Motion artifact suppression: a review of post-processing techniques

Iterative static field map estimation for off-resonance correction in non-Cartesian susceptibility weighted imaging

Purpose

Patient‐induced inhomogeneities in the magnetic field cause distortions and blurring during acquisitions with long readouts such as in susceptibility‐weighted imaging (SWI). Most correction methods require collecting an additional ΔB0 field map to remove these artifacts.

Theory

The static ΔB0 field map can be approximated with an acceptable error directly from a single echo acquisition in SWI. The main component of the observed phase is linearly related to ΔB0 and the echo time (TE), and the relative impact of non‐ ΔB0 terms becomes insignificant with TE >20 ms at 3 T for a well‐tuned system.

Methods

The main step is to combine and unfold the multi‐channel phase maps wrapped many times, and several competing algorithms are compared for this purpose. Four in vivo brain data sets collected using the recently proposed 3D spreading projection algorithm for rapid k‐space sampling (SPARKLING) readouts are used to assess the proposed method.

Results

The estimated 3D field maps generated with a 0.6 mm isotropic spatial resolution provide overall similar off‐resonance corrections compared to reference corrections based on an external ΔB0 acquisitions, and even improved for 2 of 4 individuals. Although a small estimation error is expected, no aftermath was observed in the proposed corrections, whereas degradations were observed in the references.

Conclusion

A static ΔB0 field map estimation method was proposed to take advantage of acquisitions with long echo times, and outperformed the reference technique based on an external field map. The difference can be attributed to an inherent robustness to mismatches between volumes and external ΔB0 maps, and diverse other sources investigated.

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Physically implausible signals as a quantitative quality assessment metric in prostate diffusion-weighted MR imaging

PURPOSE

To provide a quantitative assessment of diffusion-weighted MR images of the prostate through identification of PIDS which clearly represents artifacts in the data. We calculated the percentage and distribution of PIDS in prostate DWI and compare the amount of PIDS between mpMRI images obtained with and without an endorectal coil.

METHODS

This IRB approved retrospective study (from 03/03/2014 to 03/10/2020), included 40 patients scanned with endorectal coil (ERC) and 40 without ER coil (NERC). PIDS contains any voxel where: (1) the diffusion signal increases despite an increase in b-value; and/or (2) apparent diffusion coefficient (ADC) is more than 3.0 μm²/ms (the ADC of pure water at 37 °C and it is physically implausible for any material to have a higher ADC). PIDS for transition zone (TZ) and peripheral zone (PZ) was calculated using an in-house MATLAB program. DWI images were quantitatively inspected for noise, motion, and distortion. T-test was used to compare the difference between PIDS levels in ERC versus NERC and ANOVA to compare the PIDS levels in the anatomic zones. The images were evaluated by a fellowship-trained radiologist in Abdominal Imaging with more than 10 years of experience in reading prostate MRI. This was tested only in prostate in this study.

RESULTS

80 patients (58 ± 8 years old, 80 men) were evaluated. The percentage of voxels exhibiting PIDS was 17.1 ± 8.1% for the ERC cohort and 22.2 ± 15.5% for the NERC cohort. PIDS for NERC versus ERC were not significantly different (p = 0.14). The apex and base showed similar percentages of PIDS in ERC (p = 0.30) and NERC (p = 0.86). The mid (13.8 ± 8.6%) in ERC showed lower values (p = 0.02) of PIDS compared to apex (19.9 ± 11.1%) and base (17.5 ± 8.3%).

CONCLUSION

PIDS maps provide a spatially resolved quantitative quality assessment for prostate DWI. Average PIDS over the entire prostate were similar for the ERC and NERC cohorts, and did not differ significantly across prostate zones. However, for many of the patients, PIDS was focally much higher in specific prostate zones. PIDS assessment can guide Radiologist's evaluation of images and the development of improved DWI sequences.

