Robust EPI Nyquist ghost elimination via spatial and temporal encoding

SENSE EPI reconstruction with 2D phase error correction and channel-wise noise removal

PURPOSE

To develop a robust reconstruction pipeline for EPI data that enables 2D Nyquist phase error correction using sensitivity encoding without incurring major noise artifacts in low SNR data.

METHODS

SENSE with 2D phase error correction (PEC-SENSE) was combined with channel-wise noise removal using Marcenko-Pastur principal component analysis (MPPCA) to simultaneously eliminate Nyquist ghost artifacts in EPI data and mitigate the noise amplification associated with phase correction using parallel imaging. The proposed pipeline (coined SPECTRE) was validated in phantom DW-EPI data using the accuracy and precision of diffusion metrics; ground truth values were obtained from data acquired with a spin echo readout. Results from the SPECTRE pipeline were compared against PEC-SENSE reconstructions with three alternate denoising strategies: (i) no denoising; (ii) denoising of magnitude data after image formation; (iii) denoising of complex data after image formation. SPECTRE was then tested using highb $$ b $$ -value (i.e., low SNR) diffusion data (up tob = 3000 $$ b=3000 $$  s/mm2 $$ {}^2 $$ ) in four healthy subjects.

RESULTS

Noise amplification associated with phase error correction incurred a 23% bias in phantom mean diffusivity (MD) measurements. Phantom MD estimates using the SPECTRE pipeline were within 8% of the ground truth value. In healthy volunteers, the SPECTRE pipeline visibly corrected Nyquist ghost artifacts and reduced associated noise amplification in highb $$ b $$ -value data.

CONCLUSION

The proposed reconstruction pipeline is effective in correcting low SNR data, and improves the accuracy and precision of derived diffusion metrics.

EPI phase error correction with deep learning (PEC-DL) at 7 T

PURPOSE

The phase mismatch between odd and even echoes in EPI causes Nyquist ghost artifacts. Existing ghost correction methods often suffer from severe residual artifacts and are ineffective with k-space undersampling data. This study proposed a deep learning-based method (PEC-DL) to correct phase errors for DWI at 7 Tesla.

METHODS

The acquired k-space data were divided into 2 independent undersampled datasets according to their readout polarities. Then the proposed PEC-DL network reconstructed 2 ghost-free images using the undersampled data without calibration and navigator data. The network was trained with fully sampled images and applied to two- and fourfold accelerated data. Healthy volunteers and patients with Moyamoya disease were recruited to validate the efficacy of the PEC-DL method.

RESULTS

The PEC-DL method was capable to mitigate the ghost artifacts in DWI in healthy volunteers as well as patients with Moyamoya disease. The fourfold accelerated results showed much less distortion in the lesions of the Moyamoya patient using high b-value DWI and the corresponding ADC maps. The ghost-to-signal ratios were significantly lower in PEC-DL images compared to conventional linear phase corrections, mini-entropy, and PEC-GRAPPA algorithms.

CONCLUSION

The proposed method can effectively eliminate ghost artifacts for full sampled and up to fourfold accelerated EPI data without calibration and navigator data.

Magnetic resonance elastography for estimating in vivo stiffness of the abdominal aorta using cardiac-gated spin-echo echo-planar imaging: a feasibility study

INTRODUCTION

Magnetic resonance elastography (MRE)-derived aortic stiffness is a potential biomarker for multiple cardiovascular diseases. Currently, gradient-recalled echo (GRE) MRE is a widely accepted technique to estimate aortic stiffness. However, multi-slice GRE MRE requires multiple breath-holds (BHs), which can be challenging for patients who cannot consistently hold their breath. The aim of this study was to investigate the feasibility of a multi-slice spin-echo echo-planar imaging (SE-EPI) MRE sequence for quantifying in vivo aortic stiffness using a free-breathing (FB) protocol and a single-BH protocol.

METHOD

On Scanner 1, 25 healthy subjects participated in the validation of FB SE-EPI against FB GRE. On Scanner 2, another 15 healthy subjects were recruited to compare FB SE-EPI with single-BH SE-EPI. Among all volunteers, five participants were studied on both scanners to investigate the inter-scanner reproducibility of FB SE-EPI aortic MRE. Bland-Altman analysis, Lin's concordance correlation coefficient (LCCC) and coefficient of variation (COV) were evaluated. The phase-difference signal-to-noise ratios (PD SNR) were compared.

