MRI artifact cancellation due to rigid motion in the imaging plane

CINE turbo spin echo imaging

High-resolution turbo spin echo (TSE) images have demonstrated important details of carotid artery morphology; however, it is evident that pulsatile blood and wall motion related to the cardiac cycle are still significant sources of image degradation. Although ECG gating can reduce artifacts due to cardiac-induced pulsations, gating is rarely used because it lengthens the acquisition time and can cause image degradation due to nonconstant repetition time. This work introduces a relatively simple method of converting a conventional TSE acquisition into a retrospectively ECG-correlated cineTSE sequence. The cineTSE sequence generates a full sequence of ECG-correlated images at each slice location throughout the cardiac cycle in the same scan time that is conventionally used by standard TSE sequences to produce a single image at each slice location. The cineTSE images exhibit reduced pulsatile artifacts associated with a gated sequence but without the increased scan time or associated nonconstant repetition time effects.

Rigid body motion compensation for spiral projection imaging

Spiral projection imaging (SPI) is a 3D, spiral based magnetic resonance imaging (MRI) acquisition scheme that allows for self-navigated motion estimation of all six degrees-of-freedom. The trajectory, a set of spiral planes, is enhanced to accommodate motion tracking by adding orthogonal planes. Rigid-body motion tracking is accomplished by comparing the overlapping data and deducing the motion that is consistent with the comparisons. The accuracy of the proposed method is quantified for simulated data and for data collected using both a phantom and a volunteer. These tests were repeated to measure the effect of off-resonance blurring, coil sensitivity, gradient warping, undersampling, and nonrigid motion (e.g., neck). The artifacts of off-resonance, coils sensitivity, and gradient warping impose an unnotable effect on the accuracy of motion estimation. The worst mean accuracy is 0.15° and 0.20 mm for the phantom while the worst mean accuracy is 0.48° and 0.34 mm when imaging a brain, indicating that the nonrigid component in human subjects slightly degrades accuracy. When applied to in vivo motion, the proposed technique considerably reduces motion artifact.

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.

Retrospective intra-scan motion correction

This paper analyzes the effects of intra-scan motion and demonstrates the possibility of correcting them directly in k-space with a new automatic retrospective method. The method is presented for series of 2D acquisitions with Cartesian sampling. Using a reference k-space acquisition (corrected for translations) within the series, intra-scan motion parameters are accurately estimated for each trajectory in k-space of each data set in the series resulting in pseudo-random sample positions. The images are reconstructed with a Bayesian estimator that can handle sparse arbitrary sampling in k-space and reduces intra-scan rotation artefacts to the noise level. The method has been assessed by means of a Monte Carlo study on axial brain images for different signal-to-noise ratios. The accuracy of motion estimates is better than 0.1 degrees for rotation, and 0.1 and 0.05 pixel, respectively, for translation along the read and phase directions for signal-to-noise ratios higher than 6 of the signals on each trajectory. An example of reconstruction from experimental data corrupted by head motion is also given.

Motion correction using the k-space phase difference of orthogonal acquisitions

Rigid body translations of an object in MRI create image artifacts along the phase-encode (PE) direction in standard 2DFT imaging. If two images are acquired with swapped PE direction, it is possible to determine and correct for arbitrary in-plane translational interview motions in both images directly from phase differences in the k-space acquisitions by solving a large system of linear equations. For example, if one assumes two N x N 2D acquisitions with in-plane translational interview motion, 4N unknown motions may corrupt the two images, but the phase difference at each point in k-space yields a system of N(2) equations in these 4N unknowns. If the acquisitions have orthogonal PE directions, this highly overdetermined system of equations can be solved to provide the motion records, which in turn can be used to correct the motion artifacts in each image. The theory of this orthogonal k-space phase difference (ORKPHAD) technique is described, and results are presented for synthetic and in vivo motion-corrupted data sets. In all cases, the data showed clear improvement of translation-induced artifacts. These methods do not require special pulse sequences and are theoretically generalizable to partial Fourier imaging and 3D acquisitions.

