Magnetic resonance imaging of freely moving objects: prospective real-time motion correction using an external optical motion tracking system

Ultrasound-based sensors to monitor physiological motion

PURPOSE

Medical procedures can be difficult to perform on anatomy that is constantly moving. Respiration displaces internal organs by up to several centimeters with respect to the surface of the body, and patients often have limited ability to hold their breath. Strategies to compensate for motion during diagnostic and therapeutic procedures require reliable information to be available. However, current devices often monitor respiration indirectly, through changes on the outline of the body, and they may be fixed to floors or ceilings, and thus unable to follow a given patient through different locations. Here we show that small ultrasound-based sensors referred to as "organ configuration motion" (OCM) sensors can be fixed to the abdomen and/or chest and provide information-rich, breathing-related signals.

METHODS

By design, the proposed sensors are relatively inexpensive. Breathing waveforms were obtained from tissues at varying depths and/or using different sensor placements. Validation was performed against breathing waveforms derived from magnetic resonance imaging (MRI) and optical tracking signals in five and eight volunteers, respectively.

RESULTS

Breathing waveforms from different modalities were scaled so they could be directly compared. Differences between waveforms were expressed in the form of a percentage, as compared to the amplitude of a typical breath. Expressed in this manner, for shallow tissues, OCM-derived waveforms on average differed from MRI and optical tracking results by 13.1% and 15.5%, respectively.

CONCLUSION

The present results suggest that the proposed sensors provide measurements that properly characterize breathing states. While OCM-based waveforms from shallow tissues proved similar in terms of information content to those derived from MRI or optical tracking, OCM further captured depth-dependent and position-dependent (i.e., chest and abdomen) information. In time, the richer information content of OCM-based waveforms may enable better respiratory gating to be performed, to allow diagnostic and therapeutic equipment to perform at their best.

Segmented simultaneous multi-slice diffusion-weighted imaging with navigated 3D rigid motion correction

PURPOSE

To improve the robustness of diffusion-weighted imaging (DWI) data acquired with segmented simultaneous multi-slice (SMS) echo-planar imaging (EPI) against in-plane and through-plane rigid motion.

THEORY AND METHODS

The proposed algorithm incorporates a 3D rigid motion correction and wavelet denoising into the image reconstruction of segmented SMS-EPI diffusion data. Low-resolution navigators are used to estimate shot-specific diffusion phase corruptions and 3D rigid motion parameters through SMS-to-volume registration. The shot-wise rigid motion and phase parameters are integrated into a SENSE-based full-volume reconstruction for each diffusion direction. The algorithm is compared to a navigated SMS reconstruction without gross motion correction in simulations and in vivo studies with four-fold interleaved 3-SMS diffusion tensor acquisitions.

RESULTS

Simulations demonstrate high fidelity was achieved in the SMS-to-volume registration, with submillimeter registration errors and improved image reconstruction quality. In vivo experiments validate successful artifact reduction in 3D motion-compromised in vivo scans with a temporal motion resolution of approximately 0.3 s.

CONCLUSION

This work demonstrates the feasibility of retrospective 3D rigid motion correction from shot navigators for segmented SMS DWI.

Motion correction methods for MRS: experts' consensus recommendations

Long acquisition times due to intrinsically low signal-to-noise ratio and the need for highly homogeneous B₀ field make MRS particularly susceptible to motion or scanner instability compared with MRI. Motion-induced changes in both localization and shimming (ie B₀ homogeneity) degrade MRS data quality. To mitigate the effects of motion three approaches can be employed: (1) subject immobilization, (2) retrospective correction, and (3) prospective real-time correction using internal and/or external tracking methods. Prospective real-time correction methods can simultaneously update localization and the B₀ field to improve MRS data quality. While localization errors can be corrected with both internal (navigators) and external (optical camera, NMR probes) tracking methods, the B₀ field correction requires internal navigator methods to measure the B₀ field inside the imaged volume and the possibility to update the scanner shim hardware in real time. Internal and external tracking can rapidly update the MRS localization with submillimeter and subdegree precision, while scanner frequency and first-order shims of scanner hardware can be updated by internal methods every sequence repetition. These approaches are most well developed for neuroimaging, for which rigid transformation is primarily applicable. Real-time correction greatly improves the stability of MRS acquisition and quantification, as shown in clinical studies on subjects prone to motion, including children and patients with movement disorders, enabling robust measurement of metabolite signals including those with low concentrations, such as gamma-aminobutyric acid and glutathione. Thus, motion correction is recommended for MRS users and calls for tighter integration and wider availability of such methods by MR scanner manufacturers.

Combining prospective and retrospective motion correction based on a model for fast continuous motion

PURPOSE

Prospective motion correction (PMC) and retrospective motion correction (RMC) have different advantages and limitations. The present work aims to combine the advantages of both for rigid body motion, aiming at correcting for faster motions than was previously achievable. Additionally, it provides insights into the effects of motion on pulse sequences and MR signals with a goal of further improving motion correction in the future.

