Comparison of reconstruction accuracy and efficiency among autocalibrating data-driven parallel imaging methods

Chest Magnetic Resonance Imaging: Advances and Clinical Care

Many promising study results as well as technical advances for chest magnetic resonance imaging (MRI) have demonstrated its academic and clinical potentials during the last few decades, although chest MRI has been used for relatively few clinical situations in routine clinical practice. However, the Fleischner Society as well as the Japanese Society of Magnetic Resonance in Medicine have published a few white papers to promote chest MRI in routine clinical practice. In this review, we present clinical evidence of the efficacy of chest MRI for 1) thoracic oncology and 2) pulmonary vascular diseases.

Dynamic Susceptibility Contrast Perfusion, Part 2: Deployment With and Without Contrast Leakage Present

A thorough description of perfusion analysis and basic DSC MR acquisition concepts has been described in the companion article to this article, which the interested reader may also find useful. DSC MR imaging requires an MR imaging pulse sequence that is sensitive to magnetic susceptibility changes to register the contrast concentration changes when GBCA passes through the capillary bed. Any pulse sequence that has T2∗-weighting can be used to pick up these changes, provided that the sequence is fast enough to acquire an image of that slice of tissue at least every 1 to 2 second.

Lung Magnetic Resonance Imaging: Technical Advancements and Clinical Applications

ABSTRACT

Since lung magnetic resonance imaging (MRI) became clinically available, limited clinical utility has been suggested for applying MRI to lung diseases. Moreover, clinical applications of MRI for patients with lung diseases or thoracic oncology may vary from country to country due to clinical indications, type of health insurance, or number of MR units available. Because of this situation, members of the Fleischner Society and of the Japanese Society for Magnetic Resonance in Medicine have published new reports to provide appropriate clinical indications for lung MRI. This review article presents a brief history of lung MRI in terms of its technical aspects and major clinical indications, such as (1) what is currently available, (2) what is promising but requires further validation or evaluation, and (3) which developments warrant research-based evaluations in preclinical or patient studies. We hope this article will provide Investigative Radiology readers with further knowledge of the current status of lung MRI and will assist them with the application of appropriate protocols in routine clinical practice.

Model-based Deep Learning Reconstruction Using a Folded Image Training Strategy for Abdominal 3D T1-weighted Imaging

PURPOSE

To evaluate the feasibility of folded image training strategy (FITS) and the quality of images reconstructed using the improved model-based deep learning (iMoDL) network trained with FITS (FITS-iMoDL) for abdominal MR imaging.

METHODS

This retrospective study included abdominal 3D T1-weighted images of 122 patients. In the experimental analyses, peak SNR (PSNR) and structure similarity index (SSIM) of images reconstructed with FITS-iMoDL were compared with those with the following reconstruction methods: conventional model-based deep learning (conv-MoDL), MoDL trained with FITS (FITS-MoDL), total variation regularized compressed sensing (CS), and parallel imaging (CG-SENSE). In the clinical analysis, SNR and image contrast were measured on the reference, FITS-iMoDL, and CS images. Three radiologists evaluated the image quality using a 5-point scale to determine the mean opinion score (MOS).

RESULTS

The PSNR of FITS-iMoDL was significantly higher than that of FITS-MoDL, conv-MoDL, CS, and CG-SENSE (P < 0.001). The SSIM of FITS-iMoDL was significantly higher than those of the others (P < 0.001), except for FITS-MoDL (P = 0.056). In the clinical analysis, the SNR of FITS-iMoDL was significantly higher than that of the reference and CS (P < 0.0001). Image contrast was equivalent within an equivalence margin of 10% among these three image sets (P < 0.0001). MOS was significantly improved in FITS-iMoDL (P < 0.001) compared with CS images in terms of liver edge and vessels conspicuity, lesion depiction, artifacts, blurring, and overall image quality.

CONCLUSION

The proposed method, FITS-iMoDL, allowed a deeper MoDL reconstruction network without increasing memory consumption and improved image quality on abdominal 3D T1-weighted imaging compared with CS images.

Deep-learning-reconstructed high-resolution 3D cervical spine MRI for foraminal stenosis evaluation

OBJECTIVE

To compare standard-of-care two-dimensional MRI acquisitions of the cervical spine with those from a single three-dimensional MRI acquisition, reconstructed using a deep-learning-based reconstruction algorithm. We hypothesized that the improved image quality provided by deep-learning-based reconstruction would result in improved inter-rater agreement for cervical spine foraminal stenosis compared to conventional two-dimensional acquisitions.

MATERIALS AND METHODS

Forty-one patients underwent routine cervical spine MRI with a conventional protocol comprising two-dimensional T2-weighted fast spin echo scans (2 axial planes, 1 sagittal plane), and an isotropic-resolution three-dimensional T2-weighted fast spin echo scan reconstructed over a 4-h time window with a deep-learning-based reconstruction algorithm. Three radiologists retrospectively assessed images for the degree to which motion artifact limited clinical assessment, and foraminal and central stenosis at each level. Inter-rater agreement was analyzed with weighted Fleiss's kappa (k) and comparisons between two-dimensional and three-dimensional sequences were performed with Wilcoxon signed-rank test.

RESULTS

Inter-rater agreement for foraminal stenosis was "substantial" for two-dimensional sequences (k = 0.76) and "excellent" for the three-dimensional sequence (k = 0.81). Agreement was "excellent" for both sequences (k = 0.85 and 0.83) for central stenosis. The three-dimensional sequence had less perceptible motion artifact (p ≤ 0.001-0.036). Mean total scan time was 10.8 min for the two-dimensional sequences, and 7.3 min for the three-dimensional sequence.

CONCLUSION

Three-dimensional MRI reconstructed with a deep-learning-based algorithm provided "excellent" inter-observer agreement for foraminal and central stenosis, which was at least equivalent to standard-of-care two-dimensional imaging. Three-dimensional MRI with deep-learning-based reconstruction was less prone to motion artifact, with overall scan time savings.

Compare image quality of T2-weighted imaging with different phase acceleration factors

Previous studies demonstrated that adjusting the phase acceleration (PA) factors could influence image quality. To improve image quality and decrease respiratory artifacts of lesions in the liver on T2-weighted image by adjusting PA factor and number of excitation (NEX). Sixty consecutive patients with hepatic lesions were enrolled in this prospective research between May 2020 and June 2020. All patients had 3.0T magnetic resonance imaging with 4 sequences (combining PA factors and NEXs, the former was 2 and 3, the latter were 1.5 and 2, respectively, with the same other scanning parameters). Two readers used 5-point quality scales to assess image quality. The signal intensity was measured by drawing regions of interest in the liver, spleen, and background on the T2-weighted imaging. Artifacts, overall image impression, and vascular conspicuity were better when the PA factor was 3 than 2. Artifacts and vascular conspicuity were better when NEX was 2 than 1.5. PA factor 3 and NEX 2 got a higher score in 5-point quality scales and less scan time than the other 3 sequences. Meanwhile, the signal-to-noise ratio of PA factor 3 and NEX 2 was best among these 4 sequences. PA factor and NEX could influence the imaging quality and lesion-to-hepatic contrast in detecting hepatic lesions on T2-weighted images. PA factor 3 and NEX 2 may have a positive effect in the clinic, especially for those with irregular respiration, as it decreased artifacts and reduced scan time.

GRASPNET: Fast spatiotemporal deep learning reconstruction of golden-angle radial data for free-breathing dynamic contrast-enhanced magnetic resonance imaging

The purpose of the current study was to develop a deep learning technique called Golden-angle RAdial Sparse Parallel Network (GRASPnet) for fast reconstruction of dynamic contrast-enhanced 4D MRI acquired with golden-angle radial k-space trajectories. GRASPnet operates in the image-time space and does not use explicit data consistency to minimize the reconstruction time. Three different network architectures were developed: (1) GRASPnet-2D: 2D convolutional kernels (x,y) and coil and contrast dimensions collapsed into a single combined dimension; (2) GRASPnet-3D: 3D kernels (x,y,t); and (3) GRASPnet-2D + time: two 3D kernels to first exploit spatial correlations (x,y,1) followed by temporal correlations (1,1,t). The networks were trained using iterative GRASP reconstruction as the reference. Free-breathing 3D abdominal imaging with contrast injection was performed on 33 patients with liver lesions using a T1-weighted golden-angle stack-of-stars pulse sequence. Ten datasets were used for testing. The three GRASPnet architectures were compared with iterative GRASP results using quantitative and qualitative analysis, including impressions from two body radiologists. The three GRASPnet techniques reduced the reconstruction time to about 13 s with similar results with respect to iterative GRASP. Among the GRASPnet techniques, GRASPnet-2D + time compared favorably in the quantitative analysis. Spatiotemporal deep learning enables reconstruction of dynamic 4D contrast-enhanced images in a few seconds, which would facilitate translation to clinical practice of compressed sensing methods that are currently limited by long reconstruction times.