RESULTS

Aortic MRE using FB SE-EPI and FB GRE yielded similar stiffnesses (paired t-test, P = 0.19), with LCCC = 0.97. The FB SE-EPI measurements were reproducible (intra-scanner LCCC = 0.96) and highly repeatable (LCCC = 0.99). The FB SE-EPI MRE was also reproducible across different scanners (inter-scanner LCCC = 0.96). Single-BH SE-EPI scans yielded similar stiffness to FB SE-EPI scans (LCCC = 0.99) and demonstrated a low COV of 2.67% across five repeated measurements.

CONCLUSION

Multi-slice SE-EPI aortic MRE using an FB protocol or a single-BH protocol is reproducible and repeatable with advantage over multi-slice FB GRE in reducing acquisition time. Additionally, FB SE-EPI MRE provides a potential alternative to BH scans for patients who have challenges in holding their breath.

Robust autocalibrated structured low-rank EPI ghost correction

PURPOSE

We propose and evaluate a new structured low-rank method for echo-planar imaging (EPI) ghost correction called Robust Autocalibrated LORAKS (RAC-LORAKS). The method can be used to suppress EPI ghosts arising from the differences between different readout gradient polarities and/or the differences between different shots. It does not require conventional EPI navigator signals, and is robust to imperfect autocalibration data.

METHODS

Autocalibrated LORAKS is a previous structured low-rank method for EPI ghost correction that uses GRAPPA-type autocalibration data to enable high-quality ghost correction. This method works well when the autocalibration data are pristine, but performance degrades substantially when the autocalibration information is imperfect. RAC-LORAKS generalizes Autocalibrated LORAKS in two ways. First, it does not completely trust the information from autocalibration data, and instead considers the autocalibration and EPI data simultaneously when estimating low-rank matrix structure. Second, it uses complementary information from the autocalibration data to improve EPI reconstruction in a multi-contrast joint reconstruction framework. RAC-LORAKS is evaluated using simulations and in vivo data, including comparisons to state-of-the-art methods.

RESULTS

RAC-LORAKS is demonstrated to have good ghost elimination performance compared to state-of-the-art methods in several complicated EPI acquisition scenarios (including gradient-echo brain imaging, diffusion-encoded brain imaging, and cardiac imaging).

CONCLUSIONS

RAC-LORAKS provides effective suppression of EPI ghosts and is robust to imperfect autocalibration data.

Simultaneous Motion and Distortion Correction Using Dual-Echo Diffusion-Weighted MRI

BACKGROUND AND PURPOSE

Geometric distortions resulting from large pose changes reduce the accuracy of motion measurements and interfere with the ability to generate artifact-free information. Our goal is to develop an algorithm and pulse sequence to enable motion-compensated, geometric distortion compensated diffusion-weighted MRI, and to evaluate its efficacy in correcting for the field inhomogeneity and position changes, induced by large and frequent head motions.

METHODS

Dual echo planar imaging (EPI) with a blip-reversed phase encoding distortion correction technique was evaluated in five volunteers in two separate experiments and compared with static field map distortion correction. In the first experiment, dual-echo EPI images were acquired in two head positions designed to induce a large field inhomogeneity change. A field map and a distortion-free structural image were acquired at each position to assess the ability of dual-echo EPI to generate reliable field maps and enable geometric distortion correction in both positions. In the second experiment, volunteers were asked to move to multiple random positions during a diffusion scan. Images were reconstructed using the dual-echo correction and a slice-to-volume registration (SVR) registration algorithm. The accuracy of SVR motion estimates was compared to externally measured ground truth motion parameters.

RESULTS

Our results show that dual-echo EPI can produce slice-level field maps with comparable quality to field maps generated by the reference gold standard method. We also show that slice-level distortion correction improves the accuracy of SVR algorithms as slices acquired at different orientations have different levels of distortion, which can create errors in the registration process.