METHODS

The effective encoding trajectory and a global phase offset in a moving object are calculated based on complete gradient waveforms of an arbitrary sequence and a continuous motion model. These data are used to feed the forward signal model, which is then used in iterative image reconstruction to suppress the artifacts still present after the PMC.

RESULTS

Verification experiments with a rotation phantom and in vivo were performed. Predictions of simulated motion artifacts for PMC based on sequence waveforms are very accurate. The performance at combined PMC+RMC is limited by Nyquist violations in the sampled k-space and can be compensated by oversampling.

CONCLUSION

The combined correction results in better images than pure PMC in the presence of fast motion. The predictions of artifacts are very accurate, allowing for comparing sequences or protocols in simulations. The observed artifacts due to Nyquist violations are expected to be corrected by utilizing parallel imaging.

Quantitative T1 mapping using multi-slice multi-shot inversion recovery EPI

An efficient multi-slice inversion–recovery EPI (MS-IR-EPI) sequence for fast, high spatial resolution, quantitative T₁ mapping is presented, using a segmented simultaneous multi-slice acquisition, combined with slice order shifting across multiple acquisitions. The segmented acquisition minimises the effective TE and readout duration compared to a single-shot EPI scheme, reducing geometric distortions to provide high quality T₁ maps with a narrow point-spread function. The precision and repeatability of MS-IR-EPI T₁ measurements are assessed using both T₁-calibrated and T₂-calibrated ISMRM/NIST phantom spheres at 3 and 7 T and compared with single slice IR and MP2RAGE methods. Magnetization transfer (MT) effects of the spectrally-selective fat-suppression (FS) pulses required for in vivo imaging are shown to shorten the measured in-vivo T₁ values. We model the effect of these fat suppression pulses on T₁ measurements and show that the model can remove their MT contribution from the measured T₁, thus providing accurate T₁ quantification. High spatial resolution T₁ maps of the human brain generated with MS-IR-EPI at 7 T are compared with those generated with the widely implemented MP2RAGE sequence. Our MS-IR-EPI sequence provides high SNR per unit time and sharper T₁ maps than MP2RAGE, demonstrating the potential for ultra-high resolution T₁ mapping and the improved discrimination of functionally relevant cortical areas in the human brain.

Strategies to improve intratrain prospective motion correction for turbo spin-echo sequences with constant flip angles

PURPOSE

To investigate the effects of prospective motion correction on turbo spin echo sequences and optimize motion correction approaches, mitigating signal dropout artifacts caused by the imperfections of motion tracking data.

METHODS

Signal dropout artifacts caused by undesired phase deviations introduced by tracking errors are analyzed theoretically. To reduce the adverse effect of such deviations, two approaches are proposed: (1) freezing the correction for example, for even-numbered or higher number of echoes and (2) shifting the correction event prior to the left crusher gradient preceding the refocusing pulse. A comprehensive analysis is presented, including both signal simulations and experimental verifications in phantoms and in vivo. Performance of the proposed approach is validated in two healthy volunteers imaged under two types of motion conditions simulating inadvertent fast motions associated with discomfort and continuous large motions.

RESULTS

The results show that the proposed optimization is able to efficiently correct for the motion artifacts and at the same time avoid signal dropout artifacts. Specifically, performing correction every 4^th echo prior to the left crusher gradient was shown to improve image quality.

CONCLUSION

An optimization approach is proposed to exploit the potential of external tracking for intra-echo-train motion artifact correction for turbo spin echo sequences.

MC2 -Net: motion correction network for multi-contrast brain MRI

PURPOSE

A motion-correction network for multi-contrast brain MRI is proposed to correct in-plane rigid motion artifacts in brain MR images using deep learning.

METHOD

The proposed method consists of 2 parts: image alignment and motion correction. Alignment of multi-contrast MR images is performed in an unsupervised manner by a CNN work, yielding transformation parameters to align input images in order to minimize the normalized cross-correlation loss among multi-contrast images. Then, fine-tuning for image alignment is performed by maximizing the normalized mutual information. The motion correction network corrects motion artifacts in the aligned multi-contrast images. The correction network is trained to minimize the structural similarity loss and the VGG loss in a supervised manner. All datasets of motion-corrupted images are generated using motion simulation based on MR physics.

RESULTS

A motion-correction network for multi-contrast brain MRI successfully corrected artifacts of simulated motion for 4 test subjects, showing 0.96%, 7.63%, and 5.03% increases in the average structural simularity and 5.19%, 10.2%, and 7.48% increases in the average normalized mutual information for T₁ -weighted, T₂ -weighted, and T₂ -weighted fluid-attenuated inversion recovery images, respectively. The experimental setting with image alignment and artifact-free input images for other contrasts shows better performances in correction of simulated motion artifacts. Furthermore, the proposed method quantitatively outperforms recent deep learning motion correction and synthesis methods. Real motion experiments from 5 healthy subjects demonstrate the potential of the proposed method for use in a clinical environment.