K2S Challenge: From Undersampled K-Space to Automatic Segmentation

Magnetic Resonance Imaging (MRI) offers strong soft tissue contrast but suffers from long acquisition times and requires tedious annotation from radiologists. Traditionally, these challenges have been addressed separately with reconstruction and image analysis algorithms. To see if performance could be improved by treating both as end-to-end, we hosted the K2S challenge, in which challenge participants segmented knee bones and cartilage from 8× undersampled k-space. We curated the 300-patient K2S dataset of multicoil raw k-space and radiologist quality-checked segmentations. 87 teams registered for the challenge and there were 12 submissions, varying in methodologies from serial reconstruction and segmentation to end-to-end networks to another that eschewed a reconstruction algorithm altogether. Four teams produced strong submissions, with the winner having a weighted Dice Similarity Coefficient of 0.910 ± 0.021 across knee bones and cartilage. Interestingly, there was no correlation between reconstruction and segmentation metrics. Further analysis showed the top four submissions were suitable for downstream biomarker analysis, largely preserving cartilage thicknesses and key bone shape features with respect to ground truth. K2S thus showed the value in considering reconstruction and image analysis as end-to-end tasks, as this leaves room for optimization while more realistically reflecting the long-term use case of tools being developed by the MR community.

Automated MRI Field of View Prescription from Region of Interest Prediction by Intra-Stack Attention Neural Network

Manual prescription of the field of view (FOV) by MRI technologists is variable and prolongs the scanning process. Often, the FOV is too large or crops critical anatomy. We propose a deep learning framework, trained by radiologists' supervision, for automating FOV prescription. An intra-stack shared feature extraction network and an attention network are used to process a stack of 2D image inputs to generate scalars defining the location of a rectangular region of interest (ROI). The attention mechanism is used to make the model focus on a small number of informative slices in a stack. Then, the smallest FOV that makes the neural network predicted ROI free of aliasing is calculated by an algebraic operation derived from MR sampling theory. The framework's performance is examined quantitatively with intersection over union (IoU) and pixel error on position and qualitatively with a reader study. The proposed model achieves an average IoU of 0.867 and an average ROI position error of 9.06 out of 512 pixels on 80 test cases, significantly better than two baseline models and not significantly different from a radiologist. Finally, the FOV given by the proposed framework achieves an acceptance rate of 92% from an experienced radiologist.

Region of interest-specific loss functions improve T2 quantification with ultrafast T2 mapping MRI sequences in knee, hip and lumbar spine

MRI T2 mapping sequences quantitatively assess tissue health and depict early degenerative changes in musculoskeletal (MSK) tissues like cartilage and intervertebral discs (IVDs) but require long acquisition times. In MSK imaging, small features in cartilage and IVDs are crucial for diagnoses and must be preserved when reconstructing accelerated data. To these ends, we propose region of interest-specific postprocessing of accelerated acquisitions: a recurrent UNet deep learning architecture that provides T2 maps in knee cartilage, hip cartilage, and lumbar spine IVDs from accelerated T2-prepared snapshot gradient-echo acquisitions, optimizing for cartilage and IVD performance with a multi-component loss function that most heavily penalizes errors in those regions. Quantification errors in knee and hip cartilage were under 10% and 9% from acceleration factors R = 2 through 10, respectively, with bias for both under 3 ms for most of R = 2 through 12. In IVDs, mean quantification errors were under 12% from R = 2 through 6. A Gray Level Co-Occurrence Matrix-based scheme showed knee and hip pipelines outperformed state-of-the-art models, retaining smooth textures for most R and sharper ones through moderate R. Our methodology yields robust T2 maps while offering new approaches for optimizing and evaluating reconstruction algorithms to facilitate better preservation of small, clinically relevant features.

A 2D-GRAPPA Algorithm with a Boomerang Kernel for 3D MRI Data Accelerated along Two Phase-Encoding Directions

For the reconstruction of 3D MRI data that are accelerated along the two phase-encoding directions, the 2D-generalized autocalibrating partially parallel acquisitions (GRAPPA) algorithm can be used to estimate the missing data in the k-space. We propose a new boomerang-shaped kernel based on theoretic and systemic analyses of the shape and dimensions of the kernel. The reconstruction efficiency of the 2D-GRAPPA algorithm with the proposed boomerang-shaped kernel (i.e., boomerang kernel (BK)-2D-GRAPPA) was compared with other 2D-GRAPPA algorithms that utilize different types of kernels (i.e., EX-2D-GRAPPA and SK-2D-GRAPPA) based on computer simulation, phantom and in vivo experiments. The proposed method was validated for different sets of ACS lines with acceleration factors from four to eight and various sizes of the kernels. A quantitative analysis was also performed by comparing the normalized root mean squared error (nRMSE) in the images and the undersampled edges. Computer simulation, in vivo and phantom experiments, and the quantitative analysis, showed that the proposed method could reduce aliasing artifacts without reducing the SNRs of the reconstructed images.

Time resolved DCE-MRI of the kidneys: Evaluation of the renal vasculatures and tumors using F-DISCO with and without compressed sensing in normal and wide-bore 3T systems

Dynamic contrast-enhanced MR imaging (DCE-MRI) has been widely used for the evaluation of renal arteries. This method is also useful for tumor and renal parenchyma characterization. The very fast MRI may provide stable and precise information regarding vasculature and soft tissues. The purpose of this study was to evaluate the ability of DCE-MRI to assess renal vasculatures and tumor perfusions using Differential subsampling with Cartesian ordering with spectrally selected inversion recovery with adiabatic pulses (F-DISCO) with and without compressed sensing (CS) in normal and wide-bore 3T systems. Fifty-one patients who underwent DCE-MRI using F-DISCO with or without CS for evaluation of renal or adrenal regions were included. Image quality, artifacts, fat saturation, and selective visual recognition of renal vasculatures were assessed by using a 5-point scale. Tumor recognition was verified by using a 5-point scale of confidence level. Signal intensities of each structure were also measured. In all cases, the temporal resolution of each phase for DCE-MRI was 1.9 to 2.0 seconds. Image quality, artifacts, fat saturation, and selective visual recognition of vasculatures were all acceptable (mean score 4.2-4.9). The selective visualization of renal arteries and veins was successfully accomplished (mean score 4.0-4.9). Contrast media perfusion for renal vasculature, renal parenchyma, and tumors was also recognized. DCE-MRI for the evaluation of renal vasculatures and tumors using F-DISCO with or without CS can be performed with high temporal and spatial resolutions in normal and wide-bore 3T systems. This information can be obtained in a stable fashion throughout the dynamic contrast study. CS can additionally provide benefits that the total imaging time may be shorter than without CS.

GPU accelerated Cartesian GRAPPA reconstruction using CUDA

BACKGROUND AND OBJECTIVE

GRAPPA (Generalized Auto-calibrating Partially Parallel Acquisition) is an advanced parallel MRI reconstruction method (pMRI) that enables under-sampled data acquisition with multiple receiver coils to reduce the MRI scan time and reconstructs artifact free image from the acquired under-sampled data. However, the reduction in MRI scan time comes at the expense of long reconstruction time. It is because the GRAPPA reconstruction time shows exponential growth with increasing number of receiver coils. Consequently, the conventional CPU platforms may not adhere to the requirements of fast data processing for MR image reconstruction.

