Correction of periodic motion artifacts along the slice selection axis in MRI

Motion guidance lines for robust data consistency-based retrospective motion correction in 2D and 3D MRI

PURPOSE

To develop a robust retrospective motion-correction technique based on repeating k-space guidance lines for improving motion correction in Cartesian 2D and 3D brain MRI.

METHODS

The motion guidance lines are inserted into the standard sequence orderings for 2D turbo spin echo and 3D MPRAGE to inform a data consistency-based motion estimation and reconstruction, which can be guided by a low-resolution scout. The extremely limited number of required guidance lines are repeated during each echo train and discarded in the final image reconstruction. Thus, integration within a standard k-space acquisition ordering ensures the expected image quality/contrast and motion sensitivity of that sequence.

RESULTS

Through simulation and in vivo 2D multislice and 3D motion experiments, we demonstrate that respectively 2 or 4 optimized motion guidance lines per shot enables accurate motion estimation and correction. Clinically acceptable reconstruction times are achieved through fully separable on-the-fly motion optimizations (˜1 s/shot) using standard scanner GPU hardware.

CONCLUSION

The addition of guidance lines to scout accelerated motion estimation facilitates robust retrospective motion correction that can be effectively introduced without perturbing standard clinical protocols and workflows.

Scout accelerated motion estimation and reduction (SAMER)

PURPOSE

To demonstrate a navigator/tracking-free retrospective motion estimation technique that facilitates clinically acceptable reconstruction time.

METHODS

Scout accelerated motion estimation and reduction (SAMER) uses a single 3-5 s, low-resolution scout scan and a novel sequence reordering to independently determine motion states by minimizing the data-consistency error in a SENSE plus motion forward model. This eliminates time-consuming alternating optimization as no updates to the imaging volume are required during the motion estimation. The SAMER approach was assessed quantitatively through extensive simulation and was evaluated in vivo across multiple motion scenarios and clinical imaging contrasts. Finally, SAMER was synergistically combined with advanced encoding (Wave-CAIPI) to facilitate rapid motion-free imaging.

RESULTS

The highly accelerated scout provided sufficient information to achieve accurate motion trajectory estimation (accuracy ~0.2 mm or degrees). The novel sequence reordering improved the stability of the motion parameter estimation and image reconstruction while preserving the clinical imaging contrast. Clinically acceptable computation times for the motion estimation (~4 s/shot) are demonstrated through a fully separable (non-alternating) motion search across the shots. Substantial artifact reduction was demonstrated in vivo as well as corresponding improvement in the quantitative error metric. Finally, the extension of SAMER to Wave-encoding enabled rapid high-quality imaging at up to R = 9-fold acceleration.

CONCLUSION

SAMER significantly improved the computational scalability for retrospective motion estimation and correction.

TArgeted Motion Estimation and Reduction (TAMER): Data Consistency Based Motion Mitigation for MRI Using a Reduced Model Joint Optimization

We introduce a data consistency based retrospective motion correction method, TArgeted Motion Estimation and Reduction (TAMER), to correct for patient motion in Magnetic Resonance Imaging (MRI). Specifically, a motion free image and motion trajectory are jointly estimated by minimizing the data consistency error of a SENSE forward model including rigid-body subject motion. In order to efficiently solve this large non-linear optimization problem, we employ reduced modeling in the parallel imaging formulation by assessing only a subset of target voxels at each step of the motion search. With this strategy we are able to effectively capture the tight coupling between the image voxel values and motion parameters. We demonstrate in simulations TAMER's ability to find similar search directions compared to a full model, with an average error of 22%, vs. 73% error when using previously proposed alternating methods. The reduced model decreased the computation time fold compared to a full image volume evaluation. In phantom experiments, our method successfully mitigates both translation and rotation artifacts, reducing image RMSE compared to a motion-free gold standard from 21% to 14% in a translating phantom, and from 17% to 10% in a rotating phantom. Qualitative image improvements are seen in human imaging of moving subjects compared to conventional reconstruction. Finally, we compare in vivo image results of our method to the state-of-the-art.

Intrinsic detection of motion in segmented sequences

While many motion correction techniques for MRI have been proposed, their use is often limited by increased patient preparation, decreased patient comfort, additional scan time, or the use of specialized sequences not available on many commercial scanners. For this reason, we propose a simple self-navigating technique designed to detect motion in segmented sequences. We demonstrate that comparing two segments containing adjacent sets of k-space lines results in an aliased error function. A global shift of the aliased error function indicates the presence of in-plane rigid-body translation, while other types of motion are evident in the dispersion or breadth of the error function. Since segmented sequences commonly acquire data in sets of adjacent k-space lines, this method provides these sequences with an inherent method of detecting object motion. Motion corrupted data can then be reacquired proactively or in some cases corrected or removed retrospectively.