CONCLUSION

A deep learning-based motion correction method for multi-contrast MRI was successfully developed, and experimental results demonstrate the validity of the proposed method.

Prospective motion detection and re-acquisition in diffusion MRI using a phase image-based method-Application to brain and tongue imaging

PURPOSE

To develop an image-based motion-robust diffusion MRI (dMRI) acquisition framework that is able to minimize motion artifacts caused by rigid and nonrigid motion, applicable to both brain and tongue dMRI.

METHODS

We developed a novel prospective motion-correction technique in dMRI using a phase image-based real-time motion-detection method (PITA-MDD) with re-acquisition of motion-corrupted images. The prospective PITA-MDD acquisition technique was tested in the brains and tongues of volunteers. The subjects were instructed to move their heads or swallow, to induce motion. Motion-detection efficacy was validated against visual inspection as the gold standard. The effect of the PITA-MDD technique on diffusion-parameter estimates was evaluated by comparing reconstructed fiber tracts using tractography with and without re-acquisition.

RESULTS

The prospective PITA-MDD technique was able to effectively and accurately detect motion-corrupted data as compared with visual inspection. Tractography results demonstrated that PITA-MDD motion detection followed by re-acquisition helps in recovering lost and misshaped fiber tracts in the brain and tongue that would otherwise be corrupted by motion and yield erroneous estimates of the diffusion tensor.

CONCLUSION

A prospective PITA-MDD technique was developed for dMRI acquisition, providing improved dMRI image quality and motion-robust diffusion estimation of the brain and tongue.

Pilot tone-based motion correction for prospective respiratory compensated cardiac cine MRI

PURPOSE

To evaluate prospective motion correction using the pilot tone (PT) as a quantitative respiratory motion signal with high temporal resolution for cardiac cine images during free breathing.

METHODS

Before cine data acquisition, a short prescan was performed, calibrating the PT to the respiratory-induced heart motion using respiratory-resolved real-time images. The calibrated PT was then applied for nearly real-time prospective motion correction of cine MRI through slice tracking (ie, updating the slice position before every readout). Additionally, in-plane motion correction was performed retrospectively also based on the calibrated PT data. The proposed method was evaluated in a moving phantom and 10 healthy volunteers.

RESULTS

The PT showed very good correlation to the phantom motion. In volunteer studies using a long-term scan over 7.96 ± 1.40 min, the mean absolute error between registered and predicted motion from the PT was 1.44 ± 0.46 mm in head-feet and 0.46 ± 0.07 mm in anterior-posterior direction. Irregular breathing could also be corrected well with the PT. The PT motion correction leads to a significant improvement of contrast-to-noise ratio by 68% (P ≤ .01) between blood pool and myocardium and sharpness of endocardium by 24% (P = .04) in comparison to uncorrected data. The image score, which refers to the cine image quality, has improved with the utilization of the proposed PT motion correction.

CONCLUSION

The proposed approach provides respiratory motion-corrected cine images of the heart with improved image quality and a high scan efficiency using the PT. The PT is independent of the MR acquisition, making this a very flexible motion-correction approach.

Prospective Motion Correction for Brain MRI Using an External Tracking System

BACKGROUND AND PURPOSE

A wide range of strategies have been developed to mitigate motion, as a major source of image quality degradation in clinical MRI. We aimed to assess the efficiency of a commercially available prospective motion correction (PMC) system in reducing motion in acquiring high-resolution 3D magnetization-prepared rapid gradient-echo (MPRAGE).

METHODS

A total of 100 patients who referred for brain MRI studies were prospectively imaged using a 3.0T scanner. 3D MPRAGE acquisition was obtained with and without application of PMC. The motion tracking system (KinetiCor Inc.) consisted of a quad camera apparatus, which tracks a specific marker on patient's head by evaluating the marker's optical pattern. The patient's head motion in 6 degrees of freedom throughout the acquisition was then incorporated into the MRI sequence, updating the image acquisition in real time based on the most recent head pose data. MPRAGE images with and without motion correction were assessed independently by two board-certified neuroradiologists using a 5-point Likert scale. Statistical analysis included kappa and Wilcoxon Rank-Sum tests.

RESULTS

Observers 1 and 2 identified nondiagnostic studies in 17.2% and 20.7% of patients (K = .78, 95% CI .70-.86) without motion correction and in 5.7% and 8% of the studies with motion correction (K = .84, 95% CI .76-.92). The number of nondiagnostic studies was significantly (P = .001) reduced from 19.5% to 5.7% after motion correction in consensus read analysis.