METHODS

Graphics Processing Units (GPUs) have recently emerged as a viable commodity hardware to reduce the reconstruction time of pMRI methods. This paper presents a novel GPU based implementation of GRAPPA using custom built CUDA kernels, to meet the rising demands of fast MRI processing. The proposed framework exploits intrinsic parallelism in the calibration and synthesis phases of GRAPPA reconstruction process, aiming to achieve high speed MR image reconstruction for various GRAPPA configuration settings using different number of receiver coils, auto-calibration signals (ACS), sizes of GRAPPA kernel and acceleration factors. In-vivo experiments (using 8, 12 and 30 receiver coils) are performed to compare the performance of the proposed GPU accelerated GRAPPA with the CPU based GRAPPA extensions and GPU counterpart.

RESULTS

The results indicate that the proposed method achieves up to ≈47.8× , ≈17× and ≈3.8× speed up gains over multicore CPU (single thread), multicore CPU (8 thread) and Gadgetron (GPU based GRAPPA) respectively, without compromising the reconstruction accuracy.

CONCLUSIONS

The proposed method reduces the GRAPPA reconstruction time by employing the calibration phase (GRAPPA weights estimation) and synthesis phase (interpolation) on GPU. Our study shows that the proposed GPU based parallel framework for GRAPPA reconstruction provides a solution for high-speed image reconstruction while maintaining the quality of the reconstructed images.

Addressing concomitant gradient phase errors in time-interleaved chemical shift-encoded MRI fat fraction and R2 * mapping with a pass-specific phase fitting method

PURPOSE

Concomitant gradients induce phase errors that increase quadratically with distance from isocenter. This work proposes a complex-based fitting method that addresses concomitant gradient phase errors in chemical shift encoded (CSE) MRI estimation of proton density fat fraction (PDFF) and R₂ ^* through joint estimation of pass-specific phase terms. This method is applicable to time-interleaved multi-echo gradient-echo acquisitions (i.e., multi-pass acquisitions) and does not require prior knowledge of gradient waveforms typically needed to address concomitant gradient phase errors.

THEORY AND METHODS

A CSE-MRI spoiled gradient echo signal model, with pass-specific phase terms, is introduced for non-linear least squares estimation of PDFF and R₂ ^* in the presence of concomitant gradient phase errors. Cramér-Rao lower bound analysis was used to determine noise performance tradeoffs of the proposed fitting method, which was then validated in both phantom and in vivo experiments.

RESULTS

The proposed fitting method removed PDFF and R₂ ^* estimation errors up to 12% and 10 s^-1 , respectively, at ±12 cm off isocenter (S/I) in a water phantom. In healthy volunteers, PDFF and R₂ ^* bias was reduced by ~10% (12 cm off-isocenter) and ~30 s^-1 (16 cm off-isocenter), respectively. An evaluation in 29 clinical liver datasets demonstrated reduced PDFF bias and variability (8.4% improvement in the coefficient of variation), even with the imaging volume centered at isocenter.

CONCLUSION

Concomitant gradient induced phase errors in multi-pass CSE-MRI acquisitions can result in PDFF and R₂ ^* estimation biases away from isocenter. The proposed fitting method enables accurate PDFF and R₂ ^* quantification in the presence of concomitant gradient phase errors without knowledge of imaging gradient waveforms.

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.

Intra-Left Ventricular Hemodynamics Assessed with 4D Flow Magnetic Resonance Imaging in Patients with Left Ventricular Thrombus

Left ventricular thrombus (LVT) has been identified to be crucial in patients with reduced ejection fraction (EF). Three-dimensional cine phase-contrast magnetic resonance imaging (4D flow MRI) can visualize the intra-LV vortex during diastole and quantify the maximum flow velocity (Vmax) at the apex. In this study, we investigated whether the change in the intra-LV vortex was associated with the presence of LVT in patients with cardiac disease.In total, 36 patients (63.5 ± 11.9 years, 28 men, 12/24 with/without LVT) with diffuse LV dysfunction underwent 4D flow MRI. The relative vortex area using streamline images and Vmax of blood flow toward the apex at the apical left ventricle were evaluated. The correlation between the relative vortex area and Vmax was assessed using Pearson's correlation coefficient. The ability to detect LVT was evaluated using the area under the curve (AUC) of the receiver operating characteristic.The relative vortex area was found to be smaller (27 ± 10% versus 45 ± 11%, P = 0.000026), whereas Vmax at the apical left ventricle was lower (19.1 ± 4.4 cm/second versus 27.4 ± 8.9 cm/second, P = 0.0006) in patients with LVT. Vmax at the apical left ventricle demonstrated significant correlations with the relative vortex area (r = 0.43, P = 0.01) and relative transverse length of the vortex (r = 0.45, P = 0.007). The AUC was 0.91 for the relative vortex area, whereas it was 0.80 for Vmax in the apical left ventricle.A smaller LV vortex and lower flow velocity at the LV apex were associated with LVT in patients with reduced EF.

Diffusion propagator metrics are biased when simultaneous multi-slice acceleration is used

Advanced diffusion MRI models are being explored to study the complex microstructure of the brain with higher accuracy. However, these techniques require long acquisition times. Simultaneous Multi-Slice (SMS) accelerates data acquisition by exciting multiple image slices simultaneously and separating the overlapping slices using a mathematical model, which makes use of the distinct information coming from an array of receive coils. However, SMS acceleration introduces increased noise in reconstructed images and crosstalk between simultaneously excited slices. These compounded effects from SMS acceleration could affect quantitative MRI techniques such as diffusion imaging. In this study, the effects of SMS acceleration on the accuracy of propagator metrics obtained from a model-free advanced diffusion technique called Mean Apparent Propagator MRI (MAP-MRI) was investigated. Ten healthy volunteers were scanned with SMS accelerated multi-shell diffusion MRI acquisitions. Group analyses were performed to study brain regions affected by SMS acceleration. In addition, diffusion metrics from atlas-based fiber tracts of interest were analyzed to investigate how propagator metrics in major fiber tracts were biased by 2- and 3-band SMS acceleration. Both zero-displacement metrics and non-Gaussianity metrics were significantly altered when SMS acceleration was used. MAP-MRI metrics calculated from SMS-3 showed significant differences with respect to SMS-2. Furthermore, with the shorter TR afforded by SMS acceleration, the characteristics of this bias have changed. This has implications for studies using diffusion MRI with SMS acceleration to investigate the effects of a disease or injury on the brain tissues.

Magnetization-prepared spoiled gradient-echo snapshot imaging for efficient measurement of R2 -R1ρ in knee cartilage

PURPOSE

To validate the potential of quantifying R₂ -R_1ρ using one pair of signals with T_1ρ preparation and T₂ preparation incorporated to magnetization-prepared angle-modulated partitioned k-space spoiled gradient-echo snapshots (MAPSS) acquisition and to find an optimal preparation time (T_prep ) for in vivo knee MRI.

METHODS

Bloch equation simulations were first performed to assess the accuracy of quantifying R₂ -R_1ρ using T_1ρ - and T₂ -prepared signals with an equivalent T_prep . For validation of this technique in comparison to the conventional approach that calculates R₂ -R_1ρ after estimating both T₂ and T_1ρ , phantom experiments and in vivo validation with five healthy subjects and five osteoarthritis patients were performed at a clinical 3T scanner.

RESULTS

Bloch equation simulations demonstrated that the accuracy of this efficient R₂ -R_1ρ quantification method and the optimal T_prep can be affected by image signal-to-noise ratio (SNR) and tissue relaxation times, but quantification can be closest to the reference with an around 25 ms T_prep for knee cartilage. Phantom experiments demonstrated that the proposed method can depict R₂ -R_1ρ changes with agarose gel concentration. With in vivo data, significant correlation was observed between cartilage R₂ -R_1ρ measured from the conventional and the proposed methods, and a T_prep of 25.6 ms provided the most agreement by Bland-Altman analysis. R₂ -R_1ρ was significantly lower in patients than in healthy subjects for most cartilage compartments.

CONCLUSION

As a potential biomarker to indicate cartilage degeneration, R₂ -R_1ρ can be efficiently measured using one pair of T_1ρ -prepared and T₂ -prepared signals with an optimal T_prep considering cartilage relaxation times and image SNR.

Transient Respiratory-motion Artifact and Scan Timing during the Arterial Phase of Gadoxetate Disodium-enhanced MR Imaging: The Benefit of Shortened Acquisition and Multiple Arterial Phase Acquisition

Purpose:

To investigate whether shortened acquisition or multiple arterial phase acquisition improves image quality of the arterial phase compared with conventional protocol.

