Prospective motion correction in brain imaging: a review

Blind multirigid retrospective motion correction of MR images

PURPOSE

Physiological nonrigid motion is inevitable when imaging, e.g., abdominal viscera, and can lead to serious deterioration of the image quality. Prospective techniques for motion correction can handle only special types of nonrigid motion, as they only allow global correction. Retrospective methods developed so far need guidance from navigator sequences or external sensors. We propose a fully retrospective nonrigid motion correction scheme that only needs raw data as an input.

METHODS

Our method is based on a forward model that describes the effects of nonrigid motion by partitioning the image into patches with locally rigid motion. Using this forward model, we construct an objective function that we can optimize with respect to both unknown motion parameters per patch and the underlying sharp image.

RESULTS

We evaluate our method on both synthetic and real data in 2D and 3D. In vivo data was acquired using standard imaging sequences. The correction algorithm significantly improves the image quality. Our compute unified device architecture (CUDA)-enabled graphic processing unit implementation ensures feasible computation times.

CONCLUSION

The presented technique is the first computationally feasible retrospective method that uses the raw data of standard imaging sequences, and allows to correct for nonrigid motion without guidance from external motion sensors.

Real-time motion- and B0-correction for LASER-localized spiral-accelerated 3D-MRSI of the brain at 3T

The full potential of magnetic resonance spectroscopic imaging (MRSI) is often limited by localization artifacts, motion-related artifacts, scanner instabilities, and long measurement times. Localized adiabatic selective refocusing (LASER) provides accurate B1-insensitive spatial excitation even at high magnetic fields. Spiral encoding accelerates MRSI acquisition, and thus, enables 3D-coverage without compromising spatial resolution. Real-time position- and shim/frequency-tracking using MR navigators correct motion- and scanner instability-related artifacts. Each of these three advanced MRI techniques provides superior MRSI data compared to commonly used methods. In this work, we integrated in a single pulse sequence these three promising approaches. Real-time correction of motion, shim, and frequency-drifts using volumetric dual-contrast echo planar imaging-based navigators were implemented in an MRSI sequence that uses low-power gradient modulated short-echo time LASER localization and time efficient spiral readouts, in order to provide fast and robust 3D-MRSI in the human brain at 3T. The proposed sequence was demonstrated to be insensitive to motion- and scanner drift-related degradations of MRSI data in both phantoms and volunteers. Motion and scanner drift artifacts were eliminated and excellent spectral quality was recovered in the presence of strong movement. Our results confirm the expected benefits of combining a spiral 3D-LASER-MRSI sequence with real-time correction. The new sequence provides accurate, fast, and robust 3D metabolic imaging of the human brain at 3T. This will further facilitate the use of 3D-MRSI for neuroscience and clinical applications.

A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics

Functional connectomics is one of the most rapidly expanding areas of neuroimaging research. Yet, concerns remain regarding the use of resting-state fMRI (R-fMRI) to characterize inter-individual variation in the functional connectome. In particular, recent findings that "micro" head movements can introduce artifactual inter-individual and group-related differences in R-fMRI metrics have raised concerns. Here, we first build on prior demonstrations of regional variation in the magnitude of framewise displacements associated with a given head movement, by providing a comprehensive voxel-based examination of the impact of motion on the BOLD signal (i.e., motion-BOLD relationships). Positive motion-BOLD relationships were detected in primary and supplementary motor areas, particularly in low motion datasets. Negative motion-BOLD relationships were most prominent in prefrontal regions, and expanded throughout the brain in high motion datasets (e.g., children). Scrubbing of volumes with FD>0.2 effectively removed negative but not positive correlations; these findings suggest that positive relationships may reflect neural origins of motion while negative relationships are likely to originate from motion artifact. We also examined the ability of motion correction strategies to eliminate artifactual differences related to motion among individuals and between groups for a broad array of voxel-wise R-fMRI metrics. Residual relationships between motion and the examined R-fMRI metrics remained for all correction approaches, underscoring the need to covary motion effects at the group-level. Notably, global signal regression reduced relationships between motion and inter-individual differences in correlation-based R-fMRI metrics; Z-standardization (mean-centering and variance normalization) of subject-level maps for R-fMRI metrics prior to group-level analyses demonstrated similar advantages. Finally, our test-retest (TRT) analyses revealed significant motion effects on TRT reliability for R-fMRI metrics. Generally, motion compromised reliability of R-fMRI metrics, with the exception of those based on frequency characteristics - particularly, amplitude of low frequency fluctuations (ALFF). The implications of our findings for decision-making regarding the assessment and correction of motion are discussed, as are insights into potential differences among volume-based metrics of motion.

