Distortions In Echo-planar Imaging Research Articles

Accelerated point spread function mapping using signal modeling for accurate echo‐planar imaging geometric distortion correction

Echo-planar imaging is a fast and commonly used magnetic resonance imaging technique with applications in diffusion weighted and functional MRI. Fast data acquisition in echo-planar imaging is accomplished by the extended readout, which also introduces sensitivity to off-resonance effects such as amplitude of static (polarizing) field inhomogeneities and eddy-currents. These off-resonance effects produce geometric distortions in the corresponding echo-planar images. To correct for these distortions, an acceleration of point spread function (PSF) acquisition using a special sampling pattern is presented in this work. The proposed technique allows for reliable and fully automated distortion correction of echo-planar images at a field strength of 3 T. Additionally, a new approach to visualize and determine the distortions in a hybrid (x, y, kPSF) three-dimensional space is proposed. The accuracy and robustness of the proposed technique is demonstrated in phantom and in vivo experiments. The accuracy of the presented method here is compared to previous techniques for echo-planar imaging distortion correction such as PLACE.

Effects of image distortions originating from susceptibility variations and concomitant fields on diffusion MRI tractography results

In this work we investigate the effects of echo planar imaging (EPI) distortions on diffusion tensor imaging (DTI) based fiber tractography results. We propose a simple experimental framework that would enable assessing the effects of EPI distortions on the accuracy and reproducibility of fiber tractography from a pilot study on a few subjects. We compare trajectories computed from two diffusion datasets collected on each subject that are identical except for the orientation of phase encode direction, either right-left (RL) or anterior-posterior (AP). We define metrics to assess potential discrepancies between RL and AP trajectories in association, commissural, and projection pathways. Results from measurements on a 3 Tesla clinical scanner indicated that the effects of EPI distortions on computed fiber trajectories are statistically significant and large in magnitude, potentially leading to erroneous inferences about brain connectivity. The correction of EPI distortion using an image-based registration approach showed a significant improvement in tract consistency and accuracy. Although obtained in the context of a DTI experiment, our findings are generally applicable to all EPI-based diffusion MRI tractography investigations, including high angular resolution (HARDI) methods. On the basis of our findings, we recommend adding an EPI distortion correction step to the diffusion MRI processing pipeline if the output is to be used for fiber tractography.

Reference‐free unwarping of EPI data using dynamic off‐resonance correction with multiecho acquisition (DOCMA)

Inhomogeneities of the main magnetic field cause geometric distortion in echo-planar imaging, a method central to functional MRI. A number of correction methods have been proposed, most of which are based on the acquisition of a fieldmap providing the local offsets to the main magnetic field. Here, accelerated multiecho echo-planar imaging is used, with echo times short enough to enable the construction of a fieldmap of comparable quality from the data themselves. This way, each volume in a time series can be unwarped using a fieldmap obtained from that volume, avoiding volume-to-volume field-motion interactions that invalidate reference data in conventional approaches that use a single, static, fieldmap. The combination of accelerated acquisition with dynamic distortion correction yields volumes with very low distortion at repetition times similar to conventional echo-planar imaging. The method is applied to data acquired at 3 and 7 T and is shown to effectively correct image geometry. Furthermore, it is shown that dynamic distortion correction yields better temporal signal stability than correction using a static fieldmap in the presence of subject motion.

Distortion correction in EPI at ultra‐high‐field MRI using PSF mapping with optimal combination of shift detection dimension

Despite its wide use, echo-planar imaging (EPI) suffers from geometric distortions due to off-resonance effects, i.e., strong magnetic field inhomogeneity and susceptibility. This article reports a novel method for correcting the distortions observed in EPI acquired at ultra-high-field such as 7 T. Point spread function (PSF) mapping methods have been proposed for correcting the distortions in EPI. The PSF shift map can be derived either along the nondistorted or the distorted coordinates. Along the nondistorted coordinates more information about compressed areas is present but it is prone to PSF-ghosting artifacts induced by large k-space shift in PSF encoding direction. In contrast, shift maps along the distorted coordinates contain more information in stretched areas and are more robust against PSF-ghosting. In ultra-high-field MRI, an EPI contains both compressed and stretched regions depending on the B0 field inhomogeneity and local susceptibility. In this study, we present a new geometric distortion correction scheme, which selectively applies the shift map with more information content. We propose a PSF-ghost elimination method to generate an artifact-free pixel shift map along nondistorted coordinates. The proposed method can correct the effects of the local magnetic field inhomogeneity induced by the susceptibility effects along with the PSF-ghost artifact cancellation. We have experimentally demonstrated the advantages of the proposed method in EPI data acquisitions in phantom and human brain using 7-T MRI.