CONCLUSIONS

Dual-echo acquisitions with blip-reversed phase encoding can be used to generate slice-level distortion-free images, which is critical for motion-robust slice to volume registration. The distortion corrected images not only result in better motion estimates, but they also enable a more accurate final diffusion image reconstruction.

k-Space deep learning for reference-free EPI ghost correction

PURPOSE

Nyquist ghost artifacts in echo planar imaging (EPI) are originated from phase mismatch between the even and odd echoes. However, conventional correction methods using reference scans often produce erroneous results especially in high-field MRI due to the nonlinear and time-varying local magnetic field changes. Recently, it was shown that the problem of ghost correction can be reformulated as k-space interpolation problem that can be solved using structured low-rank Hankel matrix approaches. Another recent work showed that data driven Hankel matrix decomposition can be reformulated to exhibit similar structures as deep convolutional neural network. By synergistically combining these findings, we propose a k-space deep learning approach that immediately corrects the phase mismatch without a reference scan in both accelerated and non-accelerated EPI acquisitions.

THEORY AND METHODS

To take advantage of the even and odd-phase directional redundancy, the k-space data are divided into 2 channels configured with even and odd phase encodings. The redundancies between coils are also exploited by stacking the multi-coil k-space data into additional input channels. Then, our k-space ghost correction network is trained to learn the interpolation kernel to estimate the missing virtual k-space data. For the accelerated EPI data, the same neural network is trained to directly estimate the interpolation kernels for missing k-space data from both ghost and subsampling.

RESULTS

Reconstruction results using 3T and 7T in vivo data showed that the proposed method outperformed the image quality compared to the existing methods, and the computing time is much faster.

CONCLUSIONS

The proposed k-space deep learning for EPI ghost correction is highly robust and fast, and can be combined with acceleration, so that it can be used as a promising correction tool for high-field MRI without changing the current acquisition protocol.

Nyquist ghost correction of breast diffusion weighted imaging using referenceless methods

PURPOSE

Correction of Nyquist ghosts for single-shot spin-echo EPI using the standard 3-line navigator often fails in breast DWI because of incomplete fat suppression, respiration, and greater B₀ inhomogeneity. The purpose of this work is to compare the performance of the 3-line navigator with 4 data-driven methods termed "referenceless methods," including 2 previously proposed in literature, 1 introduced in this work, and finally a combination of all 3, in breast DWI.

METHODS

Breast DWI was acquired for 41 patients with SS SE-EPI. Raw data was corrected offline with the standard 3-line navigator and 4 referenceless methods, which modeled the ghost as a linear phase error and minimized 3 unique cost functions as well as the median solution of all 3. Ghost levels were evaluated based on the signal intensity in the background region, defined by a mask auto-generated from a T₁ -weighted anatomical image. Ghost intensity measurements were fit to a linear mixed model including ghost correction method and b-value as covariates.

RESULTS

All 4 referenceless methods outperformed the standard 3-line navigator with statistical significance at all 4 b-values tested (b = 0, 100, 600, and 800 s/mm² ).

CONCLUSIONS

Referenceless methods provide a robust way to reduce Nyquist ghosts in breast DWI without the need for any additional calibration scan.

Navigator-Free EPI Ghost Correction With Structured Low-Rank Matrix Models: New Theory and Methods

Structured low-rank matrix models have previously been introduced to enable calibrationless MR image reconstruction from sub-Nyquist data, and such ideas have recently been extended to enable navigator-free echo-planar imaging (EPI) ghost correction. This paper presents a novel theoretical analysis which shows that, because of uniform subsampling, the structured low-rank matrix optimization problems for EPI data will always have either undesirable or non-unique solutions in the absence of additional constraints. This theory leads us to recommend and investigate problem formulations for navigator-free EPI that incorporate side information from either image-domain or k-space domain parallel imaging methods. The importance of using nonconvex low-rank matrix regularization is also identified. We demonstrate using phantom and in vivo data that the proposed methods are able to eliminate ghost artifacts for several navigator-free EPI acquisition schemes, obtaining better performance in comparison with the state-of-the-art methods across a range of different scenarios. Results are shown for both single-channel acquisition and highly accelerated multi-channel acquisition.

PEC-GRAPPA reconstruction of simultaneous multislice EPI with slice-dependent 2D Nyquist ghost correction

PURPOSE

To provide simultaneous multislice (SMS) EPI reconstruction with k-space implementation and robust Nyquist ghost correction.