CONCLUSION

The described motion tracking system can be used effectively in clinical practice reducing motion artifact and improving image quality of 3D MPRAGE sequence.

Motion correction in magnetic resonance spectroscopy

In vivo proton magnetic resonance spectroscopy and spectroscopic imaging (MRS/MRSI) are valuable tools to study normal and abnormal human brain physiology. However, they are sensitive to motion, due to strong crusher gradients, long acquisition times, reliance on high magnetic field homogeneity, and particular acquisition methods such as spectral editing. The effects of motion include incorrect spatial localization, phase fluctuations, incoherent averaging, line broadening, and ultimately quantitation errors. Several retrospective methods have been proposed to correct motion-related artifacts. Recent advances in hardware also allow prospective (real-time) correction of the effects of motion, including adjusting voxel location, center frequency, and magnetic field homogeneity. This article reviews prospective and retrospective methods available in the literature and their implications for clinical MRS/MRSI. In combination, these methods can attenuate or eliminate most motion-related artifacts and facilitate the acquisition of high-quality data in the clinical research setting.

Neural correlates of head restraint: Unsolicited neuronal activation and dopamine release

To minimize motion-related distortion of reconstructed images, conventional positron emission tomography (PET) measurements of the brain inevitably require a firm and tight head restraint. While such a restraint is now a routine procedure in brain imaging, the physiological and psychological consequences resulting from the restraint have not been elucidated. To address this problem, we developed a restraint-free brain PET system and conducted PET scans under both restrained and non-restrained conditions. We examined whether head restraint during PET scans could alter brain activities such as regional cerebral blood flow (rCBF) and dopamine release along with psychological stress related to head restraint. Under both conditions, 20 healthy male participants underwent [¹⁵O]H₂O and [¹¹C]Raclopride PET scans during working memory tasks with the same PET system. Before, during, and after each PET scan, we measured physiological and psychological stress responses, including the State-Trait Anxiety Inventory (STAI) scores. Analysis of the [¹⁵O]H₂O-PET data revealed higher rCBF in regions such as the parahippocampus in the restrained condition. We found the binding potential (BP_ND) of [¹¹C]Raclopride in the putamen was significantly reduced in the restrained condition, which reflects an increase in dopamine release. Moreover, the restraint-induced change in BP_ND was correlated with a shift in the state anxiety score of the STAI, indicating that less anxiety accompanied smaller dopamine release. These results suggest that the stress from head restraint could cause unsolicited responses in brain physiology and emotional states. The restraint-free imaging system may thus be a key enabling technology for the natural depiction of the mind.

Prospective motion correction for diffusion weighted EPI of the brain using an optical markerless tracker

PURPOSE

To enable motion-robust diffusion weighted imaging of the brain using well-established imaging techniques.

METHODS

An optical markerless tracking system was used to estimate and correct for rigid body motion of the head in real time during scanning. The imaging coordinate system was updated before each excitation pulse in a single-shot EPI sequence accelerated by GRAPPA with motion-robust calibration. Full Fourier imaging was used to reduce effects of motion during diffusion encoding. Subjects were imaged while performing prescribed motion patterns, each repeated with prospective motion correction on and off.

RESULTS

Prospective motion correction with dynamic ghost correction enabled high quality DWI in the presence of fast and continuous motion within a 10° range. Images acquired without motion were not degraded by the prospective correction. Calculated diffusion tensors tolerated the motion well, but ADC values were slightly increased.

CONCLUSIONS

Prospective correction by markerless optical tracking minimizes patient interaction and appears to be well suited for EPI-based DWI of patient groups unable to remain still including those who are not compliant with markers.

Simultaneous feedback control for joint field and motion correction in brain MRI

T2*-weighted gradient-echo sequences count among the most widely used techniques in neuroimaging and offer rich magnitude and phase contrast. The susceptibility effects underlying this contrast scale with B₀, making T2*-weighted imaging particularly interesting at high field. High field also benefits baseline sensitivity and thus facilitates high-resolution studies. However, enhanced susceptibility effects and high target resolution come with inherent challenges. Relying on long echo times, T2*-weighted imaging not only benefits from enhanced local susceptibility effects but also suffers from increased field fluctuations due to moving body parts and breathing. High resolution, in turn, renders neuroimaging particularly vulnerable to motion of the head. This work reports the implementation and characterization of a system that aims to jointly address these issues. It is based on the simultaneous operation of two control loops, one for field stabilization and one for motion correction. The key challenge with this approach is that the two loops both operate on the magnetic field in the imaging volume and are thus prone to mutual interference and potential instability. This issue is addressed at the levels of sensing, timing, and control parameters. Performance assessment shows the resulting system to be stable and exhibit adequate loop decoupling, precision, and bandwidth. Simultaneous field and motion control is then demonstrated in examples of T2*-weighted in vivo imaging at 7T.