Methods:

This retrospective study was approved by the relevant Institutional Review Board. A total of 615 consecutive patients who underwent gadoxetate disodium-enhanced MRI including one of the following three sequences in three different periods were included: (i) conventional liver acquisition with volume acceleration (LAVA) (between October 2014 and January 2015, n = 149), (ii) Turbo-LAVA (between March and August 2016, n = 216), and (iii) differential sub-sampling with Cartesian ordering (DISCO) (between January and September 2015, n = 250). We monitored the respiratory bellows waveform during breath holding for each patient and recorded breath-hold fidelity of the patients. Two radiologists independently evaluated the degree of respiratory artifact and scan timing on the arterial phase and compared them between the three protocols (i.e., conventional LAVA, Turbo-LAVA, and DISCO), with conventional LAVA as control.

Results:

The ratio of patients with breath-hold failure was not significantly different among the three protocols (P = 0.6340 and 0.1085). Respiratory artifact was significantly lower in DISCO than in conventional LAVA (P = 0.0424), while there was no significant difference between Turbo-LAVA and conventional LAVA (P = 0.2593). The ratio of adequate scan timing and diagnosable image defined as no or mild artifact and adequate scan timing were higher in DISCO than in conventional LAVA (P = 0.0025 and 0.0019), while there was no significant difference between Turbo-LAVA and conventional LAVA (P = 0.0780 and 0.0657).

Conclusion:

Compared with conventional protocol, multiple arterial phase acquisition (DISCO) obtained a higher number of diagnosable images by reducing respiratory motion artifact and optimizing the scan timing of arterial phase.

Reproducibility of liver R2* quantification for liver iron quantification from cardiac R2* acquisitions

OBJECTIVES

To evaluate the reproducibility of liver R2* measurements between a 2D cardiac ECG-gated and a 3D breath-hold liver CSE-MRI acquisition for liver iron quantification.

METHODS

A total of 54 1.5 T MRI exams from 51 subjects (18 women, 36 men, age 35.2 ± 21.8) were included. These included two sub-studies with 23 clinical MRI exams from 19 patients identified retrospectively, 24 participants with known or suspected iron overload, and 7 healthy volunteers acquired prospectively. The 2D cardiac and the 3D liver R2* maps were acquired in the same exam. Either acquisitions were reconstructed using a complex R2* algorithm that accounts for the presence of fat and residual phase errors due to eddy currents. Data were analyzed using colocalized ROIs in the liver.

RESULTS

Linear regression analysis demonstrated high Pearson's correlation and Lin's concordance coefficient for the overall study and both sub-studies. Bland-Altman analysis also showed good agreement, except for a slight increase of the mean R2* value above ~ 400 s^-1. The Kolmogorow-Smirnow test revealed a non-normal distribution for (R2* 3D-R2* 2D) values from 0 to 600 s^-1 in contrast to the 0-200 s^-1 and 0-400 s^-1 subpopulations. Linear regression analysis showed no relevant differences other than the intercept, likely due to only 7 measurements above 400 s^-1.

CONCLUSIONS

The results demonstrate that R2*-measurements in the liver are feasible using 2D cardiac R2* maps compared to 3D liver R2* maps as the reference. Liver R2* may be underestimated for R2* > 400 s^-1 using the 2D cardiac R2* mapping method.

Accelerated Isotropic Multiparametric Imaging by High Spatial Resolution 3D-QALAS With Compressed Sensing: A Phantom, Volunteer, and Patient Study

OBJECTIVES

The aims of this study were to develop an accelerated multiparametric magnetic resonance imaging method based on 3D-quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) combined with compressed sensing (CS) and to evaluate the effect of CS on the quantitative mapping, tissue segmentation, and quality of synthetic images.

MATERIALS AND METHODS

A magnetic resonance imaging system phantom, containing multiple compartments with standardized T1, T2, and proton density (PD) values; 10 healthy volunteers; and 12 patients with multiple sclerosis were scanned using the 3D-QALAS sequence with and without CS and conventional contrast-weighted imaging. The scan times of 3D-QALAS with and without CS were 5:56 and 11:11, respectively. For healthy volunteers, brain volumetry and myelin estimation were performed based on the measured T1, T2, and PD. For patients with multiple sclerosis, the mean T1, T2, PD, and the amount of myelin in plaques and contralateral normal-appearing white matter (NAWM) were measured. Simple linear regression analysis and Bland-Altman analysis were performed for each metric obtained from the datasets with and without CS. To compare overall image quality and structural delineations on synthetic and conventional contrast-weighted images, case-control randomized reading sessions were performed by 2 neuroradiologists in a blinded manner.

RESULTS

The linearity of both phantom and volunteer measurements in T1, T2, and PD values obtained with and without CS was very strong (R2 = 0.9901-1.000). The tissue segmentation obtained with and without CS also had high linearity (R2 = 0.987-0.999). The quantitative tissue values of the plaques and NAWM obtained with CS showed high linearity with those without CS (R2 = 0.967-1.000). There were no significant differences in overall image quality between synthetic contrast-weighted images obtained with and without CS (P = 0.17-0.99).

CONCLUSIONS

Multiparametric imaging of the whole brain based on 3D-QALAS can be accelerated using CS while preserving tissue quantitative values, tissue segmentation, and quality of synthetic images.

Simultaneous multi-slice spin- and gradient-echo dynamic susceptibility-contrast perfusion-weighted MRI of gliomas

Although combined spin- and gradient-echo (SAGE) dynamic susceptibility-contrast (DSC) MRI can provide perfusion quantification that is sensitive to both macrovessels and microvessels while correcting for T₁ -shortening effects, spatial coverage is often limited in order to maintain a high temporal resolution for DSC quantification. In this work, we combined a SAGE echo-planar imaging (EPI) sequence with simultaneous multi-slice (SMS) excitation and blipped controlled aliasing in parallel imaging (blipped CAIPI) at 3 T to achieve both high temporal resolution and whole brain coverage. Two protocols using this sequence with multi-band (MB) acceleration factors of 2 and 3 were evaluated in 20 patients with treated gliomas to determine the optimal scan parameters for clinical use. ΔR₂ *(t) and ΔR₂ (t) curves were derived to calculate dynamic signal-to-noise ratio (dSNR), ΔR₂ *- and ΔR₂ -based relative cerebral blood volume (rCBV), and mean vessel diameter (mVD) for each voxel. The resulting SAGE DSC images acquired using MB acceleration of 3 versus 2 appeared visually similar in terms of image distortion and contrast. The difference in the mean dSNR from normal-appearing white matter (NAWM) and that in the mean dSNR between NAWM and normal-appearing gray matter were not statistically significant between the two protocols. ΔR₂ *- and ΔR₂ -rCBV maps and mVD maps provided unique contrast and spatial heterogeneity within tumors.

Early changes of pulmonary arterial hemodynamics in patients with systemic sclerosis: flow pattern, WSS, and OSI analysis with 4D flow MRI

OBJECTIVES

To study the pulmonary artery (PA) hemodynamics in patients with systemic sclerosis (SSc) using 4D flow MRI (4D-flow).

METHODS

Twenty-three patients with SSc (M/F: 2/21, 57 ± 15 years, 3 manifest PA hypertension (PAH) by right heart catheterization) and 10 control subjects (M/F: 1/9, 55 ± 17 years) underwent 4D-flow for the in vivo measurement of 3D blood flow velocities in the PA. Data analysis included area-averaged flow quantification at the main PA, 3D wall shear stress (WSS), oscillatory shear index (OSI) calculation along the PA surface, and Reynolds number. The composite outcome of all-cause death and major adverse cardiac events was also investigated.

RESULTS

The maximum PA flow at the systole did not differ, but the minimum flow at the diastole was significantly greater in patients with SSc compared with that in control subjects (7.7 ± 16.0 ml/s vs. ‑ 13.0 ± 17.3 ml/s, p < 0.01). The maximum WSS at the peak systole was significantly lower and OSI was significantly greater in patients with SSc compared with those in control subjects (maximum WSS: 1.04 ± 0.20 Pa vs. 1.33 ± 0.34 Pa, p < 0.01, OSI: 0.139 ± 0.031 vs. 0.101 ± 0.037, p < 0.01). The cumulative event-free rate for the composite event was significantly lower in patients with minimum flow in main PA ≤ 9.22 ml/s (p = 0.012) and in patients with Reynolds number ≤ 2560 (p < 0.001).