Single spin-echo proton transverse relaxometry of iron-loaded liver

A single-spin-echo methodology is described for the measurement and imaging of proton transverse relaxation rates (R2) in iron-loaded and normal human liver tissue in vivo. The methodology brings together previously reported techniques dealing with (i) the changes in gain between each spin-echo acquisition, (ii) signal level offset due to background noise, (iii) estimation of signal intensities in decay curves at time zero to enable reliable extraction of relaxation times from tissues with very short T2 values, (iv) bi-exponential modelling of decay curves with a small number of data points, and (v) reduction of respiratory motion artefacts. The accuracy of the technique is tested on aqueous manganese chloride solutions yielding a relaxivity of 74.1+/-0.3 s-1 (mM)-1, consistent with previous reports. The precision of the in vivo measurement of mean liver R2 values is tested through duplicate measurements on 10 human subjects with mean liver R2 values ranging from 26 to 220 s-1. The random uncertainty on the measurement of mean liver R2 was found to be 7.7%.

Reduction of respiratory motion artifacts in transverse relaxation rate (R2) images of the liver

An empirical motion artifact suppression technique has been developed to reduce the respiratory motion artifacts in axial single spin-echo magnetic resonance (MR) images of the liver post-acquisition. The correction scheme is based on the observation that the dominant motion artifacts within abdominal MR images are ghosts that follow the profile and signal intensity of high signal intensity boundaries, such as those for the subcutaneous fat along the anterior abdominal wall. The technique is applied to the reduction of respiratory motion artifacts in a spin echo image series of the liver of an iron-loaded patient and of a manganese chloride phantom subject to respiratory motion. Subsequent improvements to transverse relaxation rate (R2) image analysis are then demonstrated on the motion-corrected spin echo images, illustrating the utility of the technique for application in the R2 image-based measurement and mapping of liver iron concentration.

Using an MRI distortion transfer function to characterize the ghosts in motion-corrupted images

Motion artefact suppression remains an active topic in MRI. In this paper, we suggest that certain nonrigid, or spatially variant, characteristics of motion of an object can be represented by extending the work of Mitsa et al. This empirical extension uses a ghost distortion transfer function (GTDF) applied to the k-space (frequency domain) data. We demonstrate the variety of ghost characteristics that can be generated from various two-dimensional (2-D) GTDF's. The distortion transfer function for periodic motion along the Z-axis can be determined from the nonoverlapped portions of the ghost and central image. It required a GDTF with the shape of a belt bandpass filter to produce an image corresponding to the ghosts of a volunteer's abdomen image corrupted by unknown respiratory motion artefacts. The preliminary results of a composite method of motion artefact suppression are presented. The artefact suppression was successful for ghost images described by a GDTF have a low-pass nature, but less successful with ghosts have a GDTF of a bandpass nature.

Cancellation of motion artifact in MRI due to 2D rigid translational motion

A new algorithm for cancelling MRI artifact due to translational motion in the image plane is described. Unlike the conventional iterative phase retrieval algorithm, in which there is no guarantee for the convergence, a direct method for estimating the motion is proposed. In the previous approach, the motions in the readout(x-) direction and the phase encoding(y-) direction are estimated simultaneously. However, the feature of the each x- and y-directional motion is different. Based on the analysis of their features, each x- and y-directional motion is cancelled by different algorithms in two steps. First, we notice that the x-directional motion corresponds to a shift of the x-directional spectrum of the MRI signal, so the x-directional motion can be cancelled by shifting the spectrum in inverse direction. Next, the y-directional motion is cancelled using a new constraint, with which the motion component and the true image component can be separated. The algorithm is shown to be effective by simulations.

MRI artifact cancellation due to rigid motion in the imaging plane

A post-processing technique has been developed to suppress the magnetic resonance imaging (MRI) artifact arising from object planar rigid motion. In two-dimensional Fourier transform (2-DFT) MRI, rotational and translational motions of the target during magnetic resonance magnetic resonance (MR) scan respectively impose nonuniform sampling and a phase error an the collected MRI signal. The artifact correction method introduced considers the following three conditions: (1) for planar rigid motion with known parameters, a reconstruction algorithm based on bilinear interpolation and the super-position method is employed to remove the MRI artifact, (2) for planar rigid motion with known rotation angle and unknown translational motion (including an unknown rotation center), first, a super-position bilinear interpolation algorithm is used to eliminate artifact due to rotation about the center of the imaging plane, following which a phase correction algorithm is applied to reduce the remaining phase error of the MRI signal, and (3) to estimate unknown parameters of a rigid motion, a minimum energy method is proposed which utilizes the fact that planar rigid motion increases the measured energy of an ideal MR image outside the boundary of the imaging object; by using this property all unknown parameters of a typical rigid motion are accurately estimated in the presence of noise. To confirm the feasibility of employing the proposed method in a clinical setting, the technique was used to reduce unknown rigid motion artifact arising from the head movements of two volunteers.

