SENSE with improved tolerance to inaccuracies in coil sensitivity maps

Characterization of Effects of Compressed Sensing on High Spectral and Spatial Resolution (HiSS) MRI with Comparison to SENSE

High Spectral and Spatial resolution (HiSS) MRI shows high diagnostic performance in the breast. Acceleration methods based on k-space undersampling could allow stronger T2*-based image contrast and/or higher spectral resolution, potentially increasing diagnostic performance. An agar/oil phantom was prepared with water-fat boundaries perpendicular to the readout and phase encoding directions in a breast coil. HiSS MRI was acquired at 3T, at sensitivity encoding (SENSE) acceleration factors R of up to 10, and the R = 1 dataset was used to simulate corresponding compressed sensing (CS) accelerations. Image quality was evaluated by quantifying noise and artifact levels. Effective spatial resolution was determined via modulation transfer function analysis. Dispersion vs. absorption (DISPA) analysis and full width at half maximum (FWHM) quantified spectral lineshape changes. Noise levels remained constant with R for CS but amplified with SENSE. SENSE preserved the spatial resolution of HiSS MRI, while CS reduced it in the phase encoding direction. SENSE showed no effect on FWHM or DISPA markers, while CS increased FWHM. Thus, CS might perform better in noise-limited or geometrically constrained applications, but in geometric configurations specific to breast MRI, spectral analysis might be compromised, decreasing the diagnostic performance of HiSS MRI.

Technical Advancements in Abdominal Diffusion-weighted Imaging

Since its first observation in the 18th century, the diffusion phenomenon has been actively studied by many researchers. Diffusion-weighted imaging (DWI) is a technique to probe the diffusion of water molecules and create a MR image with contrast based on the local diffusion properties. The DWI pixel intensity is modulated by the hindrance the diffusing water molecules experience. This hindrance is caused by structures in the tissue and reflects the state of the tissue. This characteristic makes DWI a unique and effective tool to gain more insight into the tissue's pathophysiological condition. In the past decades, DWI has made dramatic technical progress, leading to greater acceptance in clinical practice. In the abdominal region, however, acquiring DWI with good quality is challenging because of several reasons, such as large imaging volume, respiratory and other types of motion, and difficulty in achieving homogeneous fat suppression. In this review, we discuss technical advancements from the past decades that help mitigate these problems common in abdominal imaging. We describe the use of scan acceleration techniques such as parallel imaging and compressed sensing to reduce image distortion in echo planar imaging. Then we compare techniques developed to mitigate issues due to respiratory motion, such as free-breathing, respiratory-triggering, and navigator-based approaches. Commonly used fat suppression techniques are also introduced, and their effectiveness is discussed. Additionally, the influence of the abovementioned techniques on image quality is demonstrated. Finally, we discuss the current and future clinical applications of abdominal DWI, such as whole-body DWI, simultaneous multiple-slice excitation, intravoxel incoherent motion, and the use of artificial intelligence. Abdominal DWI has the potential to develop further in the future, thanks to scan acceleration and image quality improvement driven by technological advancements. The accumulation of clinical proof will further drive clinical acceptance.

Motion artifact reduction for magnetic resonance imaging with deep learning and k-space analysis

Motion artifacts deteriorate the quality of magnetic resonance (MR) images. This study proposes a new method to detect phase-encoding (PE) lines corrupted by motion and remove motion artifacts in MR images. 67 cases containing 8710 slices of axial T2-weighted images from the IXI public dataset were split into three datasets, i.e., training (50 cases/6500 slices), validation (5/650), and test (12/1560) sets. First, motion-corrupted k-spaces and images were simulated using a pseudo-random sampling order and random motion tracks. A convolutional neural network (CNN) model was trained to filter the motion-corrupted images. Then, the k-space of the filtered image was compared with the motion-corrupted k-space line-by-line, to detect the PE lines affected by motion. Finally, the unaffected PE lines were used to reconstruct the final image using compressed sensing (CS). For the simulated images with 35%, 40%, 45%, and 50% unaffected PE lines, the mean peak signal-to-noise ratio (PSNRs) of resulting images (mean±standard deviation) were 36.129±3.678, 38.646±3.526, 40.426±3.223, and 41.510±3.167, respectively, and the mean structural similarity (SSIMs) were 0.950±0.046, 0.964±0.035, 0.975±0.025, and 0.979±0.023, respectively. For images with more than 35% PE lines unaffected by motion, images reconstructed with proposed algorithm exhibited better quality than those images reconstructed with CS using 35% under-sampled data (PSNR 37.678±3.261, SSIM 0.964±0.028). It was proved that deep learning and k-space analysis can detect the k-space PE lines affected by motion and CS can be used to reconstruct images from unaffected data, effectively alleviating the motion artifacts.