Optical phase modulation by natural eye movements: application to time-domain FF-OCT image retrieval

Eye movements are commonly seen as an obstacle to high-resolution ophthalmic imaging. In this context we study the natural axial movements of the in vivo human eye and show that they can be used to modulate the optical phase and retrieve tomographic images via time-domain full-field optical coherence tomography (TD-FF-OCT). This approach opens a path to a simplified ophthalmic TD-FF-OCT device, operating without the usual piezo motor-camera synchronization. The device demonstrates in vivo human corneal images under the different image retrieval schemes (2-phase and 4-phase) and different exposure times (3.5 ms, 10 ms, 20 ms). Data on eye movements, acquired with a spectral-domain OCT with axial eye tracking (180 B-scans/s), are used to study the influence of ocular motion on the probability of capturing high-signal tomographic images without phase washout. The optimal combinations of camera acquisition speed and amplitude of piezo modulation are proposed and discussed.

Sharpness in motion corrected quantitative imaging at 7T

Sub-millimeter imaging at 7T has opened new possibilities for qualitatively and quantitatively studying brain structure as it evolves throughout the life span. However, subject motion introduces image blurring on the order of magnitude of the spatial resolution and is thus detrimental to image quality. Such motion can be corrected for, but widespread application has not yet been achieved and quantitative evaluation is lacking. This raises a need to quantitatively measure image sharpness throughout the brain. We propose a method to quantify sharpness of brain structures at sub-voxel resolution, and use it to assess to what extent limited motion is related to image sharpness. The method was evaluated in a cohort of 24 healthy volunteers with a wide and uniform age range, aiming to arrive at results that largely generalize to larger populations. Using 3D fat-excited motion navigators, quantitative R₁, R₂^* and Quantitative Susceptibility Maps and T₁-weighted images were retrospectively corrected for motion. Sharpness was quantified in all modalities for selected regions of interest (ROI) by fitting the sigmoidally shaped error function to data within locally homogeneous clusters. A strong, almost linear correlation between motion and sharpness improvement was observed, and motion correction significantly improved sharpness. Overall, the Full Width at Half Maximum reduced from 0.88 mm to 0.70 mm after motion correction, equivalent to a 2.0 times smaller voxel volume. Motion and sharpness were not found to correlate with the age of study participants. We conclude that in our data, motion correction using fat navigators is overall able to restore the measured sharpness to the imaging resolution, irrespective of the amount of motion observed during scanning.

Influence of Acquisition Time on MR Image Quality Estimated with Nonparametric Measures Based on Texture Features

Correlation of parametrized image texture features (ITF) analyses conducted in different regions of interest (ROIs) overcomes limitations and reliably reflects image quality. The aim of this study is to propose a nonparametrical method and classify the quality of a magnetic resonance (MR) image that has undergone controlled degradation by using textural features in the image. Images of 41 patients, 17 women and 24 men, aged between 23 and 56 years were analyzed. T2-weighted sagittal sequences of the lumbar spine, cervical spine, and knee and T2-weighted coronal sequences of the shoulder and wrist were generated. The implementation of parallel imaging with the use of GRAPPA2, GRAPPA3, and GRAPPA4 led to a substantial reduction in the scanning time but also degraded image quality. The number of degraded image textural features was correlated with the scanning time. Longer scan times correlated with markedly higher ITF image persistence in comparison with images computed with reduced scan times. Higher ITF preservation was observed in images of bones in the spine and femur as compared to images of soft tissues, i.e., tendons and muscles. Finally, a nonparametrized image quality assessment based on an analysis of the ITF, computed for different tissues, correlating with the changes in acquisition time of the MR images, was successfully developed. The correlation between acquisition time and the number of reproducible features present in an MR image was found to yield the necessary assumptions to calculate the quality index.

Reducing motion sensitivity in 3D high-resolution T2*-weighted MRI by navigator-based motion and nonlinear magnetic field correction