METHODS

2D phase error correction SENSE (PEC-SENSE) was recently developed for Nyquist ghost correction in SMS EPI reconstruction for which virtual coil simultaneous autocalibration and k-space estimation (VC-SAKE) was used to remove slice-dependent Nyquist ghosts and intershot 2D phase variations in multi-shot EPI reference scan. However, masking coil sensitivity maps to exclude background region in PEC-SENSE and manually selecting slice-wise target ranks in VC-SAKE are cumbersome procedures in practice. To avoid masking, the concept of PEC-SENSE is extended to k-space implementation and termed as PEC-GRAPPA. Furthermore, a singular value shrinkage scheme is incorporated in VC-SAKE to circumvent the empirical slice-wise target rank selection. PEC-GRAPPA was evaluated and compared to PEC-SENSE with/without masking and 1D linear phase correction GRAPPA.

RESULTS

PEC-GRAPPA robustly reconstructed SMS EPI images from 7T phantom and human brain data, effectively removing the phase error-induced artifacts. The resulting residual artifact level and temporal SNR were comparable to those by PEC-SENSE with careful tuning. PEC-GRAPPA outperformed PEC-SENSE without masking and 1D linear phase correction GRAPPA.

CONCLUSION

Our proposed PEC-GRAPPA approach effectively removes the artifacts caused by Nyquist ghosts in SMS EPI without cumbersome tuning. This approach provides a robust and practical implementation of SMS EPI reconstruction in k-space with slice-dependent 2D Nyquist ghost correction.

Dual-polarity slice-GRAPPA for concurrent ghost correction and slice separation in simultaneous multi-slice EPI

PURPOSE

A ghost correction strategy for Simultaneous Multi-Slice (SMS) EPI methods that provides improved ghosting artifact reduction compared to conventional methods is presented. Conventional Nyquist ghost correction methods for SMS-EPI rely on navigator data that contain phase errors from all slices in the simultaneously acquired slice-group. These navigator data may contain spatially nonlinear phase differences near regions of B0 inhomogeneity, which violates the linear model employed by most EPI ghost correction algorithms, resulting in poor reconstructions.

METHODS

Dual-Polarity GRAPPA (DPG) was previously shown to accurately model and correct both spatially nonlinear and 2D phase errors in conventional single-slice EPI data. Here, an extension we call Dual-Polarity slice-GRAPPA (DPsG) is adapted to the slice-GRAPPA method and applied to SMS-EPI data for slice separation and ghost correction concurrently-eliminating the need for a separate ghost correction step while also providing improved slice-specific EPI phase error correction.

RESULTS

Images from in vivo SMS-EPI data reconstructed using DPsG in place of conventional Nyquist ghost correction and slice-GRAPPA are presented. DPsG is shown to reduce ghosting artifacts and provide improved temporal SNR compared to the conventional reconstruction.

CONCLUSION

The proposed use of DPsG for SMS-EPI reconstruction can provide images with lower artifact levels, higher image fidelity, and improved time-series stability compared to conventional reconstruction methods.

Ghost reduction in echo-planar imaging by joint reconstruction of images and line-to-line delays and phase errors

PURPOSE

To correct line-to-line delays and phase errors in echo-planar imaging (EPI).

THEORY AND METHODS

EPI-trajectory auto-corrected image reconstruction (EPI-TrACR) is an iterative maximum-likelihood technique that exploits data redundancy provided by multiple receive coils between nearby lines of k-space to determine and correct line-to-line trajectory delays and phase errors that cause ghosting artifacts. EPI-TrACR was efficiently implemented using a segmented FFT and was applied to in vivo brain data acquired at 7 T across acceleration (1×-4×) and multishot factors (1-4 shots), and in a time series.

RESULTS

EPI-TrACR reduced ghosting across all acceleration factors and multishot factors, compared to conventional calibrated reconstructions and the PAGE method. It also achieved consistently lower ghosting in the time series. Averaged over all cases, EPI-TrACR reduced root-mean-square ghosted signal outside the brain by 27% compared to calibrated reconstruction, and by 40% compared to PAGE.

CONCLUSION

EPI-TrACR automatically corrects line-to-line delays and phase errors in multishot, accelerated, and dynamic EPI. While the method benefits from additional calibration data for initialization, it was not a requirement for most reconstructions. Magn Reson Med 79:3114-3121, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

ROBUST AUTOCALIBRATED LORAKS FOR EPI GHOST CORRECTION

Nyquist ghosts are a longstanding problem in a variety of fast MRI experiments that use echo-planar imaging (EPI). Recently, several structured low-rank matrix modeling approaches have been proposed that achieve state-of-the-art ghost-elimination, although the performance of these approaches is still inadequate in several important scenarios. We present a new structured low-rank matrix recovery ghost correction method that we call Robust Autocalibrated LORAKS (RAC-LORAKS). RAC-LORAKS incorporates constraints from autocalibration data to avoid ill-posedness, but allows adaptation of these constraints to gain robustness against possible autocalibration imperfections. RAC-LORAKS is tested in two challenging scenarios: highly-undersampled multi-channel EPI of the brain, and cardiac EPI with a double-oblique slice orientation. Results show that RAC-LORAKS can provide substantial improvements over existing ghost correction methods, and potentially enables new imaging applications that were previously confounded by ghost artifacts.