CONCLUSIONS

4D-flow has the potential to detect changes of PA hemodynamics noninvasively and predict the outcome in patients with SSc at the stage before manifest PAH.

KEY POINTS

• The WSS at the peak systolic phase was significantly lower (p < 0.05), whereas OSI was greater (p < 0.01) in patients with SSc without manifest PAH than in controls. • The hemodynamic change detected by 4D-flow may help patient management even at the stage before manifest PAH in SSc. • The minimum PA flow and Reynolds number by 4D-flow will serve as a predictive marker for SSc.

Methodological Considerations for Neuroimaging in Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson's Disease Patients

Deep brain stimulation (DBS) of the subthalamic nucleus is a neurosurgical intervention for Parkinson's disease patients who no longer appropriately respond to drug treatments. A small fraction of patients will fail to respond to DBS, develop psychiatric and cognitive side-effects, or incur surgery-related complications such as infections and hemorrhagic events. In these cases, DBS may require recalibration, reimplantation, or removal. These negative responses to treatment can partly be attributed to suboptimal pre-operative planning procedures via direct targeting through low-field and low-resolution magnetic resonance imaging (MRI). One solution for increasing the success and efficacy of DBS is to optimize preoperative planning procedures via sophisticated neuroimaging techniques such as high-resolution MRI and higher field strengths to improve visualization of DBS targets and vasculature. We discuss targeting approaches, MRI acquisition, parameters, and post-acquisition analyses. Additionally, we highlight a number of approaches including the use of ultra-high field (UHF) MRI to overcome limitations of standard settings. There is a trade-off between spatial resolution, motion artifacts, and acquisition time, which could potentially be dissolved through the use of UHF-MRI. Image registration, correction, and post-processing techniques may require combined expertise of traditional radiologists, clinicians, and fundamental researchers. The optimization of pre-operative planning with MRI can therefore be best achieved through direct collaboration between researchers and clinicians.

Expanding Applications of Pulmonary MRI in the Clinical Evaluation of Lung Disorders: Fleischner Society Position Paper

Pulmonary MRI provides structural and quantitative functional images of the lungs without ionizing radiation, but it has had limited clinical use due to low signal intensity from the lung parenchyma. The lack of radiation makes pulmonary MRI an ideal modality for pediatric examinations, pregnant women, and patients requiring serial and longitudinal follow-up. Fortunately, recent MRI techniques, including ultrashort echo time and zero echo time, are expanding clinical opportunities for pulmonary MRI. With the use of multicoil parallel acquisitions and acceleration methods, these techniques make pulmonary MRI practical for evaluating lung parenchymal and pulmonary vascular diseases. The purpose of this Fleischner Society position paper is to familiarize radiologists and other interested clinicians with these advances in pulmonary MRI and to stratify the Society recommendations for the clinical use of pulmonary MRI into three categories: (a) suggested for current clinical use, (b) promising but requiring further validation or regulatory approval, and (c) appropriate for research investigations. This position paper also provides recommendations for vendors and infrastructure, identifies methods for hypothesis-driven research, and suggests opportunities for prospective, randomized multicenter trials to investigate and validate lung MRI methods.

Optimization of hyperparameters for SMS reconstruction

PURPOSE

Simultaneous multi-slice (SMS) imaging accelerates MRI data acquisition by exciting multiple image slices with a single radiofrequency pulse. Overlapping slices encoded in acquired signal are separated using a mathematical model, which requires estimation of image reconstruction kernels using calibration data. Several parameters used in SMS reconstruction impact the quality and fidelity of final images. Therefore, finding an optimal set of reconstruction parameters is critical to ensure that accelerated acquisition does not significantly degrade resulting image quality.

METHODS

Gradient-echo echo planar imaging data were acquired with a range of SMS acceleration factors from a cohort of five volunteers with no known neurological pathology. Images were collected using two available phased-array head coils (a 48-channel array and a reduced diameter 32-channel array) that support SMS. Data from these coils were identically reconstructed offline using a range of coil compression factors and reconstruction kernel parameters. A hybrid space (k-x), externally-calibrated coil-by-coil slice unaliasing approach was used for image reconstruction. The image quality of the resulting reconstructed SMS images was assessed by evaluating correlations with identical echo-planar reference data acquired without SMS. A finger tapping functional MRI (fMRI) experiment was also performed and group analysis results were compared between data sets reconstructed with different coil compression levels.

RESULTS

Between the two RF coils tested in this study, the 32-channel coil with smaller dimensions clearly outperformed the larger 48-channel coil in our experiments. Generally, a large calibration region (144-192 samples) and small kernel sizes (2-4 samples) in k_y direction improved image quality. Use of regularization in the kernel fitting procedure had a notable impact on the fidelity of reconstructed images and a regularization value 0.0001 provided good image quality. With optimal selection of other hyperparameters in the hybrid space SMS unaliasing algorithm, coil compression caused small reduction in correlation between single-band and SMS unaliased images. Similarly, group analysis of fMRI results did not show a significant influence of coil compression on resulting image quality.

CONCLUSIONS

This study demonstrated that the hyperparameters used in SMS reconstruction need to be fine-tuned once the experimental factors such as the RF receive coil and SMS factor have been determined. A cursory evaluation of SMS reconstruction hyperparameter values is therefore recommended before conducting a full-scale quantitative study using SMS technologies.

Diagnostic value of 3D-FLAIR magnetic resonance sequence in detection of white matter brain lesions in multiple sclerosis

Background

MS is common demyelinating disease in which standard T2 and 2D-FLAIR MRI sequences play important role in its diagnosis. Recently, 3D-FLAIR sequence is used and has a role that is evaluated compared to standard sequences.

Results

This study was performed on 20 selected MS patients. Brain MRI was performed using routinely used T2 and 2D FLAIR sequences, and 3D-FLAIR sequence was added. 3D-FLAIR images were reformatted, and all images were blindly analyzed. Lesions were counted in each sequence and classified according to their location into supratentorial lesions including periventricular, deep white matter, and juxta-cortical, and infratentorial lesions and relative comparison of lesion number on 3D-FLAIR versus 2D-FLAIR and T2 imaging, respectively, were expressed as percentage gain or a loss.

3D-FLAIR sequence showed significantly more lesions compared to 2D FLAIR and T2 sequences in all locations with relative ratio of 29% and 41%, respectively, in periventricular region; 22% and 30%, respectively, in deep WM; 180% and 147%, respectively, in juxta-cortical region; and 80% and 13%, respectively, in infratentorial region.

Conclusion

3D-FLAIR sequence is of greater sensitivity than standard 2D-FLAIR and T2 sequences in MS brain lesions depiction, and it is recommended to be included in MR protocol of MS.

Variable Refocusing Flip Angle Single-Shot Imaging for Sedation-Free Fast Brain MRI

BACKGROUND AND PURPOSE

Conventional single-shot FSE commonly used for fast MRI may be suboptimal for brain evaluation due to poor image contrast, SNR, or image blurring. We investigated the clinical performance of variable refocusing flip angle single-shot FSE, a variation of single-shot FSE with lower radiofrequency energy deposition and potentially faster acquisition time, as an alternative approach to fast brain MR imaging.

MATERIALS AND METHODS

We retrospectively compared half-Fourier single-shot FSE with half- and full-Fourier variable refocusing flip angle single-shot FSE in 30 children. Three readers reviewed images for motion artifacts, image sharpness at the brain-fluid interface, and image sharpness/tissue contrast at gray-white differentiation on a modified 5-point Likert scale. Two readers also evaluated full-Fourier variable refocusing flip angle single-shot FSE against T2-FSE for brain lesion detectability in 38 children.

RESULTS

Variable refocusing flip angle single-shot FSE sequences showed more motion artifacts (P < .001). Variable refocusing flip angle single-shot FSE sequences scored higher regarding image sharpness at brain-fluid interfaces (P < .001) and gray-white differentiation (P < .001). Acquisition times for half- and full-Fourier variable refocusing flip angle single-shot FSE were faster than for single-shot FSE (P < .001) with a 53% and 47% reduction, respectively. Intermodality agreement between full-Fourier variable refocusing flip angle single-shot FSE and T2-FSE findings was near-perfect (κ = 0.90, κ = 0.95), with an 8% discordance rate for ground truth lesion detection.