T₂*-weighted gradient echo (GRE) MRI at high field is uniquely sensitive to the magnetic properties of tissue and allows the study of brain and vascular anatomy at high spatial resolution. However, it is also sensitive to B₀ field changes induced by head motion and physiological processes such as the respiratory cycle. Conventional motion correction techniques do not take these field changes into account, and consequently do not fully recover image quality in T₂*-weighted MRI. Here, a novel approach was developed to address this by monitoring the B₀ field with a volumetric EPI phase navigator. The navigator was acquired at a shorter echo time than that of the (higher resolution) T₂*-weighted GRE imaging data and accelerated with parallel imaging for high temporal resolution. At 4 ​mm isotropic spatial resolution and 0.54 ​s temporal resolution, the accuracy for estimation of rotation and translation was better than 0.2° and 0.1 ​mm, respectively. The 10% and 90% percentiles of B₀ measurement error using the navigator were -1.8 and 1.5 Hz  at 7 T, respectively. A fast retrospective reconstruction algorithm correcting for both motion and nonlinear B₀ changes was also developed. The navigator and reconstruction algorithm were evaluated in correcting motion-corrupted high-resolution T₂*-weighted GRE MRI on healthy human subjects at 7 ​T. Excellent image quality was demonstrated with the proposed correction method.

Common and Uncommon Artifacts in T1 FLAIR SAG Sequences of MRI Brain

OBJECTIVE

This study aims at identifying, classifying, and measuring the frequency the different artifacts that show up in the images of the Sagittal T1 Fluid Attenuated Inversion Recovery (FLAIR) sequence.

MATERIALS AND METHODS

A total of 101 subjects underwent brain magnetic resonance imaging examination with the following sequences: Axial T1 FLAIR, Axial T2-weighted imaging, Diffusion Weighted Imaging, 2D Multiple Echo Recombined Gradient Echo, Sagittal T1 FLAIR, Coronal T2 Turbo Spin Echo, Spin Echo T1-weighted imaging, and 3D Fast Spoiled Gradient-echo. In these images, we observed the following categories of artifacts: (a) ghost artifacts, (b) aliasing behind the occipital bone, (c) aliasing inside the sphenoid cavity, (d) susceptibility artifacts, and (e) pulsation artifacts. In order to recognize and verify the artifacts, we used not only the Sagittal T1 FLAIR sequence, but also Sagittal reconstructions from the 3-dimensional Fast Spoiled Gradient-echo sequence and the other routine sequences.

RESULTS

Aliasing artifacts and especially aliasing of nose are present in 41% of the cases. In 45% of these cases the uncommon aliasing artifacts, which took place into the brain parenchyma (sphenoid cavity, subarachnoid bay, or pituitary) originated from nose. In 33% of the subjects, ghost artifacts are presented, which stem from the nose, the orbits, or other pulsating structures (pulsation artifacts) or even from fat tissue. Moreover, susceptibility artifacts comprise 8% of all the artifacts. Finally, 19% of brains were presented without artifact.

CONCLUSIONS

We suggest in addition to T1 FLAIR, the application of Sagittal SE or TSE sequences in magnetic resonance imaging examination of brain, trying to include the nose in the square of FOV.

Effect of head motion on MRI B0 field distribution

PURPOSE

To identify and characterize the sources of B₀ field changes due to head motion, to reduce motion sensitivity in human brain MRI.

METHODS

B₀ fields were measured in 5 healthy human volunteers at various head poses. After measurement of the total field, the field originating from the subject was calculated by subtracting the external field generated by the magnet and shims. A subject-specific susceptibility model was created to quantify the contribution of the head and torso. The spatial complexity of the field changes was analyzed using spherical harmonic expansion.

RESULTS

Minor head pose changes can cause substantial and spatially complex field changes in the brain. For rotations and translations of approximately 5 º and 5 mm, respectively, at 7 T, the field change that is associated with the subject's magnetization generates a standard deviation (SD) of about 10 Hz over the brain. The stationary torso contributes to this subject-associated field change significantly with a SD of about 5 Hz. The subject-associated change leads to image-corrupting phase errors in multi-shot <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>T</mml:mi> <mml:mn>2</mml:mn> <mml:mo>*</mml:mo></mml:msubsup> </mml:mrow> </mml:math> -weighted acquisitions.

CONCLUSION

The B₀ field changes arising from head motion are problematic for multishot <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>T</mml:mi> <mml:mn>2</mml:mn> <mml:mo>*</mml:mo></mml:msubsup> </mml:mrow> </mml:math> -weighted imaging. Characterization of the underlying sources provides new insights into mitigation strategies, which may benefit from individualized predictive field models in addition to real-time field monitoring and correction strategies.