Accelerating EPI Distortion Correction by Utilizing a Modern GPU‐Based Parallel Computation

The combination of phase demodulation and field mapping is a practical method to correct echo planar imaging (EPI) geometric distortion. However, since phase dispersion accumulates in each phase-encoding step, the calculation complexity of phase modulation is Ny-fold higher than conventional image reconstructions. Thus, correcting EPI images via phase demodulation is generally a time-consuming task. Parallel computing by employing general-purpose calculations on graphics processing units (GPU) can accelerate scientific computing if the algorithm is parallelized. This study proposes a method that incorporates the GPU-based technique into phase demodulation calculations to reduce computation time. The proposed parallel algorithm was applied to a PROPELLER-EPI diffusion tensor data set. The GPU-based phase demodulation method reduced the EPI distortion correctly, and accelerated the computation. The total reconstruction time of the 16-slice PROPELLER-EPI diffusion tensor images with matrix size of 128 × 128 was reduced from 1,754 seconds to 101 seconds by utilizing the parallelized 4-GPU program. GPU computing is a promising method to accelerate EPI geometric correction. The resulting reduction in computation time of phase demodulation should accelerate postprocessing for studies performed with EPI, and should effectuate the PROPELLER-EPI technique for clinical practice.

B0 mapping with multi‐channel RF coils at high field

Mapping the static magnetic field via the phase evolution over gradient echo scans acquired at two or more echo times is an established method. A number of possibilities exist, however, for combining phase data from multi-channel coils, denoising and thresholding field maps for high field applications. Three methods for combining phase images when no body/volume coil is available are tested: (i) Hermitian product, (ii) phase-matching over channels, and (iii) a new approach based on calculating separate field maps for each channel. The separate channel method is shown to yield field maps with higher signal-to-noise ratio than the Hermitian product and phase-matching methods and fewer unwrapping errors at low signal-to-noise ratio. Separate channel combination also allows unreliable voxels to be identified via the standard deviation over channels, which is found to be the most effective means of denoising field maps. Tests were performed using multichannel coils with between 8 and 32 channels at 3 T, 4 T, and 7 T. For application in the correction of distortions in echo-planar images, a formulation is proposed for reducing the local gradient of field maps to eliminate signal pile-up or swapping artifacts. Field maps calculated using these techniques, implemented in a freely available MATLAB toolbox, provide the basis for an effective correction for echo-planar imaging distortions at high fields.

Combining prospective motion correction and distortion correction for EPI: towards a comprehensive correction of motion and susceptibility-induced artifacts

State-of-the-art MR techniques that rely on echo planar imaging (EPI), such as real-time fMRI, are limited in their applicability by both subject motion and B(0) field inhomogeneities. The goal of this work is to demonstrate that in principle it is possible to accurately predict the B(0) field inhomogeneities that occur during echo planar imaging in the presence of large scale head motion and apply this knowledge for distortion correction. In this work, prospective motion correction is combined with a field-prediction method and a method for correcting geometric distortions in EPI. To validate the methods, echo planar images were acquired of a custom-made phantom rotated to different angles relative to the B(0) field. For each orientation, field maps were acquired for comparison with the field predictions. The calculated field maps are very similar to the measured field maps for all orientations used in the experiments. The root mean squared error (RMSE) of the difference maps was between 15 to 20 Hz. The quality of distortion correction using calculated field maps is comparable to distortion correction done with measured field maps. The results suggest that distortion-free echo planar imaging of moving objects may be feasible if prospective motion correction is combined with a field inhomogeneity estimation approach.

Correction of Shearing Distortions in Echo-Planar Imaging

In this study, the existence of linear geometric distortions due to readout (RO) train-induced background gradients was investigated under B0 homogeneity; this paper was aimed at deriving and implementing a simple method for correcting such linear geometric distortions without carrying out the reference measurements of field errors within the echo-planar imaging (EPI) acquisition window. The background gradient in the EPI acquisition window in the RO direction was estimated from the autocorrelation phase, which was calculated from the complex-valued RO 1-D inverse-Fourier-transformed k-space (x-ky space). All the correction procedures were performed in the complex domain in the hybrid x-ky space after acquiring the data. No prior adjustments or additional measurements are required, and this correction algorithm can be applied to most EPI techniques. The echo-planar images of several phantoms and a human brain were acquired with one 1.5-T and two 3-T MRI systems to validate the effectiveness of the correction method. The severe global spatial shearing distortion caused by the linear background RO gradient in the images was corrected, and improvements were observed in all cases. The results indicate that distortions caused by the background RO gradient under B0 homogeneity can be corrected by online processing, even in high-resolution echo-planar images such as 128 × 128 pixel imaging.