Hemodynamic Data Assimilation in a Subject-specific Circle of Willis Geometry

PURPOSE

The anatomy of the circle of Willis (CoW), the brain's main arterial blood supply system, strongly differs between individuals, resulting in highly variable flow fields and intracranial vascularization patterns. To predict subject-specific hemodynamics with high certainty, we propose a data assimilation (DA) approach that merges fully 4D phase-contrast magnetic resonance imaging (PC-MRI) data with a numerical model in the form of computational fluid dynamics (CFD) simulations.

METHODS

To the best of our knowledge, this study is the first to provide a transient state estimate for the three-dimensional velocity field in a subject-specific CoW geometry using DA. High-resolution velocity state estimates are obtained using the local ensemble transform Kalman filter (LETKF).

RESULTS

Quantitative evaluation shows a considerable reduction (up to 90%) in the uncertainty of the velocity field state estimate after the data assimilation step. Velocity values in vessel areas that are below the resolution of the PC-MRI data (e.g., in posterior communicating arteries) are provided. Furthermore, the uncertainty of the analysis-based wall shear stress distribution is reduced by a factor of 2 for the data assimilation approach when compared to the CFD model alone.

CONCLUSION

This study demonstrates the potential of data assimilation to provide detailed information on vascular flow, and to reduce the uncertainty in such estimates by combining various sources of data in a statistically appropriate fashion.

SLIMM: Slice localization integrated MRI monitoring

Functional MRI (fMRI) is extremely challenging to perform in subjects who move because subject motion disrupts blood oxygenation level dependent (BOLD) signal measurement. It has become common to use retrospective framewise motion detection and censoring in fMRI studies to eliminate artifacts arising from motion. Data censoring results in significant loss of data and statistical power unless the data acquisition is extended to acquire more data not corrupted by motion. Acquiring more data than is necessary leads to longer than necessary scan duration, which is more expensive and may lead to additional subject non-compliance. Therefore, it is well established that real-time prospective motion monitoring is crucial to ensure data quality and reduce imaging costs. In addition, real-time monitoring of motion allows for feedback to the operator and the subject during the acquisition, to enable intervention to reduce the subject motion. The most widely used form of motion monitoring for fMRI is based on volume-to-volume registration (VVR), which quantifies motion as the misalignment between subsequent volumes. However, motion is not constrained to occur only at the boundaries of volume acquisition, but instead may occur at any time. Consequently, each slice of an fMRI acquisition may be displaced by motion, and assessment of whole volume to volume motion may be insensitive to both intra-volume and inter-volume motion that is revealed by displacement of the slices. We developed the first slice-by-slice self-navigated motion monitoring system for fMRI by developing a real-time slice-to-volume registration (SVR) algorithm. Our real-time SVR algorithm, which is the core of the system, uses a local image patch-based matching criterion along with a Levenberg-Marquardt optimizer, all accelerated via symmetric multi-processing, with interleaved and simultaneous multi-slice acquisition schemes. Extensive experimental results on real motion data demonstrated that our fast motion monitoring system, named Slice Localization Integrated MRI Monitoring (SLIMM), provides more accurate motion measurements than a VVR based approach. Therefore, SLIMM offers improved online motion monitoring which is particularly important in fMRI for challenging patient populations. Real-time motion monitoring is crucial for online data quality control and assurance, for enabling feedback to the subject and the operator to act to mitigate motion, and in adaptive acquisition strategies that aim to ensure enough data of sufficient quality is acquired without acquiring excess data.

Probing in vivo cortical myeloarchitecture in humans via line-scan diffusion acquisitions at 7 T with 250-500 micron radial resolution

PURPOSE

The goal of this study was to measure diffusion signals within the cerebral cortex using the line-scan technique to achieve extremely high resolution in the radial direction (ie, perpendicular to the cortical surface) and to demonstrate the utility of these measurements for investigating laminar architecture in the living human brain.

METHODS

Line-scan diffusion data with 250-500 micron radial resolution were acquired at 7 T on 8 healthy volunteers, with each line prescribed perpendicularly to primary somatosensory cortex (S1) and primary motor cortex (M1). Apparent diffusion coefficients, fractional anisotropy values, and radiality indices were measured as a function of cortical depth.

RESULTS

In the deep layers of S1, we found evidence for high anisotropy and predominantly tangential diffusion, with low anisotropy observed in superficial S1. In M1, moderate anisotropy and predominantly radial diffusion was seen at almost all cortical depths. These patterns were consistent across subjects and were conspicuous without averaging data across different locations on the cortical sheet.

CONCLUSION

Our results are in accord with the myeloarchitecture of S1 and M1, known from prior histology studies: in S1, dense bands of tangential myelinated fibers run through the deep layers but not the superficial ones, and in M1, radial myelinated fibers are prominent at most cortical depths. This work therefore provides support for the idea that high-resolution diffusion signals, measured with the line-scan technique and receiving a boost in SNR at 7 T, may serve as a sensitive probe of in vivo laminar architecture.