Pain Neuroimaging in Humans: A Primer for Beginners and Non-Imagers

Human pain neuroimaging has exploded in the past 2 decades. During this time, the broader neuroimaging community has continued to investigate and refine methods. Another key to progress is exchange with clinicians and pain scientists working with other model systems and approaches. These collaborative efforts require that non-imagers be able to evaluate and assess the evidence provided in these reports. Likewise, new trainees must design rigorous and reliable pain imaging experiments. In this article we provide a guideline for designing, reading, evaluating, analyzing, and reporting results of a pain neuroimaging experiment, with a focus on functional and structural magnetic resonance imaging. We focus in particular on considerations that are unique to neuroimaging studies of pain in humans, including study design and analysis, inferences that can be drawn from these studies, and the strengths and limitations of the approach.

Removing movement artifacts from equine ECG recordings acquired with textile electrodes

This study reports on the implementation of a novel system to detect and reduce movement artifact (MA) contribution in electrocardiogram (ECG) recordings acquired from horses in free movement conditions. The system comprises both integrated textile electrodes for ECG acquisition and one triaxial accelerometer for movement monitoring. Here, ECG and physical activity are continuously acquired from seven horses through the wearable system and a model that integrates cardiovascular and movement information to estimate the MA contribution is implemented. Moreover, in this study we propose a new algorithm where the Stationary Wavelet Transform (SWT) decomposition algorithm is employed to identify and remove movement artifacts from ECG recodigns. Achieved results showed a reduction of MA percentage greater than 40% between before- and after- the application of the proposed algorithm to seven hours of recordings.

The Relative Impact of Ghosting and Noise on the Perceived Quality of MR Images

Magnetic resonance (MR) imaging is vulnerable to a variety of artifacts, which potentially degrade the perceived quality of MR images and, consequently, may cause inefficient and/or inaccurate diagnosis. In general, these artifacts can be classified as structured or unstructured depending on the correlation of the artifact with the original content. In addition, the artifact can be white or colored depending on the flatness of the frequency spectrum of the artifact. In current MR imaging applications, design choices allow one type of artifact to be traded off with another type of artifact. Hence, to support these design choices, the relative impact of structured versus unstructured or colored versus white artifacts on perceived image quality needs to be known. To this end, we conducted two subjective experiments. Clinical application specialists rated the quality of MR images, distorted with different types of artifacts at various levels of degradation. The results demonstrate that unstructured artifacts deteriorate quality less than structured artifacts, while colored artifacts preserve quality better than white artifacts.

A Novel Algorithm for Movement Artifact Removal in ECG Signals Acquired from Wearable Systems Applied to Horses

This study reports on a novel method to detect and reduce the contribution of movement artifact (MA) in electrocardiogram (ECG) recordings gathered from horses in free movement conditions. We propose a model that integrates cardiovascular and movement information to estimate the MA contribution. Specifically, ECG and physical activity are continuously acquired from seven horses through a wearable system. Such a system employs completely integrated textile electrodes to monitor ECG and is also equipped with a triaxial accelerometer for movement monitoring. In the literature, the most used technique to remove movement artifacts, when noise bandwidth overlaps the primary source bandwidth, is the adaptive filter. In this study we propose a new algorithm, hereinafter called Stationary Wavelet Movement Artifact Reduction (SWMAR), where the Stationary Wavelet Transform (SWT) decomposition algorithm is employed to identify and remove movement artifacts from ECG signals in horses. A comparative analysis with the Normalized Least Mean Square Adaptive Filter technique (NLMSAF) is performed as well. Results achieved on seven hours of recordings showed a reduction greater than 40% of MA percentage (between before- and after- the application of the proposed algorithm). Moreover, the comparative analysis with the NLMSAF, applied to the same ECG recordings, showed a greater reduction of MA percentage in favour of SWMAR with a statistical significant difference (p-value < 0.0.5).

Lung dynamic MRI deblurring using low-rank decomposition and dictionary learning

PURPOSE

Lung dynamic MRI (dMRI) has emerged to be an appealing tool to quantify lung motion for both planning and treatment guidance purposes. However, this modality can result in blurry images due to intrinsically low signal-to-noise ratio in the lung and spatial/temporal interpolation. The image blurring could adversely affect the image processing that depends on the availability of fine landmarks. The purpose of this study is to reduce dMRI blurring using image postprocessing.