Model-based iterative reconstruction for single-shot EPI at 7T

PURPOSE

To describe a model-based reconstruction strategy for single-shot echo planar imaging (EPI) that intrinsically accounts for k-space nonuniformity, Nyquist ghosting, and geometric distortions during rather than before or after image reconstruction.

METHODS

Ramp sampling and inhomogeneous B0 field-induced distortion cause the EPI samples to lie on a non-Cartesian grid, thus requiring the nonuniform fast Fourier transform. Additionally, a 2D Nyquist ghost phase correction without the need for extra navigator acquisition is included in the proposed reconstruction. Coil compression is also incorporated to reduce the computational load. The proposed method is applied to phantom and human brain MRI data.

RESULTS

The results demonstrate that Nyquist ghosting and geometric distortions are reduced by the proposed reconstruction. The proposed 2D phase correction is superior to a conventional 1D correction. The reductions of both artifacts lead to improved temporal signal-to-noise ratio (tSNR). The virtual coil results suggest that the processing time can be reduced by up to 75%, with a mean tSNR loss of only 3.2% when using 8-virtual instead of 32-physical coils for twofold undersampled data.

CONCLUSION

The proposed reconstruction improves the quality (ghosting, geometry, and tSNR) of EPI without requiring calibration data for Nyquist ghost correction. Magn Reson Med 78:2250-2264, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Robust EPI Nyquist ghost removal by incorporating phase error correction with sensitivity encoding (PEC-SENSE)

PURPOSE

The existing approach of Nyquist ghost correction by parallel imaging in echo planar imaging (EPI) can suffer from image noise amplification. We propose a method that estimates a phase error map from multi-channel data itself and incorporates it into the sensitivity encoding (SENSE) reconstruction for Nyquist ghost correction without compromising the image SNR.

METHODS

This method first reconstructs two ghost-free images from positive and negative echoes using SENSE, respectively, from which the phase error map is computed. This map is then incorporated into the coil sensitivity maps for the negative echo image during the joint SENSE reconstruction of all k-space data to obtain the final ghost-free image. Phantom and in vivo EPI experiments at 7 T and 3 T were performed to evaluate the proposed method.

RESULTS

Nyquist ghost was effectively removed in all images even under oblique imaging and poor eddy current conditions. Resulting image signal-to-noise ratio (SNR) was comparable to that by the traditional linear phase error correction method and higher than that by a previous SENSE-based parallel imaging correction approach.

CONCLUSION

The proposed correction method can robustly eliminate Nyquist ghost while preserving the image SNR. This approach requires no additional calibration data beyond standard coil sensitivity maps and can be readily applied to all EPI applications. Magn Reson Med 79:943-951, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Noise and non-neuronal contributions to the BOLD signal: applications to and insights from animal studies

The BOLD signal reflects hemodynamic events within the brain, which in turn are driven by metabolic changes and neural activity. However, the link between BOLD changes and neural activity is indirect and can be influenced by a number of non-neuronal processes. Motion and physiological cycles have long been known to affect the BOLD signal and are present in both humans and animal models. Differences in physiological baseline can also contribute to intra- and inter-subject variability. The use of anesthesia, common in animal studies, alters neural activity, vascular tone, and neurovascular coupling. Most intriguing, perhaps, are the contributions from other processes that do not appear to be neural in origin but which may provide information about other aspects of neurophysiology. This review discusses different types of noise and non-neuronal contributors to the BOLD signal, sources of variability for animal studies, and insights to be gained from animal models.

EPI Nyquist ghost and geometric distortion correction by two-frame phase labeling

PURPOSE

To develop a new Nyquist ghost and geometric distortion correction method in echo planar imaging (EPI) using parallel imaging.