Reducing distortions in diffusion‐weighted echo planar imaging with a dual‐echo blip‐reversed sequence

The inherent distortions in echo-planar imaging that arise due to inhomogeneities in the static magnetic field can lead to difficulties when attempting to obtain structurally accurate diffusion-tensor imaging data. Parallel acceleration techniques can reduce the magnitude of these distortions but do not remove them entirely. Images can be corrected using a measured field map, but this is prone to error. One approach to correcting for these distortions, referred to here as "blip-reversed" echo-planar imaging, involves collecting a second set of images with the phase encoding reversed. Here, a novel approach to collecting blip-reversed echo-planar imaging data for diffusion-tensor imaging is presented: a dual-echo sequence is used in which the phase-encoding direction of the second echo is swapped compared to the first echo. This allows benefits of the blip-reversed approach to be exploited, with only a modest increase in scan time and, due to the extra data acquired, no significant loss of signal-to-noise efficiency. A novel approach to recombining blip-reversed data is also presented, which involves refining the measured field map, using an algorithm to minimize the difference between the corrected images. The field map refinement is also applicable to conventionally acquired blip-reversed sequences.

Improved B0 field map estimation for high field EPI

Echo planar imaging (EPI) is an ultrafast magnetic resonance imaging (MRI) technique that allows one to acquire a 2D image in about 100 ms. Unfortunately, the standard EPI images suffer from substantial geometric distortions, mainly originating from susceptibility differences in adjacent tissues. To reduce EPI distortions, correction methods based on a field map, which is a map of the off-resonance frequencies, have been developed. In this work, a nonlinear least squares estimator is used to optimize the estimation of the field map of the B(0) field. The model of the EPI and reference data includes parameters for the phase evolution, the complex magnitude, the relaxation of the MRI signal and the EPI-specific phase difference between odd and even echoes, and from these parameters, additional corrections might be computed. The reference data required to estimate the field map can be acquired with a modified EPI-sequence. The proposed method is tested on simulated as well as experimental data and proves to be significantly more robust against noise, compared to the previously suggested method.

Double-spin-echo diffusion weighting with a modified eddy current adjustment

Magnetic field inhomogeneities like eddy current-related gradient fields cause geometric distortions in echo-planar imaging (EPI). This in particular affects diffusion-weighted imaging where these distortions vary with the direction of the diffusion weighting and hamper the accurate determination of diffusion parameters. The double-spin-echo preparation often used aims to reduce the cumulative eddy current effect by adjusting the diffusion-weighting gradient pulse durations to the time constant of the dominant eddy current contribution. However, eddy currents with a variety of time constants may be present and cause residual distortions. Here, a modification is proposed where the two bipolar gradient pairs of the preparation are adjusted independently to different time constants. At the expense of a slightly prolonged echo time, residual geometric distortions and correspondingly increased values of the diffusion anisotropy can be reduced as is demonstrated in phantoms and the human brain. Thus, it may help to improve the reliability of diffusion-weighted EPI.

Efficient correction of inhomogeneous static magnetic field-induced distortion in Echo Planar Imaging

Single-shot Echo Planar Imaging (EPI) is one of the most efficient magnetic resonance imaging (MRI) acquisition schemes, producing relatively high-definition images in 100 ms or less. These qualities make it desirable for Diffusion Tensor Imaging (DTI), functional MRI (fMRI), and Dynamic Susceptibility Contrast MRI (DSC-MRI). However, EPI suffers from severe spatial and intensity distortion due to B0 field inhomogeneity induced by magnetic susceptibility variations. Anatomically accurate, undistorted images are essential for relating DTI and fMRI images with anatomical MRI scans, and for spatial registration with other modalities. We present here a fast, robust, and accurate procedure for correcting EPI images from such spatial and intensity distortions. The method involves acquisition of scans with opposite phase encoding polarities, resulting in opposite spatial distortion patterns, and alignment of the resulting images using a fast nonlinear registration procedure. We show that this method, requiring minimal additional scan time, provides superior accuracy relative to the more commonly used, and more time consuming, field mapping approach. This method is also highly computationally efficient, allowing for direct “real-time” implementation on the MRI scanner. We further demonstrate that the proposed method can be used to recover dropouts in gradient echo (BOLD and DSC-MRI) EPI images.