METHODS

To enhance the image quality and exploit the spatiotemporal continuity of dMRI sequences, a low-rank decomposition and dictionary learning (LDDL) method was employed to deblur lung dMRI and enhance the conspicuity of lung blood vessels. Fifty frames of continuous 2D coronal dMRI frames using a steady state free precession sequence were obtained from five subjects including two healthy volunteer and three lung cancer patients. In LDDL, the lung dMRI was decomposed into sparse and low-rank components. Dictionary learning was employed to estimate the blurring kernel based on the whole image, low-rank or sparse component of the first image in the lung MRI sequence. Deblurring was performed on the whole image sequences using deconvolution based on the estimated blur kernel. The deblurring results were quantified using an automated blood vessel extraction method based on the classification of Hessian matrix filtered images. Accuracy of automated extraction was calculated using manual segmentation of the blood vessels as the ground truth.

RESULTS

In the pilot study, LDDL based on the blurring kernel estimated from the sparse component led to performance superior to the other ways of kernel estimation. LDDL consistently improved image contrast and fine feature conspicuity of the original MRI without introducing artifacts. The accuracy of automated blood vessel extraction was on average increased by 16% using manual segmentation as the ground truth.

CONCLUSIONS

Image blurring in dMRI images can be effectively reduced using a low-rank decomposition and dictionary learning method using kernels estimated by the sparse component.

Quantitative framework for prospective motion correction evaluation

PURPOSE

Establishing a framework to evaluate performances of prospective motion correction (PMC) MRI considering motion variability between MRI scans.

METHODS

A framework was developed to obtain quantitative comparisons between different motion correction setups, considering that varying intrinsic motion patterns between acquisitions can induce bias. Intrinsic motion was considered by replaying in a phantom experiment the recorded motion trajectories from subjects. T1-weighted MRI on five volunteers and two different marker fixations (mouth guard and nose bridge fixations) were used to test the framework. Two metrics were investigated to quantify the improvement of the image quality with PMC.

RESULTS

Motion patterns vary between subjects as well as between repeated scans within a subject. This variability can be approximated by replaying the motion in a distinct phantom experiment and used as a covariate in models comparing motion corrections. We show that considering the intrinsic motion alters the statistical significance in comparing marker fixations. As an example, two marker fixations, a mouth guard and a nose bridge, were evaluated in terms of their effectiveness for PMC. A mouth guard achieved better PMC performance.

CONCLUSION

Intrinsic motion patterns can bias comparisons between PMC configurations and must be considered for robust evaluations. A framework for evaluating intrinsic motion patterns in PMC is presented.

Motion-compensation techniques in neonatal and fetal MR imaging

SUMMARY

Fetal and neonatal MR imaging is increasingly used as a complementary diagnostic tool to sonography. MR imaging is an ideal technique for imaging fetuses and neonates because of the absence of ionizing radiation, the superior contrast of soft tissues compared with sonography, the availability of different contrast options, and the increased FOV. Motion in the normally mobile fetus and the unsettled, sleeping, or sedated neonate during a long acquisition will decrease image quality in the form of motion artifacts, hamper image interpretation, and often necessitate a repeat MR imaging to establish a diagnosis. This article reviews current techniques of motion compensation in fetal and neonatal MR imaging, including the following: 1) motion-prevention strategies (such as adequate patient preparation, patient coaching, and sedation, when required), 2) motion-artifacts minimization methods (such as fast imaging protocols, data undersampling, and motion-resistant sequences), and 3) motion-detection/correction schemes (such as navigators and self-navigated sequences, external motion-tracking devices, and postprocessing approaches) and their application in fetal and neonatal brain MR imaging. Additionally some background on the repertoire of motion of the fetal and neonatal patient and the resulting artifacts will be presented, as well as insights into future developments and emerging techniques of motion compensation.

On the significance of motion degradation in high-resolution 3D μMRI of trabecular bone

RATIONALE AND OBJECTIVES

Subtle subject movement during high-resolution three-dimensional micro-magnetic resonance imaging of trabecular bone (TB) causes blurring, thereby rendering the data unreliable for quantitative analysis. In this work, the effects of translational and rotational motion displacements were evaluated qualitatively and quantitatively.