Navigator-based reacquisition and estimation of motion-corrupted data: Application to multi-echo spin echo for carotid wall MRI

PURPOSE

To assess whether artifacts in multi-slice multi-echo spin echo neck imaging, thought to be caused by brief motion events such as swallowing, can be corrected by reacquiring corrupted central k-space data and estimating the remainder with parallel imaging.

METHODS

A single phase-encode line (ky = 0, phase-encode direction anteroposterior) navigator echo was used to identify motion-corrupted data and guide the online reacquisition. If motion corruption was detected in the 7 central k-space lines, they were replaced with reacquired data. Subsequently, GRAPPA reconstruction was trained on the updated central portion of k-space and then used to estimate the remaining motion-corrupted k-space data from surrounding uncorrupted data. Similar compressed sensing-based approaches have been used previously to compensate for respiration in cardiac imaging. The g-factor noise amplification was calculated for the parallel imaging reconstruction of data acquired with a 10-channel neck coil. The method was assessed in scans with 9 volunteers and 12 patients.

RESULTS

The g-factor analysis showed that GRAPPA reconstruction of 2 adjacent motion-corrupted lines causes high noise amplification; therefore, the number of 2-line estimations should be limited. In volunteer scans, median ghosting reduction of 24% was achieved with 2 adjacent motion-corrupted lines correction, and image quality was improved in 2 patient scans that had motion corruption close to the center of k-space.

CONCLUSION

Motion-corrupted echo-trains can be identified with a navigator echo. Combined reacquisition and parallel imaging estimation reduced motion artifacts in multi-slice MESE when there were brief motion events, especially when motion corruption was close to the center of k-space.

Correction of out-of-FOV motion artifacts using convolutional neural network

PURPOSE

Subject motion during MRI scan can result in severe degradation of image quality. Existing motion correction algorithms rely on the assumption that no information is missing during motions. However, this assumption does not hold when out-of-FOV motion happens. Currently available algorithms are not able to correct for image artifacts introduced by out-of-FOV motion. The purpose of this study is to demonstrate the feasibility of incorporating convolutional neural network (CNN) derived prior image into solving the out-of-FOV motion problem.

METHODS AND MATERIALS

A modified U-net network was proposed to correct out-of-FOV motion artifacts by incorporating motion parameters into the loss function. A motion model based data fidelity term was applied in combination with the CNN prediction to further improve the motion correction performance. We trained the CNN on 1113 MPRAGE images with simulated oscillating and sudden motion trajectories, and compared our algorithm to a gradient-based autofocusing (AF) algorithm in both 2D and 3D images. Additional experiment was performed to demonstrate the feasibility of transferring the networks to different dataset. We also evaluated the robustness of this algorithm by adding Gaussian noise to the motion parameters. The motion correction performance was evaluated using mean square error (NMSE), peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM).

RESULTS

The proposed algorithm outperformed AF-based algorithm for both 2D (NMSE: 0.0066 ± 0.0009 vs 0.0141 ± 0.008, P < .01; PSNR: 29.60 ± 0.74 vs 21.71 ± 0.27, P < .01; SSIM: 0.89 ± 0.014 vs 0.73 ± 0.004, P < .01) and 3D imaging (NMSE: 0.0067 ± 0.0008 vs 0.070 ± 0.021, P < .01; PSNR: 32.40 ± 1.63 vs 22.32 ± 2.378, P < .01; SSIM: 0.89 ± 0.01 vs 0.62 ± 0.03, P < .01). Robust reconstruction was achieved with 20% data missed due to the out-of-FOV motion.

CONCLUSION

In conclusion, the proposed CNN-based motion correction algorithm can significantly reduce out-of-FOV motion artifacts and achieve better image quality compared to AF-based algorithm.

Retrospective Brain Motion Correction in Glutamate Chemical Exchange Saturation Transfer (GluCEST) MRI

PURPOSE

To evaluate the feasibility of motion correction in glutamate chemical exchange saturation transfer (GluCEST) imaging, using a rat model of epileptic seizure.

PROCEDURES

Epileptic seizure was induced in six male Wistar rats by intraperitoneal injection of kainic acid (KA). CEST data were obtained using a 7.0 T Bruker MRI scanner before and 3 h after KA injection. Retrospective motion correction was performed in CEST images using a gradient-based motion correction (GradMC) algorithm. GluCEST signals in the hippocampal regions were quantitatively evaluated with and without motion correction.

RESULTS

Calculated GluCEST signals differed significantly between the pre-KA injection group, regardless of motion-correction implementation, and the post-KA injection group with motion correction (3.662 ± 1.393 % / 3.726 ± 1.982 % for pre-KA injection group with/without motion correction vs. 6.996 ± 1.684 % for post-KA injection group with motion correction; all P < 0.05).