Fast noniterative calibration of an external motion tracking device

PURPOSE

Prospective motion correction of magnetic resonance (MR) scans commonly uses an external device, such as a camera, to track the pose of the organ of interest. However, in order for external tracking data to be translated into the MR scanner reference frame, the pose of the camera relative to the MR scanner must be known accurately. Here, we describe a fast, accurate, non-iterative technique to determine the position of an external tracking device de novo relative to the MR reference frame.

THEORY AND METHODS

The method relies on imaging a sparse object that allows simultaneous tracking of arbitrary rigid body transformations in the reference frame of the magnetic resonance imaging (MRI) machine and that of the external tracking device.

RESULTS

Large motions in the MRI reference frame can be measured using a sparse phantom with an accuracy of 0.2 mm, or approximately 1/10 of the voxel size. By using a dual quaternion algorithm to solve the calibration problem, a good camera calibration can be achieved with fewer than six measurements. Further refinements can be achieved by applying the method iteratively and using motion correction feedback.

CONCLUSION

Independent tracking of a series of movements in two reference frames allows for an analytical solution to the hand-eye-calibration problem for various motion tracking setups in MRI.

Advanced respiratory motion compensation for coronary MR angiography

Despite technical advances, respiratory motion remains a major impediment in a substantial amount of patients undergoing coronary magnetic resonance angiography (CMRA). Traditionally, respiratory motion compensation has been performed with a one-dimensional respiratory navigator positioned on the right hemi-diaphragm, using a motion model to estimate and correct for the bulk respiratory motion of the heart. Recent technical advancements has allowed for direct respiratory motion estimation of the heart, with improved motion compensation performance. Some of these new methods, particularly using image-based navigators or respiratory binning, allow for more advanced motion correction which enables CMRA data acquisition throughout most or all of the respiratory cycle, thereby significantly reducing scan time. This review describes the three components typically involved in most motion compensation strategies for CMRA, including respiratory motion estimation, gating and correction, and how these processes can be utilized to perform advanced respiratory motion compensation.

Advances in multimodal neuroimaging: hybrid MR-PET and MR-PET-EEG at 3 T and 9.4 T

Multi-modal MR-PET-EEG data acquisition in simultaneous mode confers a number of advantages at 3 T and 9.4 T. The three modalities complement each other well; structural-functional imaging being the domain of MRI, molecular imaging with specific tracers is the strength of PET, and EEG provides a temporal dimension where the other two modalities are weak. The utility of hybrid MR-PET at 3 T in a clinical setting is presented and critically discussed. The potential problems and the putative gains to be accrued from hybrid imaging at 9.4 T, with examples from the human brain, are outlined. Steps on the road to 9.4 T multi-modal MR-PET-EEG are also illustrated. From an MR perspective, the potential for ultra-high resolution structural imaging is discussed and example images of the cerebellum with an isotropic resolution of 320 μm are presented, setting the stage for hybrid imaging at ultra-high field. Further, metabolic imaging is discussed and high-resolution images of the sodium distribution are presented. Examples of tumour imaging on a 3 T MR-PET system are presented and discussed. Finally, the perspectives for multi-modal imaging are discussed based on two on-going studies, the first comparing MR and PET methods for the measurement of perfusion and the second which looks at tumour delineation based on MRI contrasts but the knowledge of tumour extent is based on simultaneously acquired PET data.