METHODS

Two frames of EPI data are acquired with normal and phase-labeled sequence. The phase label is applied by modifying the PE prephase gradient to shift the central echo by one echo spacing. GRAPPA weights are trained from both frames and used to reconstruct images from positive or negative echoes in each frame to remove Nyquist ghost. Geometric distortion is then corrected by the B₀ field map generated from the phase difference between positive and negative echo images. Phantom and in vivo experiments at 7 Tesla (T) and 3T were performed to evaluate the proposed method.

RESULTS

Nyquist ghost was greatly reduced in all images even under oblique imaging and poor eddy current conditions, yielding significant improvements over the existing reference scan and image entropy minimization based methods. Image geometries were fully restored after distortion correction. Phantom results indicated that the signal-to-noise ratio efficiency was largely preserved while fMRI results showed no apparent degradation of temporal resolution.

CONCLUSION

The proposed method provides robust correction of both Nyquist ghost and geometric distortion in EPI, and it is particularly suitable for dynamic EPI applications. Magn Reson Med 77:1749-1761, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Joint correction of Nyquist artifact and minuscule motion-induced aliasing artifact in interleaved diffusion weighted EPI data using a composite two-dimensional phase correction procedure

Diffusion-weighted imaging (DWI) obtained with interleaved echo-planar imaging (EPI) pulse sequence has great potential of characterizing brain tissue properties at high spatial-resolution. However, interleaved EPI based DWI data may be corrupted by various types of aliasing artifacts. First, inconsistencies in k-space data obtained with opposite readout gradient polarities result in Nyquist artifact, which is usually reduced with 1D phase correction in post-processing. When there exist eddy current cross terms (e.g., in oblique-plane EPI), 2D phase correction is needed to effectively reduce Nyquist artifact. Second, minuscule motion induced phase inconsistencies in interleaved DWI scans result in image-domain aliasing artifact, which can be removed with reconstruction procedures that take shot-to-shot phase variations into consideration. In existing interleaved DWI reconstruction procedures, Nyquist artifact and minuscule motion-induced aliasing artifact are typically removed subsequently in two stages. Although the two-stage phase correction generally performs well for non-oblique plane EPI data obtained from well-calibrated system, the residual artifacts may still be pronounced in oblique-plane EPI data or when there exist eddy current cross terms. To address this challenge, here we report a new composite 2D phase correction procedure, which effective removes Nyquist artifact and minuscule motion induced aliasing artifact jointly in a single step. Our experimental results demonstrate that the new 2D phase correction method can much more effectively reduce artifacts in interleaved EPI based DWI data as compared with the existing two-stage artifact correction procedures. The new method robustly enables high-resolution DWI, and should prove highly valuable for clinical uses and research studies of DWI.

Reference-free single-pass EPI Nyquist ghost correction using annihilating filter-based low rank Hankel matrix (ALOHA)

PURPOSE

MR measurements from an echo-planar imaging (EPI) sequence produce Nyquist ghost artifacts that originate from inconsistencies between odd and even echoes. Several reconstruction algorithms have been proposed to reduce such artifacts, but most of these methods require either additional reference scans or multipass EPI acquisition. This article proposes a novel and accurate single-pass EPI ghost artifact correction method that does not require any additional reference data.

THEORY AND METHODS

After converting a ghost correction problem into separate k-space data interpolation problems for even and odd phase encoding, our algorithm exploits an observation that the differential k-space data between the even and odd echoes is a Fourier transform of an underlying sparse image. Accordingly, we can construct a rank-deficient Hankel structured matrix, whose missing data can be recovered using an annihilating filter-based low rank Hankel structured matrix completion approach.

RESULTS

The proposed method was applied to EPI data for both single and multicoil acquisitions. Experimental results using in vivo data confirmed that the proposed method can completely remove ghost artifacts successfully without prescan echoes.

CONCLUSION

Owing to the discovery of the annihilating filter relationship from the intrinsic EPI image property, the proposed method successfully suppresses ghost artifacts without a prescan step. Magn Reson Med 76:1775-1789, 2016. © 2016 International Society for Magnetic Resonance in Medicine.

Dual-polarity GRAPPA for simultaneous reconstruction and ghost correction of echo planar imaging data

PURPOSE

The purpose of this study was to seek improved image quality from accelerated echo planar imaging (EPI) data, particularly at ultrahigh fields. Certain artifacts in EPI reconstructions can be attributed to nonlinear phase differences between data acquired using frequency-encoding gradients of alternating polarity. These errors appear near regions of local susceptibility gradients and typically cannot be corrected with conventional Nyquist ghost correction (NGC) methods.