MATERIALS AND METHODS

In experiment 1, motion was induced by applying various simulated and previously observed in vivo trajectories as phase shifts to k-space or rotation angles to k-space segments of a virtually motion-free data set. In experiment 2, images that were visually free of motion artifacts from two groups of 10 healthy individuals, differing in age, were selected to probe the effects of motion on TB parameters. In both experiments, images were rated for motion severity, and the scores were compared to a focus criterion, the normalized gradient squared.

RESULTS

Strong correlations were observed between the motion quality scores and the corresponding normalized gradient squared values (R(2) = 0.52-0.64, P < .01). The results from experiment 1 demonstrated consistently lower image quality and alterations in structural parameters of 9% to 45% with increased amplitude of displacements. In experiment 2, the significant differences in structural parameter group means of the motion-free images were lost upon motion degradation. Autofocusing, a postprocessing correction method, partially recovered the sharpness of the original motion-free images in 13 of 20 subjects.

CONCLUSIONS

Quantitative TB structural measures are highly sensitive to subtle motion-induced degradation, which adversely affects precision and statistical power. The results underscore the influence of subject movement in high-resolution three-dimensional micro-magnetic resonance imaging and its correction for TB structure analysis.

Automatic quality assessment in structural brain magnetic resonance imaging

MRI has evolved into an important diagnostic technique in medical imaging. However, reliability of the derived diagnosis can be degraded by artifacts, which challenge both radiologists and automatic computer-aided diagnosis. This work proposes a fully-automatic method for measuring image quality of three-dimensional (3D) structural MRI. Quality measures are derived by analyzing the air background of magnitude images and are capable of detecting image degradation from several sources, including bulk motion, residual magnetization from incomplete spoiling, blurring, and ghosting. The method has been validated on 749 3D T(1)-weighted 1.5T and 3T head scans acquired at 36 Alzheimer's Disease Neuroimaging Initiative (ADNI) study sites operating with various software and hardware combinations. Results are compared against qualitative grades assigned by the ADNI quality control center (taken as the reference standard). The derived quality indices are independent of the MRI system used and agree with the reference standard quality ratings with high sensitivity and specificity (>85%). The proposed procedures for quality assessment could be of great value for both research and routine clinical imaging. It could greatly improve workflow through its ability to rule out the need for a repeat scan while the patient is still in the magnet bore.

RINGLET motion correction for 3D MRI acquired with the elliptical centric view order

A new rigid-body motion correction algorithm is described that is compatible with 3D image sets acquired with the elliptical centric (EC) view order. With this view order, an annular ring of k-space data is acquired in the ky-kz plane during any short time interval. Images for tracking motion can be reconstructed in the yz-plane from any ring of the acquisition data. In these tracking images, a point source (such as an external marker) shows a characteristic bull's-eye pattern that permits motion monitoring and correction. The true position of the point object is located at the center of the bull's-eye pattern. Cross correlation can be performed to automatically track the positions of markers reconstructed from adjacent rings of k-space. To increase the marker signal, the markers are encased in inductively coupled RF coils. Rigid-body motion in the yz-plane is calculated directly with the Euclidean group for rotation and translation, and corrected by rotating and applying phase shifts to any corrupted rings of data. In the current work we present a theoretical analysis of this method, as well as results of volunteer and controlled phantom experiments that demonstrate its initial feasibility. Although the EC view order has mainly been used for MR angiography (MRA), it can also be used for most 3D acquisitions.

Motion artifact in magnetic resonance imaging: implications for automated analysis

Automated measures of cerebral magnetic resonance images (MRI) often provide greater speed and reliability compared to manual techniques but can be particularly sensitive to motion artifact. This study employed an automatic MRI analysis program that quantified regional gray matter volume and created images for verification and quality control. Motion artifact was assessed on each image and assigned a rating of none, mild, moderate, or severe. Greater motion artifact was associated with smaller gray matter volumes. Severity of motion artifact is an important, but often overlooked, consideration in the interpretation of automated MRI measures.