CONCLUSIONS

Our results clearly show that GradMC can be used in CEST imaging for efficient correction of seizure-like motion. The GradMC can be further implemented in various CEST imaging techniques to increase the accuracy of analysis.

Activity or connectivity? A randomized controlled feasibility study evaluating neurofeedback training in Huntington's disease

Non-invasive methods, such as neurofeedback training, could support cognitive symptom management in Huntington’s disease by targeting brain regions whose function is impaired. The aim of our single-blind, sham-controlled study was to collect rigorous evidence regarding the feasibility of neurofeedback training in Huntington’s disease by examining two different methods, activity and connectivity real-time functional MRI neurofeedback training. Thirty-two Huntington’s disease gene-carriers completed 16 runs of neurofeedback training, using an optimized real-time functional MRI protocol. Participants were randomized into four groups, two treatment groups, one receiving neurofeedback derived from the activity of the supplementary motor area, and another receiving neurofeedback based on the correlation of supplementary motor area and left striatum activity (connectivity neurofeedback training), and two sham control groups, matched to each of the treatment groups. We examined differences between the groups during neurofeedback training sessions and after training at follow-up sessions. Transfer of training was measured by measuring the participants’ ability to upregulate neurofeedback training target levels without feedback (near transfer), as well as by examining change in objective, a priori defined, behavioural measures of cognitive and psychomotor function (far transfer) before and at 2 months after training. We found that the treatment group had significantly higher neurofeedback training target levels during the training sessions compared to the control group. However, we did not find robust evidence of better transfer in the treatment group compared to controls, or a difference between the two neurofeedback training methods. We also did not find evidence in support of a relationship between change in cognitive and psychomotor function and learning success. We conclude that although there is evidence that neurofeedback training can be used to guide participants to regulate the activity and connectivity of specific regions in the brain, evidence regarding transfer of learning and clinical benefit was not robust.

A Reconfigurable Platform for Magnetic Resonance Data Acquisition and Processing

Developments in magnetic resonance imaging (MRI) in the last decades show a trend towards a growing number of array coils and an increasing use of a wide variety of sensors. Associated cabling and safety issues have been addressed by moving data acquisition closer to the coil. However, with the increasing number of radio-frequency (RF) channels and trend towards higher acquisition duty-cycles, the data amount is growing, which poses challenges for throughput and data handling. As it is becoming a limitation, early compression and preprocessing is becoming ever more important. Additionally, sensors deliver diverse data, which require distinct and often low-latency processing for run-time updates of scanner operation. To address these challenges, we propose the transition to reconfigurable hardware with an application tailored assembly of interfaces and real-time processing resources. We present an integrated solution based on a system-on-chip (SoC), which offers sufficient throughput and hardware-based parallel processing power for very challenging applications. It is equipped with fiber-optical modules serving as versatile interfaces for modular systems with in-field operation. We demonstrate the utility of the platform on the example of concurrent imaging and field sensing with hardware-based coil compression and trajectory extraction. The preprocessed data are then used in expanded encoding model based image reconstruction of single-shot and segmented spirals as used in time-series and anatomical imaging respectively.

Anatomy of brain lesions after stroke predicts effectiveness of mirror therapy

To improve clinical outcome, one longstanding goal in treating stroke patients has been an individual therapy based on functional and anatomical knowledge of the single patient. Therefore, in this study brain imaging of 36 chronic stroke patients was analyzed to identify parameters predicting clinical recovery. T1-weighted MRI was acquired to assess the lesion; functional MRI was used to visualize existing resources; DTI for the integrity of the corticospinal tract (CST) and long association tracts. These data were related to the clinical course. All patients were treated intensively with the mirror therapy (MT) only. After the training period, we analyzed which patient's feature would predict a beneficial course. Patients as a group improved after MT, but according to the fMRI activation of primary sensorimotor cortex (SMC), they could be divided in two groups with very diverging clinical outcome: those with ipsilesional SMC activation showed a noticeable increase of clinical scores, accompanied with ipsilesional activation in the frontal projection areas of the dorsal and ventral streams during action observation in fMRI. Those with contralesional SMC activation had lesions affecting both the dorsal and ventral stream and did not benefit from MT. The outcome for this therapy was not related to affection of CST. This study demonstrates that only in patients in which dorsal and ventral streams are not affected and therefore an interaction between these streams in post- and prerolandic regions is possible, MT can induce clinical improvement. Consequently, knowledge of the anatomical lesion can predict the beneficial course of MT.

A within-coil optical prospective motion-correction system for brain imaging at 7T

PURPOSE

Motion artifact limits the clinical translation of high-field MR. We present an optical prospective motion correction system for 7 Tesla MRI using a custom-built, within-coil camera to track an optical marker mounted on a subject.