The Use of a priori Information in ICA-Based Techniques for Real-Time fMRI: An Evaluation of Static/Dynamic and Spatial/Temporal Characteristics

Real-time brain functional MRI (rt-fMRI) allows in vivo non-invasive monitoring of neural networks. The use of multivariate data-driven analysis methods such as independent component analysis (ICA) offers an attractive trade-off between data interpretability and information extraction, and can be used during both task-based and rest experiments. The purpose of this study was to assess the effectiveness of different ICA-based procedures to monitor in real-time a target IC defined from a functional localizer which also used ICA. Four novel methods were implemented to monitor ongoing brain activity in a sliding window approach. The methods differed in the ways in which a priori information, derived from ICA algorithms, was used to monitor a target independent component (IC). We implemented four different algorithms, all based on ICA. One Back-projection method used ICA to derive static spatial information from the functional localizer, off-line, which was then back-projected dynamically during the real-time acquisition. The other three methods used real-time ICA algorithms that dynamically exploited temporal, spatial, or spatial-temporal priors during the real-time acquisition. The methods were evaluated by simulating a rt-fMRI experiment that used real fMRI data. The performance of each method was characterized by the spatial and/or temporal correlation with the target IC component monitored, computation time, and intrinsic stochastic variability of the algorithms. In this study the Back-projection method, which could monitor more than one IC of interest, outperformed the other methods. These results are consistent with a functional task that gives stable target ICs over time. The dynamic adaptation possibilities offered by the other ICA methods proposed may offer better performance than the Back-projection in conditions where the functional activation shows higher spatial and/or temporal variability.

Reproduction of motion artifacts for performance analysis of prospective motion correction in MRI

PURPOSE

Despite numerous publications describing the ability of prospective motion correction to improve image quality in magnetic resonance imaging of the brain, a reliable approach to assess this improvement is still missing. A method that accurately reproduces motion artifacts correctable with prospective motion correction is developed, and enables the quantification of the improvements achieved.

METHODS

A software interface was developed to simulate rigid body motion by changing the scanning coordinate system relative to the object. Thus, tracking data recorded during a patient scan can be used to reproduce the prevented motion artifacts on a volunteer or a phantom. The influence of physiological motion on image quality was investigated by filtering these data. Finally, the method was used to reproduce and quantify the motion artifacts prevented in a patient scan.

RESULTS

The accuracy of the method was tested in phantom experiments and in vivo. The calculated quality factor, as well as a visual inspection of the reproduced artifacts shows a good correspondence to the original.

CONCLUSION

Precise reproduction of motion artifacts assists qualification of prospective motion correction strategies. The presented method provides an important tool to investigate the effects of rigid body motion on a wide range of sequences, and to quantify the improvement in image quality through prospective motion correction.

An embedded optical tracking system for motion-corrected magnetic resonance imaging at 7T

OBJECT

Prospective motion correction using data from optical tracking systems has been previously shown to reduce motion artifacts in MR imaging of the head. We evaluate a novel optical embedded tracking system.

MATERIALS AND METHODS

The home-built optical embedded tracking system performs image processing within a 7 T scanner bore, enabling high speed tracking. Corrected and uncorrected in vivo MR volumes are acquired interleaved using a modified 3D FLASH sequence, and their image quality is assessed and compared.

RESULTS

The latency between motion and correction of the slice position was measured to be (19 ± 5) ms, and the tracking noise has a standard deviation no greater than 10 μm/0.005° during conventional MR scanning. Prospective motion correction improved the edge strength by 16 % on average, even though the volunteers were asked to remain motionless during the acquisitions.

CONCLUSION

Using a novel method for validating the effectiveness of in vivo prospective motion correction, we have demonstrated that prospective motion correction using motion data from the embedded tracking system considerably improved image quality.