Implications of respiratory motion for the quantification of 2D MR spectroscopic imaging data in the abdomen

Magnetic resonance spectroscopic imaging (MRSI) studies in the abdomen or breast are acquired in the presence of respiratory motion. This modifies the point spread function (PSF) and hence the reconstructed spectra. We evaluated the quantitative effects of both periodic and aperiodic motion on spectra localized by MRSI. Artefactual signal changes, both the modification of native to a voxel and spurious signals arising elsewhere, depend primarily upon the motion amplitude relative to the voxel dimension. A similar dependence on motion amplitude was observed for simple harmonic motion (SHM), quasi-periodic motion and random displacements. No systematic dependence upon the period or initial phase of SHM or on the array size was found. There was also no significant variation with motion direction relative to the internal and external phase-encoding directions. In measured excursion ranges of 20 breast and abdominal tumours, 70% moved < or = 5 mm, while 30% moved 6-23 mm. The diaphragm and fatty tissues in the gut typically moved approximately 15-20 mm. While tumour/organ excursions less than half the voxel dimension do not substantially affect native signals, the bleeding in of strong lipid signals will be problematic in 1H studies. MRSI studies in the abdomen, even of relatively well-anchored tumours, are thus likely to benefit from the addition of respiratory triggering or other motion compensation strategies.

Reduction of motion artifacts in magnetic resonance imaging of the neck and cervical spine by long-term averaging

RATIONALE AND OBJECTIVES

We performed a prospective comparison of T1-weighted turbo spin-echo (TSE) imaging with standard averaging and with the long-term averaging method (LOTA), comparing the effects on signal-to-artifact noise ratio (S/aN) and motion artifacts.

METHODS

In 30 consecutive patients undergoing imaging of the neck or cervical spine, a transverse T1-weighted TSE sequence was applied with and without LOTA by using identical sequence parameters. Quantitative image analysis was done by calculating S/Ns in the phase-encoding direction (S/aN). Visual image analysis was performed by four independent, masked readers using a standardized score sheet for anatomic and pathological findings.

RESULTS

The LOTA sequence yielded significantly superior S/aN values compared with the standard averaging sequence. In the subjective evaluation, the LOTA sequence showed significantly fewer motion artifacts and better visualization of normal anatomy of the neck, cervical spine, and spinal cord, as well as of the pathological findings.

CONCLUSIONS

LOTA is a valuable method for increasing S/aN in magnetic resonance imaging of the neck and cervical spine. It reduces motion artifacts and increases the conspicuity of pathology without increasing acquisition time. No additional hardware is needed, and this technique can be combined with other artifact-reducing methods.

Uniqueness of tomography with unknown view angles

In the standard two-dimensional (2-D) parallel beam tomographic formulation, it is assumed that the angles at which the projections were acquired are known. In certain situations, however, these angles are known only approximately (as in the case of magnetic resonance imaging (MRI) of a moving patient), or are completely unknown. The latter occurs in a three-dimensional (3-D) version of the problem in the electron microscopy-based imaging of viral particles. We address the problem of determining the view angles directly from the projection data itself in the 2-D parallel beam case. We prove the surprising result that under some fairly mild conditions, the view angles are uniquely determined by the projection data. We present conditions for the unique recovery of these view angles based on the Helgasson-Ludwig consistency conditions for the Radon transform, we also show that when the projections are shifted by some random amount which must be jointly estimated with the view angles, unique recovery of both the shifts and view angles is possible.

Feasibility of tomography with unknown view angles

In the standard two-dimensional (2-D) parallel beam tomographic formulation, it is generally assumed that the angles at which the projections were acquired are known. We have previously demonstrated, however, that under fairly mild conditions these view angles can be uniquely recovered from the projections themselves. We address the question of reliability of such solutions to the angle recovery problem using moments of the projections. We demonstrate that under mild conditions, the angle recovery problem has unique solutions and is stable with respect to perturbations in the data. Furthermore, we determine the Cramer-Rao lower bounds on the variance of the estimates of the angles when the projection are corrupted by additive Gaussian noise. We also treat the case in which each projection is shifted by some unknown amount which must be jointly estimated with the view angles. Motivated by the stability results and relatively small values of the error bounds, we construct a simple algorithm to approximate the ML estimator and demonstrate that the problem can be feasibly solved in the presence of noise. Simulations using this simple estimator on a variety of phantoms show excellent performance at low to moderate noise levels, essentially achieving the Cramer-Rao bounds.

