 (**) years of experience rated the clinical impact of 30 T2 -w three-dimensional FLAIR exams with LRIA to determine the diagnostic uncertainty. Statistical comparisons between retrospective intensity normalized T1 m and original T1 -w images were made. STATISTICAL TESTS: For each image type, a linear mixed effects model was fit using LRIA scores from all scanners, regions, and participants as the outcome and age and sex as predictors. Statistical significance was defined as having a P-value <0.05. RESULTS: LRIA scores were significantly different from zero on most scanners. All clinicians were uncertain or recommended definite diagnostic follow-up in 62.5% of cases with LRIA >10%. Individuals with acute brain pathology or focal neurologic deficits are not enrolled in ADNI; therefore, focal signal abnormalities were considered false positives. DATA CONCLUSION: LRIA is system specific, systematic, creates diagnostic uncertainty, and impacts IR-SPGR, MP-RAGE, and LT-FSE-IR product sequences. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 3.

Improved Brain MR Imaging from a Compact, Lightweight 3T Scanner with High-Performance Gradients.

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 <0.05 was considered statistically significant. RESULTS: The 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 CONCLUSION: The 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 EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 1.

Three-Dimensional Ultrasound Localization Microscopy with Bipartite Graph-Based Microbubble Pairing and Kalman-Filtering-Based Tracking on a 256-Channel Verasonics Ultrasound System with a 32 × 32 Matrix Array.

Three-dimensional (3D) ultrasound localization microscopy (ULM) using a 2-D matrix probe and microbubbles (MBs) has been recently proposed to visualize microvasculature beyond the ultrasound diffraction limit in three spatial dimensions. However, 3D ULM suffers from several limitations: (1) high system complexity due to numerous channel counts, (2) complex MB flow dynamics in 3D, and (3) extremely long acquisition time. To reduce the system complexity while maintaining high image quality, we used a sub-aperture process to reduce received channel counts. To address the second issue, a 3D bipartite graph-based method with Kalman filtering-based tracking was used in this study for MB tracking. An MB separation approach was incorporated to separate high concentration MB data into multiple, sparser MB datasets, allowing better MB localization and tracking for a limited acquisition time. The proposed method was first validated in a flow channel phantom, showing improved spatial resolutions compared with the contrasted enhanced power Doppler image. Then the proposed method was evaluated with an in vivo chicken embryo brain dataset. Results showed that the reconstructed 3D super-resolution image achieved a spatial resolution of around 52 µm (smaller than the wavelength of around 200 µm). Microvessels that cannot be resolved clearly using localization only, can be well identified with the tailored 3D pairing and tracking algorithms. To sum up, the feasibility of the 3D ULM is shown, indicating the great possibility in clinical applications.

Fast 3D MR elastography of the whole brain using spiral staircase: Data acquisition, image reconstruction, and joint deblurring.

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.

MRI quantitative susceptibility mapping of the substantia nigra as an early biomarker for Lewy body disease.

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.

Fast super-resolution ultrasound microvessel imaging using spatiotemporal data with deep fully convolutional neural network.

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 133µm to 35µm, which is smaller than the ultrasound wavelength (73µm). The proposed method was further tested in anin vivohuman liver data. Results showed the reconstructed super-resolved images could resolve a microvessel of nearly 170µm (FWHM). Adjacent microvessels with a distance of 670µm, 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.

Simultaneous Noise Suppression and Incoherent Artifact Reduction in Ultrafast Ultrasound Vascular Imaging.

Ultrasound vascular imaging based on ultrafast plane wave imaging and singular value decomposition (SVD) clutter filtering has demonstrated superior sensitivity in blood flow detection. However, ultrafast ultrasound vascular imaging is susceptible to electronic noise due to the weak penetration of unfocused waves, leading to a lower signal-to-noise ratio (SNR) at larger depths. In addition, incoherent clutter artifacts originating from strong and moving tissue scatterers that cannot be completely removed create a strong mask on top of the blood signal that obscures the vessels. Herein, a method that can simultaneously suppress the background noise and incoherent artifacts is proposed. The method divides the tilted plane or diverging waves into two subgroups. Coherent spatial compounding is performed within each subgroup, resulting in two compounded data sets. An SVD-based clutter filter is applied to each data set, followed by a correlation between the two data sets to produce a vascular image. Uncorrelated noise and incoherent artifacts can be effectively suppressed with the correlation process, while the coherent blood signal can be preserved. The method was evaluated in wire-target simulations and phantom, in which around 7-10-dB SNR improvement was shown. Consistent results were found in a flow channel phantom with improved SNR by the proposed method (39.9 ± 0.2 dB) against conventional power Doppler (29.1 ± 0.6 dB). Last, we demonstrated the effectiveness of the method combined with block-wise SVD clutter filtering in a human liver, breast tumor, and inflammatory bowel disease data sets. The improved blood flow visualization may facilitate more reliable small vessel imaging for a wide range of clinical applications, such as cancer and inflammatory diseases.

Improved Ultrasound Microvessel Imaging Using Deconvolution with Total Variation Regularization.

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.