Improved shimming for fMRI specifically optimizing the local BOLD sensitivity

In functional MRI, magnetic field inhomogeneities due to air-tissue susceptibility differences may lead to severe signal dropouts and geometric distortions in echo-planar images. Therefore, the inhomogeneities in the field are routinely minimized by shimming prior to imaging. However in fMRI, the Blood Oxygen Level Dependent (BOLD) effect is the measure of interest, so the BOLD sensitivity (BS) should be optimized rather than the magnetic field homogeneity. The analytical expression for an estimate of the BOLD sensitivity has been recently developed, allowing for the computation of BOLD sensitivity maps from echo-planar images and field maps. This report describes a novel shimming procedure that optimizes the local BOLD sensitivity over a region of interest. The method is applied in vivo and compared to a standard global shimming procedure. A breath-holding experiment was carried out and demonstrated that the BS-based shimming significantly improved the detection of activation in a target region of interest, the medial orbitofrontal cortex.

Correction for Susceptibility-Induced Distortion in Echo-Planar Imaging Using Field Maps and Model-Based Point Spread Function

Susceptibility-induced distortion is one of the major artifacts in echo-planar imaging (EPI), and many solutions have been proposed for the problem, including the Fourier method and the point spread function (PSF) method. In this paper, a framework unifying both methods is presented. Under this framework, a model-based PSF method is proposed in which the PSF of the source object is modeled along with a single field map measured by TE-offset reference scans. EPI images of a phantom and a healthy human subject were acquired, and the results of distortion correction by the Fourier method, linear interpolation method, and the model-based PSF method were compared. The results showed that the model-based PSF method could correct for geometric distortion and signal intensity distortion satisfactorily, avoiding the rippling artifact shown in the Fourier method. In conclusion, the proposed framework gave us an overall picture of how different correction methods work. The model-based PSF method, which required fewer reference scans and less computational load, was more clinically feasible than other methods.

High‐resolution diffusion tensor imaging with inner field‐of‐view EPI

To demonstrate the applicability of inner field-of-view (FOV) echo-planar imaging based on spatially two-dimensional selective radiofrequency excitations to high-resolution diffusion tensor imaging. Diffusion tensor imaging of inner FOVs with in-plane resolutions of 0.90 x 0.90 mm(2) and 0.50 x 0.50 mm(2) was performed in the human brain and cervical spinal cord on a 3 T whole-body MR system. Using inner FOVs reduces geometric distortions in echo-planar imaging and allows for an improved in-plane resolution. Some of the crossings of transverse pontine fibers with the pyramidal tracts in the brainstem could be resolved, increased diffusion anisotropy and fiber orientation could be identified in cerebellar white matter, and the reduced diffusion anisotropy of spinal cord gray matter could be detected. Inner FOV echo-planar imaging may help to improve the spatial resolution and thus the accuracy of diffusion anisotropy and white matter fiber orientation measurements in the human central nervous system.

Geometric distortion correction for echo planar images using nonrigid registration with spatially varying scale

One method used to correct geometric and intensity distortions in echo planar images is to register them to undistorted images via nonrigid deformations. However, some areas in the echo planar images are more distorted than others, thus suggesting the use of deformations whose characteristics are adapted spatially. In this article, we incorporate into our previously developed registration algorithm a spatially varying scale mechanism, which adapts the local scale properties of the transformation by means of a scale map. To compute the scale map, a technique is proposed that relies on an estimate of the expected deformation field. This estimate is generated using knowledge of the physical processes that induce distortions in echo planar images. We evaluate the method of spatially varying scale on both simulated and real data. We find that, in comparison with our earlier method using fixed scale, our new method finds deformation fields that are smoother and finds them faster without sacrificing accuracy.