Linear motion correction in three dimensions applied to dynamic gadolinium enhanced breast imaging

Quantitative analysis of dynamic gadolinium-DTPA (diethylenetriamine pentaacetic acid) enhanced magnetic resonance imaging (MRI) is emerging as a highly sensitive tool for detecting malignant breast tissue. Three-dimensional rapid imaging techniques, such as keyhole MRI, yield high temporal sampling rates to accurately track contrast enhancement and washout in lesions over the course of multiple volume acquisitions. Patient motion during the dynamic acquisitions is a limiting factor that degrades the image quality, particularly of subsequent subtraction images used to identify and quantitatively evaluate regions suggestive of malignancy. Keyhole imaging is particularly sensitive to motion since datasets acquired over an extended period are combined in k-space. In this study, motion is modeled as set of translations in each of the three orthogonal dimensions. The specific objective of the study is to develop and implement an algorithm to correct the consequent phase shifts in k-space data prior to offline keyhole reconstruction three-dimensional (3D) volume breast MR acquisitions.

Review and evaluation of MRI nonuniformity corrections for brain tumor response measurements

Current MRI nonuniformity correction techniques are reviewed and investigated. Many approaches are used to remedy this artifact, but it is not clear which method is the most appropriate in a given situation, as the applications have been with different MRI coils and different clinical applications. In this work four widely used nonuniformity correction techniques are investigated in order to assess the effect on tumor response measurements (change in tumor volume over time): a phantom correction method, an image smoothing technique, homomorphic filtering, and surface fitting approach. Six brain tumor cases with baseline and follow-up MRIs after treatment with varying degrees of difficulty of segmentation were analyzed without and with each of the nonuniformity corrections. Different methods give significantly different correction images, indicating that rf nonuniformity correction is not yet well understood. No improvement in tumor segmentation or in tumor growth/shrinkage assessment was achieved using any of the evaluated corrections.

Two motion-detection algorithms for projection-reconstruction magnetic resonance imaging: theory and experimental verification

In this paper, projection-reconstruction (PR) magnetic resonance (MR) imaging is considered. We present two new quantitative techniques that allow to check when motion was present during a PR MR experiment. No a priori information about the motion is required since only the measured MR signals are used in the calculations. Moreover, the proposed methods can be implemented on a standard personal computer or workstation. It is experimentally shown that both methods are able to detect motion intervals with an accuracy of one repetition time.

Planar-motion correction with use of K-space data acquired in Fourier MR imaging

The authors have developed a method for reducing magnetic resonance (MR) image artifacts caused by planar motion. Segments of k-space acquired with the subject stationary are detected automatically. Each k-space segment is Fourier transformed into an image in which rotational and translational displacements are measured manually. Before correction, k-space is made as Hermitian as allowed by the largest symmetric range of low spatial frequencies acquired with the subject stationary. Segments of k-space acquired with the subject in different positions are corrected separately. Although translation corrections can be applied effectively to both k-space and the spatial domain, rotation corrections are applied in the spatial domain to avoid image artifacts. To complement the correction, data corrupted by rotation are replaced by the complex conjugate of data of the opposite kappa x and kappa y, provided that these data have not been corrupted by rotation. The method reduced ghosts and blurring substantially on sagittal head images acquired with a standard spin-echo pulse sequence while a volunteer subject nodded his head.

Respiratory triggered imaging with an optical displacement sensor

Motion of abdominal organs with respiration is a major problem in NMR spectroscopy and imaging thereof. Triggering each phase-encoding step with respiration or gating a number of phase-encoding steps is one approach to the problem. The design of a sensor for small animal experiments has not been as simple. An optical device, implemented with polymer optical fibres is described, along with associated hardware and electronics which can act as a trigger for small animal NMR experiments. A brief description of a similar device for human application is also given. 2DFT spin-echo and B0 susceptibility images, both triggered and untriggered, are presented to validate the technique.