METHODS

We propose a new reconstruction method that integrates ghost correction into the parallel imaging data recovery process. This is achieved through a pair of generalized autocalibrating partially parallel acquisitions (GRAPPA) kernels that operate directly on the measured EPI data. The proposed dual-polarity GRAPPA (DPG) method estimates missing k-space data while simultaneously correcting inherent EPI phase errors.

RESULTS

Simulation results showed that standard NGC is incapable of correcting higher-order phase errors, whereas the DPG kernel approach successfully removed these errors. The presence of higher-order phase errors near regions of local susceptibility gradients was demonstrated with in vivo data. DPG reconstructions of in vivo 3T and 7T EPI data acquired near these regions showed a marked improvement over conventional methods.

CONCLUSION

This new parallel imaging method for reconstructing accelerated EPI data shows better resilience to inherent EPI phase errors, resulting in higher image quality in regions where higher-order EPI phase errors commonly occur. Magn Reson Med 76:32-44, 2016. © 2015 Wiley Periodicals, Inc.

A correction method for streak artifacts in gradient-echo EPI using spin-echo EPI reference data

OBJECTIVE

To analyze the streak artifacts in a gradient-echo echo planar imaging (GE-EPI) sequence and to propose a correction method for the Nyquist ghost artifacts that does not cause streak artifacts in the GE-EPI imaging.

MATERIALS AND METHODS

Several GE-EPI imaging experiments with various reference scans, using both GE-EPI and SE-EPI scan data, were performed to analyze the streak artifacts and to investigate the spin dephasing phenomena of the GE-EPI reference scan. In addition, the analysis based on the spin dephasing was undertaken in order to demonstrate that the SE-EPI reference data can be used for the correction of the GE-EPI main scan data.

RESULTS

The experimental results confirmed that the improvement of the reference data using either signal averaging or a large flip angle cannot guarantee perfect correction of the streak artifact if the noise is not completely removed. Due to the main field inhomogeneity, the spins of the GE-EPI reference data were dephased in multiple echo signals. The proposed correction method, which uses a SE-EPI reference scan for the GE-EPI images, eliminates the N/2 ghost artifacts without producing streak artifacts.

CONCLUSION

It is believed that the proposed phase error correction scheme can improve the EPI performance in high field MRIs with higher magnetic field inhomogeneities.

Single-shot echo-planar imaging with Nyquist ghost compensation: interleaved dual echo with acceleration (IDEA) echo-planar imaging (EPI)

Echo planar imaging (EPI) is most commonly used for blood oxygen level-dependent fMRI, owing to its sensitivity and acquisition speed. A major problem with EPI is Nyquist (N/2) ghosting, most notably at high field. EPI data are acquired under an oscillating readout gradient and hence vulnerable to gradient imperfections such as eddy current delays and off-resonance effects, as these cause inconsistencies between odd and even k-space lines after time reversal. We propose a straightforward and pragmatic method herein termed "interleaved dual echo with acceleration (IDEA) EPI": two k-spaces (echoes) are acquired under the positive and negative readout lobes, respectively, by performing phase encoding blips only before alternate readout gradients. From these two k-spaces, two almost entirely ghost free images per shot can be constructed, without need for phase correction. The doubled echo train length can be compensated by parallel imaging and/or partial Fourier acquisition. The two k-spaces can either be complex averaged during reconstruction, which results in near-perfect cancellation of residual phase errors, or reconstructed into separate images. We demonstrate the efficacy of IDEA EPI and show phantom and in vivo images at both 3 T and 7 T.

Rapid full-brain fMRI with an accelerated multi shot 3D EPI sequence using both UNFOLD and GRAPPA

The desire to understand complex mental processes using functional MRI drives development of imaging techniques that scan the whole human brain at a high spatial and temporal resolution. In this work, an accelerated multishot three-dimensional echo-planar imaging sequence is proposed to increase the temporal resolution of these studies. A combination of two modern acceleration techniques, UNFOLD and GRAPPA is used in the secondary phase encoding direction to reduce the scan time effectively. The sequence (repetition time of 1.02 s) was compared with standard two-dimensional echo-planar imaging (3 s) and multishot three-dimensional echo-planar imaging (3 s) sequences with both block design and event-related functional MRI paradigms. With the same experimental setup and imaging time, the temporal resolution improvement with our sequence yields similar activation regions in the block design functional MRI paradigm with slightly increased t-scores. Moreover, additional information on the timing of rapid dynamic changes was extracted from accelerated images for the case of the event related complex mental paradigm.