An improved method for MRI artifact correction due to translational motion in the imaging plane

A computer postprocessing technique is developed to remove MRI artifact arising from unknown translational motion in the imaging plane. Based on previous artifact correction methods, the improved technique uses two successive steps to reduce read out and phase-encoding direction artifacts: First, the spectrum shift method is applied to remove read-out axis translational motion. Then, the phase retrieval method is employed to eliminate the remaining subpixel motion of the read-out axis and the entire motion of the phase-encoding axis. In the presence of noise, to protect edge detection (in the spectrum shift method), two high-density gray-level markers are added, one to each side of the imaging object. Experimental results with an actual MR scan confirmed the ability of the method to correct the artifact of an MR image caused by unknown translational motion in the imaging plane.

Out-of-plane motion compensation in multislice spin-echo MRI

In magnetic resonance imaging (MRI), it is well-known that patient motion plays a significant role in the degradation of image quality. Although the case of translational in-plane motion (x-y-motion) has been studied by several researchers, the effect of rigid, translational out-of-plane motion (z-motion) has not yet been completely analyzed due to its more complex nature. Out-of-plane motion introduces blurring along the slice-selection direction in addition to motion artifacts. Here, the authors present a model to represent the effect of out-of-plane motion on multislice MR data. The inversion of this model not only results in the correction of the artifacts due to out-of-plane motion, but also reduces blurring in the slice-selection direction, yielding higher resolution images. Because of the shift-varying nature of the authors' model, they propose to use a nonlinear postprocessing method, projection onto convex sets (POCS), for its inversion, provided that the motion kernel and the slice-selection profile are known. The proposed method has been tested on simulated data and then applied to actual MR data to demonstrate the feasibility of the technique in real imaging situations.

Correction of translational motion artifacts in multi-slice spin-echo imaging using self-calibration

In this paper, we describe a method for detecting and correcting in-plane bulk translational motion in multislice spin-echo imaging using self-calibration and postprocessing. A constant phase encoding offset between slices is used to evenly spread out the low spatial frequency echoes to allow accurate motion detection by self-calibration. Motion detection in both x and y directions is achieved by interchanging the readout and phase encoding directions for the alternate slices. Displacements are determined by cross correlating the modulus of each 1D transformed echo with a reference box car function whose width equals that of the imaged object. In addition, phase errors induced by the velocity in the readout direction are estimated and corrected using the displacement data. The results obtained from knee studies at 0.5 T and 1.5 T show that the artifacts due to translational motions are significantly suppressed upon correction. The method does not require any additional pulses or time, and the data processing can be easily implemented.

Motion artifact suppression: a review of post-processing techniques

Patient motion during data acquisition in magnetic resonance imaging causes artifacts in the reconstructed image, which for two-dimensional Fourier transform imaging techniques appear as blurring and ghost repetitions of the moving structures. While the problem with intra-view effects has been effectively addressed using gradient moment nulling techniques, there is no corresponding technique for inter-view effects with equal effectiveness and general applicability. A number of techniques have been proposed for correcting the inter-view effects, and these may be divided into those that minimise the corruption of the data, and those that post-process the data to restore the image. The techniques in the former category are briefly reviewed, then those in the latter category are examined in detail. These are analysed in terms of motion model, model parameter estimation, and data correction.

Suppression of slice selection axis motion artifacts in MRI

Patient motion during data acquisition in magnetic resonance imaging causes artifacts in the reconstructed image, which for two-dimensional Fourier transform imaging techniques appear as blurring and ghost repetitions of the moving structures. T. Mitsa et al. (1990) proposed a technique for suppressing artifacts from periodic motion along the slice selection axis. A different approach to the same problem is presented which is not restricted to periodic motion. The algorithm is verified using a simulated phantom and motion. It is also shown to perform well in the presence of noise and motion within the imaging plane.

An improved algorithm for 2-D translational motion artifact correction

The quality of magnetic resonance imaging systems has improved to the point that motion is a major limitation in many examinations. Translational motion in the imaging plane causes the phase of the data to be corrupted. An algorithm using computer post-processing is proposed to correct the phase of the data, and hence remove the artifact. This algorithm has superior convergence properties to an earlier algorithm, which is achieved by incorporating additional prior information specific to the situation. The algorithm is verified using a Shepp and Logan phantom with simulated motion in the imaging plane. It is shown that the algorithm can correct both periodic and random motion, and that the algorithm is not significantly degraded when noise is present.