State-of-the-art magnetic resonance imaging sequences for pediatric body imaging

Longer examination time, need for anesthesia in smaller children and the inability of most children to hold their breath are major limitations of MRI in pediatric body imaging. Fortunately, with technical advances, many new and upcoming MRI sequences are overcoming these limitations. Advances in data acquisition and k-space sampling methods have enabled sequences with improved temporal and spatial resolution, and minimal artifacts. Sequences to minimize movement artifacts mainly utilize radial k-space filling, and examples include the stack-of-stars method for T1-weighted imaging and the periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER)/BLADE method for T2-weighted imaging. Similarly, the sequences with improved temporal resolution and the ability to obtain multiple phases in a single breath-hold in dynamic imaging mainly use some form of partial k-space filling method. New sequences use a variable combination of data sampling methods like compressed sensing, golden-angle radial k-space filling, parallel imaging and partial k-space filling to achieve free-breathing, faster sequences that could be useful for pediatric abdominal and thoracic imaging. Simultaneous multi-slice method has improved diffusion-weighted imaging (DWI) with reduction in scan time and artifacts. In this review, we provide an overview of data sampling methods like parallel imaging, compressed sensing, radial k-space sampling, partial k-space sampling and simultaneous multi-slice. This is followed by newer available and upcoming sequences for T1-, T2- and DWI based on these other advances. We also discuss the Dixon method and newer approaches to reducing metal artifacts.

Rapid Imaging: Recent Advances in Abdominal MRI for Reducing Acquisition Time and Its Clinical Applications

Magnetic resonance imaging (MRI) plays an important role in abdominal imaging. The high contrast resolution offered by MRI provides better lesion detection and its capacity to provide multiparametric images facilitates lesion characterization more effectively than computed tomography. However, the relatively long acquisition time of MRI often detrimentally affects the image quality and limits its accessibility. Recent developments have addressed these drawbacks. Specifically, multiphasic acquisition of contrast-enhanced MRI, free-breathing dynamic MRI using compressed sensing technique, simultaneous multi-slice acquisition for diffusion-weighted imaging, and breath-hold three-dimensional magnetic resonance cholangiopancreatography are recent notable advances in this field. This review explores the aforementioned state-of-the-art techniques by focusing on their clinical applications and potential benefits, as well as their likely future direction.

Chemical exchange saturation transfer (CEST) imaging with fast variably-accelerated sensitivity encoding (vSENSE)

PURPOSE

The widespread clinical use of chemical exchange saturation transfer (CEST) imaging is hampered by relatively long scan times due to its requirement that multiple saturation-offset image frames be acquired. Here, a novel variably-accelerated sensitivity encoding (vSENSE) method is proposed that provides faster CEST acquisition than conventional SENSE.

THEORY AND METHODS

The vSENSE method fully samples one CEST saturation frame, then undersamples the other frames variably. The fully-sampled frame, in conjunction with newly proposed incoherence absorption and artifact suppression strategies, improves the accuracy of sensitivity maps and permits higher acceleration factors for the other undersampled frames than regular SENSE. vSENSE is validated in a phantom, a normal volunteer and eight brain tumor patients at 3 Tesla.

RESULTS

vSENSE with an acceleration factor of four generated a 3-6 times smaller error on average than conventional SENSE (P ≤ 0.02), with acceleration factors of 2-4, as compared with full k-space reconstruction. vSENSE permitted four-fold acceleration for amide proton transfer-weighted images, while regular SENSE could only provide a factor of two. When conventional SENSE is used with vSENSE's variable undersampling pattern, erroneous (∼9%) z-spectra result.

CONCLUSION

The vSENSE method enabled twice the acceleration and generated more accurate images than conventional SENSE. Magn Reson Med 77:2225-2238, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Fat-suppressed, three-dimensional T1-weighted imaging using high-acceleration parallel acquisition and a dual-echo Dixon technique for gadoxetic acid-enhanced liver MRI at 3 T

BACKGROUND

Parallel imaging (PI) techniques are used for overcoming lower spatial and time resolution for magnetic resonance imaging (MRI). There is clinical need to overcome inevitable noise by decreased voxel size and signal-to-noise issue by using high-acceleration factor (AF).

PURPOSE

To determine whether the combination of a modified Dixon three-dimensional (3D) T1-weighted (T1W) gradient echo technique (mDixon-3D-GRE) and high-acceleration ([HA], AF = 5) PI can provide breath-hold (BH) T1W imaging with better image quality than conventional fat-suppressed 3D-T1W-GRE (SPAIR-3D-GRE) for Gd-EOB-DTPA-enhanced liver MR.

MATERIAL AND METHODS

This retrospective study was approved by our institutional review board and informed consent was waived. There were 138 patients who underwent Gd-EOB-DTPA-enhanced liver MR at 3 T using either standard SPAIR-3D-GRE sequences with an AF of 2.6 (n = 68, Standard group) or mDixon-3D-GRE with an AF of 5 (n = 70, HA group). In the HA group, hepatobiliary phase was obtained three times using HA-mDixon-3D-GRE (AF = 5), HA-SPAIR-3D-GRE (AF = 5), and standard-SPAIR-3D-GRE (AF = 2.6). Image noise, quality, and anatomic depiction of dynamic phase were compared between standard and HA groups, and those of hepatobiliary phase were compared among the three image sets in HA group.