Optimized RF shielding techniques for simultaneous PET/MR

PURPOSE

Integration of positron emission tomography (PET) and magnetic resonance (MR) in a merged device requires shielding of the PET detector electronics. The authors demonstrate that a multiple shell setup exhibits advantages over a single shell shielding enclosure.

METHODS

A spherical shell model is used to derive analytical results. Numerical computations of the electromagnetic fields with a commercial software package (FEKO) and experiments are used to confirm our findings.

RESULTS

Replacing a single shell enclosure by a multilayer approach barely changes its behavior toward low frequency magnetic fields (MR gradient fields), while improving shielding at high frequencies (proton resonant frequency) by orders of magnitude.

CONCLUSIONS

For a given required shielding factor at the proton resonant frequency, the eddy currents induced by the MR gradient fields may be reduced by employing a multiple shell setup.

Improved least squares MR image reconstruction using estimates of k-space data consistency

This study describes a new approach to reconstruct data that has been corrupted by unfavorable magnetization evolution. In this new framework, images are reconstructed in a weighted least squares fashion using all available data and a measure of consistency determined from the data itself. The reconstruction scheme optimally balances uncertainties from noise error with those from data inconsistency, is compatible with methods that model signal corruption, and may be advantageous for more accurate and precise reconstruction with many least squares-based image estimation techniques including parallel imaging and constrained reconstruction/compressed sensing applications. Performance of the several variants of the algorithm tailored for fast spin echo and self-gated respiratory gating applications was evaluated in simulations, phantom experiments, and in vivo scans. The data consistency weighting technique substantially improved image quality and reduced noise as compared to traditional reconstruction approaches.

Two-dimensional phase cycled reconstruction for inherent correction of echo-planar imaging Nyquist artifacts

The inconsistency of k-space trajectories results in Nyquist artifacts in echo-planar imaging (EPI). Traditional techniques often only correct for phase errors along the frequency-encoding direction (one-dimensional correction), which may leave significant residual artifacts, particularly for oblique-plane EPI or in the presence of cross-term eddy currents. As compared with one-dimensional correction, two-dimensional (2D) phase correction can be much more effective in suppressing Nyquist artifacts. However, most existing 2D correction methods require reference scans and may not be generally applicable to different imaging protocols. Furthermore, EPI reconstruction with these 2D phase correction methods is susceptible to error amplification due to subject motion. To address these limitations, we report an inherent and general 2D phase correction technique for EPI Nyquist removal. First, a series of images are generated from the original dataset, by cycling through different possible values of phase errors using a 2D reconstruction framework. Second, the image with the lowest artifact level is identified from images generated in the first step using criteria based on background energy in sorted and sigmoid-weighted signals. In this report, we demonstrate the effectiveness of our new method in removing Nyquist ghosts in single-shot, segmented and parallel EPI without acquiring additional reference scans and the subsequent error amplifications.

3D GRASE PROPELLER: improved image acquisition technique for arterial spin labeling perfusion imaging

Arterial spin labeling is a noninvasive technique that can quantitatively measure cerebral blood flow. While traditionally arterial spin labeling employs 2D echo planar imaging or spiral acquisition trajectories, single-shot 3D gradient echo and spin echo (GRASE) is gaining popularity in arterial spin labeling due to inherent signal-to-noise ratio advantage and spatial coverage. However, a major limitation of 3D GRASE is through-plane blurring caused by T(2) decay. A novel technique combining 3D GRASE and a periodically rotated overlapping parallel lines with enhanced reconstruction trajectory (PROPELLER) is presented to minimize through-plane blurring without sacrificing perfusion sensitivity or increasing total scan time. Full brain perfusion images were acquired at a 3 × 3 × 5 mm(3) nominal voxel size with pulsed arterial spin labeling preparation sequence. Data from five healthy subjects was acquired on a GE 1.5T scanner in less than 4 minutes per subject. While showing good agreement in cerebral blood flow quantification with 3D gradient echo and spin echo, 3D GRASE PROPELLER demonstrated reduced through-plane blurring, improved anatomical details, high repeatability and robustness against motion, making it suitable for routine clinical use.