CONCLUSIONS

Variable refocusing flip angle single-shot FSE achieved 2× faster scan times than single-shot FSE with improved image sharpness at brain-fluid interfaces and gray-white differentiation. Such improvements are likely attributed to a combination of improved contrast, spatial resolution, SNR, and reduced T2-decay associated with blurring. While variable refocusing flip angle single-shot FSE may be a useful alternative to single-shot FSE and, potentially, T2-FSE when faster scan times are desired, motion artifacts were more common in variable refocusing flip angle single-shot FSE, and, thus, they remain an important consideration before clinical implementation.

Pulmonary Vascular Disease Evaluation with Magnetic Resonance Angiography

Pulmonary vascular assessment commonly relies on computed tomography angiography (CTA), but continued advances in magnetic resonance angiography have allowed pulmonary magnetic resonance angiography (pMRA) to become a reasonable alternative to CTA without exposing patients to ionizing radiation. pMRA allows the evaluation of pulmonary vascular anatomy, hemodynamic physiology, lung parenchymal perfusion, and (optionally) right and left ventricular function with a single examination. This article discusses pMRA techniques and artifacts; performance in commonly encountered pulmonary vascular diseases, specifically pulmonary embolism and pulmonary hypertension; and recent advances in both contrast-enhanced and noncontrast pMRA.

Combined gadoxetic acid and gadobenate dimeglumine enhanced liver MRI: a parameter optimization study

PURPOSE

To demonstrate the feasibility of combined delayed-phase gadoxetic acid (GA) and gadobenate dimeglumine (GD) enhanced liver MRI for improved detection of liver metastases, and to optimize contrast agent dose, timing, and flip angle (FA).

METHODS

Fourteen healthy volunteers underwent liver MRI at 3.0T at two visits during which they received two consecutive injections: 1. GA (Visit 1 = 0.025 mmol/kg; Visit 2 = 0.05 mmol/kg) and 2. GD (both visits = 0.1 mmol/kg) 20 min after GA administration. Two sub-studies were performed: Experiment-1 Eight subjects underwent multi-phase breath-held 3D-fat-saturated T1-weighted spoiled gradient echo (SGRE) imaging to determine the optimal imaging window for the combined GA + GD protocol to create a homogeneously hyperintense liver and vasculature ("plain-white-liver") with maximum contrast to muscle which served as a surrogate for metastatic lesions in both experiments. Experiment-2 Six subjects underwent breath-held 3D-fat-saturated T1-weighted SGRE imaging at three different FA to determine the optimal FA for best image contrast. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were evaluated.

RESULTS

Experiment-1 The combined GA + GD protocol created a homogeneously hyperintense liver and vasculature with maximum CNR liver/muscle at approximately 60-120 s after automatic GD-bolus detection. Experiment-2 Flip angles between 25° and 35° at a dose of 0.025 mmol/kg GA provided the best combination that minimized liver/vasculature CNR, while maximizing liver/muscle CNR. CNR performance to achieve a "plain-white-liver" was superior with 0.025 mmol/kg GA compared to 0.05 mmol/kg.

CONCLUSION

Combined GA + GD enhanced T1-weighted MRI is feasible to achieve a homogeneously "plain-white-liver". Future studies need to confirm that this protocol can improve sensitivity of liver lesion detection in patients with metastatic liver disease.

Differential Subsampling with Cartesian Ordering for Ultrafast High-Resolution MRA in the Assessment of Intracranial Aneurysms

BACKGROUND AND PURPOSE

We aimed to evaluate the feasibility of an ultrafast whole head contrast-enhanced MRA (CE-MRA) in morphometric assessment of intracranial aneurysms in comparison to routinely used time-of-flight (TOF)-MRA.

METHODS

In this prospective single institutional study, patients with known untreated intracranial aneurysm underwent MRA. Routine multislab TOF-MRA was obtained with a 3D voxel sizes of .6 × .6 × 1 (6-minute acquisition time). CE-MRA of whole head was obtained using Differential Subsampling with Cartesian Ordering (DISCO) and 2D Auto-calibrating Reconstruction for Cartesian imaging with a 3D voxel-sizes of .75 × .75 × 1 mm³ during a 6-second temporal resolution. Morphometric features of intracranial aneurysms, including size, aneurysm sac morphology, and the presence of intraluminal thrombosis, were assessed on both techniques. Statistical analysis was performed using a combination of Kappa test, Bland-Altman, and correlation coefficient analysis.

RESULTS

A total of 34 aneurysms in 28 patients were included. Aneurysm size measurements (mean ± SD) were similar between DISCO-MRA (4.1 ± 2.3 mm) and TOF-MRA (4.3 ± 2.8 mm) (P = .27). Bland-Altman analysis showed a mean difference of .4 mm and there was excellent correlation r = .91 (95% CI: .87-.96). In six aneurysms (17.6%), TOF-MRA was nonconfidant to exclude intraluminal thrombosis. In seven aneurysms (20%), TOF-MRA was unable or nonconfidant in depicting aneurysm sac morphology.

CONCLUSIONS

Described ultrafast high spatial-resolution MRA is superior to routinely used TOF-MRA in assessment of morphometric features of intracranial aneurysms, such as intraluminal thrombosis and aneurysm morphology, and is obtained in a fraction of the time (6 seconds).

Improving GRAPPA reconstruction using joint nonlinear kernel mapped and phase conjugated virtual coils

To improve the reconstruction condition and alleviate the noise amplification of GRAPPA reconstruction by aggregating the phase conjugated and nonlinear kernel mapped coils with the original physical coil. Nonlinear GRAPPA (NL-GRAPPA) is a kernel-based non-iterative approach which can reduce noise-induced error in GRAPPA reconstruction. And virtual conjugate coil (VCC) embeds the conjugate symmetric property of k-space into GRAPPA data synthesis to improve reconstruction condition. This work proposed NL-VCC-GRAPPA to jointly utilize the nonlinear mapped virtual coil and phase conjugated virtual coil to further reduce noise amplification in parallel imaging. In vivo static and dynamic 2D imaging accelerated by uniform undersampling schemes were performed to evaluate the proposed method in terms of visual image quality, root-mean-square-error (RMSE), and geometry factor (g-factor). The effects of acceleration factors, calibration data size and kernel shape on the proposed model were also separately analyzed and discussed. The proposed method illustrated improved visual image quality evidenced by reduced retrospective RMSE and prospective g-factor comparing with conventional GRAPPA and the recently proposed iterative SENSE-LORAKS reconstructions. Although a larger amount of calibration data and smaller kernel size were required to stabilize the calibration of fourfold extended kernel for the proposed method, it was non-iterative and relatively insensitive to parameter adjustment in the applications. The proposed NL-VCC-extension to conventional GRAPPA brings visible improvements for imaging scenarios accelerated by the widely available uniform undersampling schemes in a practically efficient manner without iteration.

MR susceptibility contrast imaging using a 2D simultaneous multi-slice gradient-echo sequence at 7T

Purpose

To develop a 7T simultaneous multi-slice (SMS) 2D gradient-echo sequence for susceptibility contrast imaging, and to compare its quality to 3D imaging.

Methods

A frequency modulated and phase cycled RF pulse was designed to simultaneously excite multiple slices in multi-echo 2D gradient-echo imaging. The imaging parameters were chosen to generate images with susceptibility contrast, including T₂*-weighted magnitude/phase images, susceptibility-weighted images and quantitative susceptibility/R₂* maps. To compare their image quality with 3D gradient-echo imaging, both 2D and 3D imaging were performed on 11 healthy volunteers and 4 patients with multiple sclerosis (MS). The signal to noise ratio (SNR) in gray and white matter and their contrast to noise ratio (CNR) was simulated for the 2D and 3D magnitude images using parameters from the imaging. The experimental SNRs and CNRs were measured in gray/white matter and deep gray matter structures on magnitude, phase, R₂* and QSM images from volunteers and the visibility of MS lesions on these images from patients was visually rated. All SNRs and CNRs were compared between the 2D and 3D imaging using a paired t-test.