Ｓｉｎｇｌｅ−ｓｈｏｔ ＥＰＩにおけるＳＥＮＳＥ折り返し展開ＥＲＲＯＲについて（３．０Ｔ装置での検討）

Magnetic field inhomogeneity causes artifacts in MRI. For example, in single-shot echo-planar imaging (EPI), they often appear as severe geometric distortions along the phase-encoding direction. Sensitivity encoding (SENSE) is useful in reducing the distortion in EPI since it only acquires partial k-space data using multiple receiver channels. In SENSE, a reference scan usually needs to be performed to create a sensitivity profile of each receiver channel. Gradient echo (GRE) sequences are often used in the reference scan. In diffusion-weighted imaging (DWI) using single-shot EPI with SENSE, non-negligible aliasing artifacts often remain in the reconstructed images. We suppose that these artifacts result from misregistration between the reference images acquired using GRE sequences and the DWI acquired using EPI. In this study, we used two types of acquisition methods to create sensitivity profiles, GRE sequences and EPI, and have compared the residual artifacts in the reconstructed images. The sensitivity profiles were created from the data acquired using the GRE and EPI sequences. Artifacts were reduced when EPI sensitivity profiles were used. This resulted from the fact that off-resonance effects, e.g., magnetic field inhomogeneity, susceptibility, and chemical shift, often cause severe image distortion in EPI, and, therefore, there is misregistration between images reconstructed from the data acquired using GRE and EPI sequences. Our study suggests that EPI sensitivity profiles be used when imaging data are acquired using a single-shot EPI with SENSE, although GRE sensitivity profiles have often been used in practice.

EPI distortion correction from a simultaneously acquired distortion map using TRAIL

To develop a method for shot-by-shot distortion correction of single-shot echo-planar imaging (EPI) that is capable of correcting each image individually using a distortion measurement performed during acquisition of the image itself. The recently-introduced method known as two reduced acquisitions interleaved (TRAIL) was extended to measure the distribution of the main magnetic field B0 with each shot. This corresponded to a map of distortion, and allowed distortion to be corrected in the acquired images. Distortion-corrected images were demonstrated in the human brain. The distortion field could be directly visualized using the "stripe" distribution imposed by the TRAIL pulse sequence. This confirmed the success of the correction. Over a time-course measurement of 10 images, variance was reduced by using shot-by-shot distortion correction compared to correction with a constant field map. Shot-by-shot distortion correction may be performed for EPI images acquired using an extension of the TRAIL technique, ensuring that the correction reflects the actual distortion pattern and not merely a previously measured, but possibly no longer valid, distortion field. This avoids errors due to changes in the distortion field or misregistration of a previously measured distortion map resulting from subject motion.

Application of k-space energy spectrum analysis to susceptibility field mapping and distortion correction in gradient-echo EPI

Echo-planar imaging (EPI) is widely used in functional MRI studies. It is well known that EPI quality is usually degraded by geometric distortions, when there exist susceptibility field inhomogeneities. EPI distortions may be corrected if the field maps are available. It is possible to estimate the susceptibility field gradients from the phase reconstruction of a single-TE EPI image, after a successful phase-unwrapping procedure. However, in regions affected by pronounced field gradients, the phase-unwrapping of a single-TE image may fail, and therefore the estimated field maps may be incorrect. It has been reported that the field inhomogeneity may be calculated more reliably from T2*-weighted images corresponding to multiple TEs. However, the multi-TE MRI field mapping increases the scan time. Furthermore, the measured field maps may be invalid if the subject's position changes during dynamic scans. To overcome the limitations in conventional field mapping approaches, a novel k-space energy spectrum analysis algorithm is developed, which quantifies the spatially dependent echo-shifting effect and the susceptibility field gradients directly from the k-space data of single-TE gradient-echo EPI. Using the k-space energy spectrum analysis, susceptibility field gradients can be reliably measured without phase-unwrapping, and EPI distortions can be corrected without extra field mapping scans or pulse sequence modification. The reported technique can be used to retrospectively improve the image quality of the previously acquired EPI and functional MRI data, provided that the complex-domain k-space data are still available.

Strategies for block-design fMRI experiments during task-related motion of structures of the oral cavity

Functional MRI (fMRI) studies of jaw motion, speech, and swallowing disorders have been hampered by motion artifacts. Tissue motion perturbs the static magnetic field, creating geometric distortions in echo-planar images that lead to many false positives in activation maps. These problems have restricted blood oxygenation level-dependent (BOLD) fMRI studies involving orofacial muscles to event-related designs, which offer weak contrast-to-noise ratios when compared to block designs. Two new approaches are described that greatly reduce false positives in the activation maps created by the distortions in block-design fMRI studies involving jaw and tongue motion during chewing. First, an appropriate task duration of 10−14 s was found to maximize functional contrast while minimizing motion artifacts. Second, three motion-sensitive postprocessing methods were applied successively to examine the temporal and spatial characteristics of responses and identify and remove false positives caused by motion artifacts. These techniques are shown to allow the use of block design in an fMRI study of a jaw motion task. Extension to speech and swallowing tasks is discussed.