RESULTS

As for dynamic imaging, the HA-mDixon-3D-GRE images showed better anatomic details and overall image quality than standard-SPAIR-3D-GRE sequence (arterial phase: 3.56 ± 0.63 vs. 2.66 ± 0.69, P < 0.001). In the intra-individual comparison, HA-mDixon-3D-GRE provided better orang depiction and overall image quality than standard-SPAIR-3D-GRE (3.99 ± 0.75 vs. 3.0 ± 0.72, P < 0.001) and better fat suppression and significantly less noise than HA-SPAIR-3D-GRE (4.76 ± 0.43 vs. 3.71 ± 0.54, P < 0.001).

CONCLUSION

The combined use of mDixon-3D-GRE sequence and high-acceleration PI provided better quality BH-T1W imaging compared with conventional SPAIR-3D-GRE for Gd-EOB-DTPA-enhanced liver MRI.

RARE/turbo spin echo imaging with Simultaneous Multislice Wave-CAIPI

PURPOSE

To enable highly accelerated RARE/Turbo Spin Echo (TSE) imaging using Simultaneous MultiSlice (SMS) Wave-CAIPI acquisition with reduced g-factor penalty.

METHODS

SMS Wave-CAIPI incurs slice shifts across simultaneously excited slices while playing sinusoidal gradient waveforms during the readout of each encoding line. This results in an efficient k-space coverage that spreads aliasing in all three dimensions to fully harness the encoding power of coil sensitivities. The novel MultiPINS radiofrequency (RF) pulses dramatically reduce the power deposition of multiband (MB) refocusing pulse, thus allowing high MB factors within the Specific Absorption Rate (SAR) limit.

RESULTS

Wave-CAIPI acquisition with MultiPINS permits whole brain coverage with 1 mm isotropic resolution in 70 s at effective MB factor 13, with maximum and average g-factor penalties of gmax  = 1.34 and gavg  = 1.12, and without √R penalty. With blipped-CAIPI, the g-factor performance was degraded to gmax  = 3.24 and gavg  = 1.42; a 2.4-fold increase in gmax relative to Wave-CAIPI. At this MB factor, the SAR of the MultiBand and PINS pulses are 4.2 and 1.9 times that of the MultiPINS pulse, while the peak RF power are 19.4 and 3.9 times higher.

CONCLUSION

Combination of the two technologies, Wave-CAIPI and MultiPINS pulse, enables highly accelerated RARE/TSE imaging with low SNR penalty at reduced SAR.

Motion artifacts in MRI: A complex problem with many partial solutions

Subject motion during magnetic resonance imaging (MRI) has been problematic since its introduction as a clinical imaging modality. While sensitivity to particle motion or blood flow can be used to provide useful image contrast, bulk motion presents a considerable problem in the majority of clinical applications. It is one of the most frequent sources of artifacts. Over 30 years of research have produced numerous methods to mitigate or correct for motion artifacts, but no single method can be applied in all imaging situations. Instead, a "toolbox" of methods exists, where each tool is suitable for some tasks, but not for others. This article reviews the origins of motion artifacts and presents current mitigation and correction methods. In some imaging situations, the currently available motion correction tools are highly effective; in other cases, appropriate tools still need to be developed. It seems likely that this multifaceted approach will be what eventually solves the motion sensitivity problem in MRI, rather than a single solution that is effective in all situations. This review places a strong emphasis on explaining the physics behind the occurrence of such artifacts, with the aim of aiding artifact detection and mitigation in particular clinical situations.

Transmit and receive RF fields determination from a single low-tip-angle gradient-echo scan by scaling of SVD data

PURPOSE

A new method, called Transmit and Receive Patterns from Low-Tip-angle gradient-Echo Images (TRIPLET), is described which simultaneously maps the B1+ and B1- fields of a transmit/receive radiofrequency coil array. The input data are low-tip-angle gradient-echo images, which can be acquired in a relatively short scanning time.

THEORY AND METHODS

For each voxel in the field of view, a matrix can be assembled with the low-tip-angle gradient-echo image values of the radiofrequency coil array. Applying the singular value decomposition to those matrices, datasets are obtained which show a high resemblance with the true B1+ and B1- fields. These datasets are a voxel-wise scaled version of the true radiofrequency maps. The channel independent scaling parameters can be found by implicitly forcing the reconstructed fields to be solutions of the Maxwell equations. This is achieved by introducing a multipole expansion consisting of Bessel/Fourier functions.

RESULTS

Two FDTD simulated radiofrequency fields for two coil array combinations at 7 T and a measured, in vivo dataset at 7 T are investigated to illustrate the singular value decomposition analysis of the low-tip-angle gradient-echo images and to show how the B1+ and B1- fields can be reconstructed by Transmit and Receive Patterns from Low-Tip-angle gradient-Echo Images.

CONCLUSION

The Transmit and Receive Patterns from Low-Tip-angle gradient-Echo Images algorithm can convert the datasets from singular value decomposition analysis of low-tip-angle gradient-echo images to true B1+ and B1- fields.