Results

Although the 3D magnitude images still had significantly higher SNRs (by 13.0~17.6%), the 2D magnitude and QSM images generated significantly higher gray/white matter or globus pallidus/putamen contrast (by 13.3~87.5%) and significantly higher MS lesion contrast (by 5.9~17.3%).

Conclusion

2D SMS gradient-echo imaging can serve as an alternative to often used 3D imaging to obtain susceptibility-contrast-weighted images, with an advantage of providing better image contrast and MS lesion sensitivity.

Volumetric abdominal perfusion measurement using a pseudo-randomly sampled 3D fast-spin-echo (FSE) arterial spin labeling (ASL) sequence and compressed sensing reconstruction

PURPOSE

To improve image quality and spatial coverage for abdominal perfusion imaging by implementing an arterial spin labeling (ASL) sequence that combines variable-density 3D fast-spin-echo (FSE) with Cartesian trajectory and compressed-sensing (CS) reconstruction.

METHODS

A volumetric FSE sequence was modified to include background-suppressed pseudo-continuous ASL labeling and to support variable-density (VD) Poisson-disk sampling for acceleration. We additionally explored the benefits of center oversampling and variable outer k-space sampling. Fourteen healthy volunteers were scanned on a 3T scanner to test acceleration factors as well as the various sampling schemes described under synchronized-breathing to limit motion issues. A CS reconstruction was implemented using the BART toolbox to reconstruct perfusion-weighted ASL volumes, assessing the impact of acceleration, different reconstruction, and sampling strategies on image quality.

RESULTS

CS acceleration is feasible with ASL, and a strong renal perfusion signal could be observed even at very high acceleration rates (≈15). We have shown that ASL k-space complex subtraction was desirable before CS reconstruction. Although averaging of multiple highly accelerated images helped to reduce artifacts from physiologic fluctuations, superior image quality was achieved by interleaving of different highly undersampled pseudo-random spatial sampling patterns and using 4D-CS reconstruction. Combination of these enhancements produces high-quality ASL volumes in under 5 min.

CONCLUSIONS

High-quality isotropic ASL abdominal perfusion volumes can be obtained in healthy volunteers with a VD-FSE and CS reconstruction. This lays the groundwork for future developments toward whole abdomen free-breathing non-contrast perfusion imaging.

KerNL: Kernel-Based Nonlinear Approach to Parallel MRI Reconstruction

The conventional calibration-based parallel imaging method assumes a linear relationship between the acquired multi-channel k-space data and the unacquired missing data, where the linear coefficients are estimated using some auto-calibration data. In this paper, we first analyze the model errors in the conventional calibration-based methods and demonstrate the nonlinear relationship. Then, a much more general nonlinear framework is proposed for auto-calibrated parallel imaging. In this framework, kernel tricks are employed to represent the general nonlinear relationship between acquired and unacquired k-space data without increasing the computational complexity. Identification of the nonlinear relationship is still performed by solving linear equations. Experimental results demonstrate that the proposed method can achieve reconstruction quality superior to GRAPPA and NL-GRAPPA at high net reduction factors.

Computation of exact g-factor maps in 3D GRAPPA reconstructions

PURPOSE

To characterize the noise distributions in 3D-MRI accelerated acquisitions reconstructed with GRAPPA using an exact noise propagation analysis that operates directly in k-space.

THEORY AND METHODS

We exploit the extensive symmetries and separability in the reconstruction steps to account for the correlation between all the acquired k-space samples. Monte Carlo simulations and multi-repetition phantom experiments were conducted to test both the accuracy and feasibility of the proposed method; a high-resolution in-vivo experiment was performed to assess the applicability of our method to clinical scenarios.

RESULTS

Our theoretical derivation shows that the direct k-space analysis renders an exact noise characterization under the assumptions of stationarity and uncorrelation in the original k-space. Simulations and phantom experiments provide empirical support to the theoretical proof. Finally, the high-resolution in-vivo experiment demonstrates the ability of the proposed method to assess the impact of the sub-sampling pattern on the overall noise behavior.

CONCLUSIONS

By operating directly in the k-space, the proposed method is able to provide an exact characterization of noise for any Cartesian pattern sub-sampled along the two phase-encoding directions. Exploitation of the symmetries and separability into independent blocks through the image reconstruction procedure allows us to overcome the computational challenges related to the very large size of the covariance matrices involved.

Diagnosing common bile duct obstruction: comparison of image quality and diagnostic performance of three-dimensional magnetic resonance cholangiopancreatography with and without compressed sensing

PURPOSE

This study aimed to evaluate image quality and diagnostic performance of a recently developed navigated three-dimensional magnetic resonance cholangiopancreatography (3D-MRCP) with compressed sensing (CS) based on parallel imaging (PI) and conventional 3D-MRCP with PI only in patients with abnormal bile duct dilatation.

METHODS

This institutional review board-approved study included 45 consecutive patients [non-malignant common bile duct lesions (n = 21) and malignant common bile duct lesions (n = 24)] who underwent MRCP of the abdomen to evaluate bile duct dilatation. All patients were imaged at 3T (MR 750, GE Healthcare, Waukesha, WI) including two kinds of 3D-MRCP using 352 × 288 matrices with and without CS based on PI. Two radiologists independently and blindly assessed randomized images.

RESULTS

CS acceleration reduced the acquisition time on average 5 min and 6 s to a total of 2 min and 56 s. The all CS cine image quality was significantly higher than standard cine MR image for all quantitative measurements. Diagnostic accuracy for benign and malignant lesions is statistically different between standard and CS 3D-MRCP.

CONCLUSIONS

Total image quality and diagnostic accuracy at biliary obstruction evaluation demonstrates that CS-accelerated 3D-MRCP sequences can provide superior quality of diagnostic information in 42.5% less time. This has the potential to reduce motion-related artifacts and improve diagnostic efficacy.

Quantification of Liver Fat Content With Unenhanced MDCT: Phantom and Clinical Correlation With MRI Proton Density Fat Fraction

OBJECTIVE

The purpose of this study was to evaluate the relation between unenhanced CT liver attenuation values and MRI-derived proton density fat fraction (PDFF) for estimation of liver fat content at CT.

MATERIALS AND METHODS

A CT-MRI phantom was constructed and imaged containing 12 vials with lipid fractions ranging from 0% to 100%. For the retrospective clinical arm, 221 patients (120 men, 101 women; mean age, 54 years) underwent both unenhanced CT and chemical shift-encoded MRI of the liver between 2007 and 2017. Among these patients, 92 had more than one 120-kV CT scan for comparison. CT attenuation and MRI PDFF were derived with coregistered ROI measurements in the right hepatic lobe. The 120-kV subgroup of CT examinations performed within 1 month of MRI PDFF examinations (n = 72) served as the primary cohort for linear correlation. The effects of different tube voltage settings, time intervals between CT and MRI, and iron overload were assessed. Linear least squares regression analysis was performed.

RESULTS

Phantom results showed excellent linear fit between CT attenuation and MRI PDFF (r² = 0.986). In patients, 120-kV CT performed within 1 month of MRI PDFF exhibited strong linear correlation (r² = 0.828) that closely matched the phantom data, yielding the following clinical CT-MRI conversion formula: MRI PDFF (%) = -0.58 × CT attenuation (HU) + 38.2. Correlation worsened for CT-to-MRI intervals longer than 1 month (r² = 0.565), and this specific relationship did not apply as well to non-120-kV settings (r² = 0.554). For patients with multiple scans, correlation progressively worsened over time. CT-based liver fat content was underestimated in several patients with iron overload.

CONCLUSION

The linear correlation between unenhanced CT attenuation and MRI PDFF allows quantification of liver fat content by means of unenhanced CT in clinical practice. As expected, correlation worsened with increasing CT-MRI time interval, variable tube voltage settings, and iron overload.