Motion artifact reduction technique for dual-contrast FSE imaging

There is considerable similarity between proton density-weighted (PDw) and T2-weighted (T2w) images acquired by dual-contrast fast spin-echo (FSE) sequences. The similarity manifests itself in image space as consistency between the phases of PDw and T2w images and in k-space as correspondence between PDw and T2w k-space data. A method for motion artifact reduction for dual-contrast FSE imaging has been developed. The method uses projection onto convex sets (POCS) formalism and is based on image space phase consistency and the k-space similarity between PDw and T2w images. When coupled with a modified dual-contrast FSE phase encoding scheme the method can yield considerable artifact reduction, as long as less than half of the acquired data is corrupted by motion. The feasibility and efficiency of the developed method were demonstrated using phantom and human MRI data.

Autocorrection in MR imaging: adaptive motion correction without navigator echoes

A technique for automatic retrospective correction of motion artifacts on magnetic resonance (MR) images was developed that uses only the raw (complex) data from the MR imager and requires no knowledge of patient motion during the acquisition. The algorithm was tested on coronal images of the rotator cuff in a series of 144 patients, and the improvements in image quality were similar to those achieved with navigator echoes. The results demonstrate that autocorrection can significantly reduce motion artifacts in a technically demanding MR imaging application.

Image metric-based correction (autocorrection) of motion effects: analysis of image metrics

Magnetic resonance (MR) imaging of the shoulder necessitates high spatial and contrast resolution resulting in long acquisition times, predisposing these images to degradation due to motion. Autocorrection is a new motion correction algorithm that attempts to deduce motion during imaging by calculating a metric that reflects image quality and searching for motion values that optimize this metric. The purpose of this work is to report on the evaluation of 24 metrics for use in autocorrection of MR images of the rotator cuff. Raw data from 164 clinical coronal rotator cuff exams acquired with interleaved navigator echoes were used. Four observers then scored the original and corrected images based on the presence of any motion-induced artifacts. Changes in metric values before and after navigator-based adaptive motion correction were correlated with changes in observer score using a least-squares linear regression model. Based on this analysis, the metric that exhibited the strongest relationship with observer ratings of MR shoulder images was the entropy of the one-dimensional gradient along the phase-encoding direction. We speculate (and show preliminary evidence) that this metric will be useful not only for autocorrection of shoulder MR images but also for autocorrection of other MR exams.

Automatic compensation of motion artifacts in MRI

Patient motion during the acquisition of a magnetic resonance image can cause blurring and ghosting artifacts in the image. This paper presents a new post-processing strategy that can reduce artifacts due to in-plane, rigid-body motion in times comparable to that required to re-scan a patient. The algorithm iteratively determines unknown patient motion such that corrections for this motion provide the best image quality, as measured by an entropy-related focus criterion. The new optimization strategy features a multi-resolution approach in the phase-encode direction, separate successive one-dimensional searches for rotations and translations, and a novel method requiring only one re-gridding calculation for each rotation angle considered. Applicability to general rigid-body in-plane rotational and translational motion and to a range of differently weighted images and k-space trajectories is demonstrated. Motion artifact reduction is observed for data from a phantom, volunteers, and patients.

An improved algorithm for rotational motion artifact suppression in MRI

An improved algorithm for planar rotational motion artifact suppression in standard two-dimensional Fourier transform magnetic resonance images is presented. It is shown that interpolation of acquired view data on the uncorrupted k-space create data overlap and void regions. We present a method of managing overlap data regions, using weighted averaging of redundant data. The weights are assigned according to a priority ranking based on the minimum distance between the data set and the k-space grid points. An iterative estimation technique for filling the data void regions, using projections onto convex sets (POCS), is also described. The method has been successfully tested using computer simulations.