Magnetic resonance angiography for the primary diagnosis of pulmonary embolism: A review from the international workshop for pulmonary functional imaging

Pulmonary contrast enhanced magnetic resonance angiography (CE-MRA) is useful for the primary diagnosis of pulmonary embolism (PE). Many sites have chosen not to use CE-MRA as a first line of diagnostic tool for PE because of the speed and higher efficacy of computerized tomographic angiography (CTA). In this review, we discuss the strengths and weaknesses of CE-MRA and the appropriate imaging scenarios for the primary diagnosis of PE derived from our unique multi-institutional experience in this area. The optimal patient for this test has a low to intermediate suspicion for PE based on clinical decision rules. Patients in extremis are not candidates for this test. Younger women (< 35 years of age) and patients with iodinated contrast allergies are best served by using this modality We discuss the history of the use of this test, recent technical innovations, artifacts, direct and indirect findings for PE, ancillary findings, and the effectiveness (patient outcomes) of CE-MRA for the exclusion of PE. Current outcomes data shows that CE-MRA and NM V/Q scans are effective alternative tests to CTA for the primary diagnosis of PE.

The cost effectiveness and utility of a "quick MRI" for the evaluation of intra-abdominal abscess after acute appendicitis in the pediatric patient population

INTRODUCTION

Contrast-enhanced CT remains the first-line imaging for evaluating postoperative abscess (POA) after appendicitis. Given concerns of ionizing radiation use in children, we began utilizing quick MRI to evaluate POA and summarize our findings in this study.

MATERIALS AND METHODS

Children imaged with quick MRI from 2015 to 2017 were compared to children evaluated with CT from 2012 to 2014 using an age and weight matched case-control model. Radiation exposure, size and number of abscesses, length of exam, drain placement, and patient outcomes were compared.

RESULTS

There was no difference in age or weight (p>0.60) between children evaluated with quick MRI (n=16) and CT (n=16). Mean imaging time was longer (18.2±8.5min) for MRI (p<0.001), but there was no difference in time from imaging order to drain placement (p=0.969). No children required sedation or had non-diagnostic imaging. There were no differences in abscess volume (p=0.346) or drain placement (p=0.332). Thirty-day follow-up showed no difference in readmissions (p=0.551) and no missed abscesses. Quick MRI reduced imaging charges to $1871 from $5650 with CT.

CONCLUSION

Quick MRI demonstrated equivalent outcomes to CT in terms of POA detection, drain placement, and 30-day complications suggesting that MRI provides an equally effective, less expensive, and non-radiation modality for the identification of POA.

TYPE OF STUDY

Retrospective Case-Control Study.

LEVEL OF EVIDENCE

Level III.

Clinical outcomes after magnetic resonance angiography (MRA) versus computed tomographic angiography (CTA) for pulmonary embolism evaluation

PURPOSE

To compare patient outcomes following magnetic resonance angiography (MRA) versus computed tomographic angiography (CTA) ordered for suspected pulmonary embolism (PE).

METHODS

In this IRB-approved, single-center, retrospective, case-control study, we reviewed the medical records of all patients evaluated for PE with MRA during a 5-year period along with age- and sex-matched controls evaluated with CTA. Only the first instance of PE evaluation during the study period was included. After application of our exclusion criteria to both study arms, the analysis included 1173 subjects. The primary endpoint was major adverse PE-related event (MAPE), which we defined as major bleeding, venous thromboembolism, or death during the 6 months following the index imaging test (MRA or CTA), obtained through medical record review. Logistic regression, chi-square test for independence, and Fisher's exact test were used with a p < 0.05 threshold.

RESULTS

The overall 6-month MAPE rate following MRA (5.4%) was lower than following CTA (13.6%, p < 0.01). Amongst outpatients, the MAPE rate was lower for MRA (3.7%) than for CTA (8.0%, p = 0.01). Accounting for age, sex, referral source, BMI, and Wells' score, patients were less likely to suffer MAPE than those who underwent CTA, with an odds ratio of 0.44 [0.24, 0.80]. Technical success rate did not differ significantly between MRA (92.6%) and CTA (90.5%) groups (p = 0.41).

CONCLUSION

Within the inherent limitations of a retrospective case-controlled analysis, we observed that the rate of MAPE was lower (more favorable) for patients following pulmonary MRA for the primary evaluation of suspected PE than following CTA.

Characterization and evaluation of a flexible MRI receive coil array for radiation therapy MR treatment planning using highly decoupled RF circuits

The growth in the use of magnetic resonance imaging (MRI) data for radiation therapy (RT) treatment planning has been facilitated by scanner hardware and software advances that have enabled RT patients to be imaged in treatment position while providing morphologic and functional assessment of tumor volumes and surrounding normal tissues. Despite these advances, manufacturers have been slow to develop radiofrequency (RF) coils that closely follow the contour of a RT patient undergoing MR imaging. Instead, relatively large form surface coil arrays have been adapted from diagnostic imaging. These arrays can be challenging to place on, and in general do not conform to the patient's body habitus, resulting in sub optimal image quality. The purpose of this study is to report on the characterization of a new flexible and highly decoupled RF coil for use in MR imaging of RT patients. Coil performance was evaluated by performing signal-to-noise ratio (SNR) and noise correlation measurements using two coil (SNR) and four coil (noise correlation) element combinations as a function of coil overlap distance and comparing these values to those obtained using conventional coil elements. In vivo testing was performed in both normal volunteers and patients using a four and 16 element RF coil. Phantom experiments demonstrate the highly decoupled nature of the new coil elements when compared to conventional RF coils, while in vivo testing demonstrate that these coils can be integrated into extremely flexible and form fitting substrates that follow the exact contour of the patient. The new coil design addresses limitations imposed by traditional surface coil arrays and have the potential to significantly impact MR imaging for both diagnostic and RT applications.

Exact Calculation of Noise Maps and ${g}$ -Factor in GRAPPA Using a ${k}$ -Space Analysis

Characterization of the noise distribution in magnetic resonance images has multiple applications, including quality assurance and protocol optimization. Noise characterization is particularly important in the presence of parallel imaging acceleration with multi-coil acquisitions, where the noise distribution can contain severe spatial heterogeneities. If the parallel imaging reconstruction is a linear process, an accurate noise analysis can be carried out by taking into account the correlations between all the samples involved. However, for -space-based techniques such as generalized autocalibrating partially parallel acquisition (GRAPPA), the exact analysis has been considered computationally prohibitive due to the very large size of the noise covariance matrices required to characterize the noise propagation from -space to image space. Previously proposed methods avoid this computational burden by formulating the GRAPPA reconstruction as a pixel-wise linear operation performed in the image space. However, these methods are not exact in the presence of non-uniform sampling of -space (e.g., containing a calibration region). For this reason, in this paper, we develop an accurate characterization of the noise distribution for self-calibrated parallel imaging in the presence of arbitrary Cartesian sampling patterns. By exploiting the symmetries and separability in the noise propagation process, the proposed method is computationally efficient and does not require large matrices. Under the assumption of a fixed reconstruction kernel, this method provides the precise distribution of the noise variance for each coil's image. These coil-by-coil noise maps are subsequently combined according to the coil combination approach used in image reconstruction, and therefore can be applied with both complex coil combination and root-sum-of-squares approaches. In this paper, we present the proposed noise characterization method and compare it to previous techniques using Monte Carlo simulations as well as phantom acquisitions.

Iterative Schemes to Solve Low-Dimensional Calibration Equations in Parallel MR Image Reconstruction with GRAPPA

GRAPPA (Generalized Autocalibrating Partially Parallel Acquisition) is a widely used parallel MRI reconstruction technique. The processing of data from multichannel receiver coils may increase the storage and computational requirements of GRAPPA reconstruction. Random projection on GRAPPA (RP-GRAPPA) uses random projection (RP) method to overcome the computational overheads of solving large linear equations in the calibration phase of GRAPPA, saving reconstruction time. However, RP-GRAPPA compromises the reconstruction accuracy in case of large reductions in the dimensions of calibration equations. In this paper, we present the implementation of GRAPPA reconstruction method using potential iterative solvers to estimate the reconstruction coefficients from the randomly projected calibration equations. Experimental results show that the proposed methods withstand the reconstruction accuracy (visually and quantitatively) against large reductions in the dimension of linear equations, when compared with RP-GRAPPA reconstruction. Particularly, the proposed method using conjugate gradient for least squares (CGLS) demonstrates more savings in the computational time of GRAPPA, without significant loss in the reconstruction accuracy, when compared with RP-GRAPPA. It is also demonstrated that the proposed method using CGLS complements the channel compression method for reducing the computational complexities associated with higher channel count, thereby resulting in additional memory savings and speedup.