METHODS

The camera was constructed to fit between the transmit-receive coils with direct line of sight to a forehead-mounted marker, improving upon prior mouthpiece work at 7 Tesla MRI. We validated the system by acquiring a 3D-IR-FSPGR on a phantom with deliberate motion applied. The same 3D-IR-FSPGR and a 2D gradient echo were then acquired on 7 volunteers, with/without deliberate motion and with/without motion correction. Three neuroradiologists blindly assessed image quality. In 1 subject, an ultrahigh-resolution 2D gradient echo with 4 averages was acquired with motion correction. Four single-average acquisitions were then acquired serially, with the subject allowed to move between acquisitions. A fifth single-average 2D gradient echo was acquired following subject removal and reentry.

RESULTS

In both the phantom and human subjects, deliberate and involuntary motion were well corrected. Despite marked levels of motion, high-quality images were produced without spurious artifacts. The quantitative ratings confirmed significant improvements in image quality in the absence and presence of deliberate motion across both acquisitions (P < .001). The system enabled ultrahigh-resolution visualization of the hippocampus during a long scan and robust alignment of serially acquired scans with interspersed movement.

CONCLUSION

We demonstrate the use of a within-coil camera to perform optical prospective motion correction and ultrahigh-resolution imaging at 7 Tesla MRI. The setup does not require a mouthpiece, which could improve accessibility of motion correction during 7 Tesla MRI exams.

The dot-compartment revealed? Diffusion MRI with ultra-strong gradients and spherical tensor encoding in the living human brain

The so-called “dot-compartment” is conjectured in diffusion MRI to represent small spherical spaces, such as cell bodies, in which the diffusion is restricted in all directions. Previous investigations inferred its existence from data acquired with directional diffusion encoding which does not permit a straightforward separation of signals from ‘sticks’ (axons) and signals from ‘dots’. Here we combine isotropic diffusion encoding with ultra-strong diffusion gradients (240 ​mT/m) to achieve high diffusion-weightings with high signal to noise ratio, while suppressing signal arising from anisotropic water compartments with significant mobility along at least one axis (e.g., axons). A dot-compartment, defined to have apparent diffusion coefficient equal to zero and no exchange, would result in a non-decaying signal at very high b-values (b≳7000s/mm2). With this unique experimental setup, a residual yet slowly decaying signal above the noise floor for b-values as high as 15000s/mm2 was seen clearly in the cerebellar grey matter (GM), and in several white matter (WM) regions to some extent. Upper limits of the dot-signal-fraction were estimated to be 1.8% in cerebellar GM and 0.5% in WM. By relaxing the assumption of zero diffusivity, the signal at high b-values in cerebellar GM could be represented more accurately by an isotropic water pool with a low apparent diffusivity of 0.12 μm2/ms and a substantial signal fraction of 9.7%. The T2 of this component was estimated to be around 61ms. This remaining signal at high b-values has potential to serve as a novel and simple marker for isotropically-restricted water compartments in cerebellar GM.

•

The “dot-compartment” is conjectured in diffusion MRI to represent e.g. cell bodies.

•

We combine isotropic encoding with ultra-strong gradients to study the dot-compartment.

•

A slowly decaying signal for high b-values was seen in cerebellar GM.

•

An apparent diffusivity of 0.12 and signal fraction of 9.7% were estimated.

•

The signal could serve as a novel and simple marker for spherical compartments.

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.

Resting State fMRI: Going Through the Motions

Resting state functional magnetic resonance imaging (rs-fMRI) has become an indispensable tool in neuroscience research. Despite this, rs-fMRI signals are easily contaminated by artifacts arising from movement of the head during data collection. The artifacts can be problematic even for motions on the millimeter scale, with complex spatiotemporal properties that can lead to substantial errors in functional connectivity estimates. Effective correction methods must be employed, therefore, to distinguish true functional networks from motion-related noise. Research over the last three decades has produced numerous correction methods, many of which must be applied in combination to achieve satisfactory data quality. Subject instruction, training, and mild restraints are helpful at the outset, but usually insufficient. Improvements come from applying multiple motion correction algorithms retrospectively after rs-fMRI data are collected, although residual artifacts can still remain in cases of elevated motion, which are especially prevalent in patient populations. Although not commonly adopted at present, “real-time” correction methods are emerging that can be combined with retrospective methods and that promise better correction and increased rs-fMRI signal sensitivity. While the search for the ideal motion correction protocol continues, rs-fMRI research will benefit from good disclosure practices, such as: (1) reporting motion-related quality control metrics to provide better comparison between studies; and (2) including motion covariates in group-level analyses to limit the extent of motion-related confounds when studying group differences.

Retrospective correction of head motion using measurements from an electromagnetic tracker

PURPOSE

To investigate the feasibility of using an electromagnetic (EM) tracker to estimate rigid body head motion parameters, and using these measurements to retrospectively reduce motion artifacts.

THEORY AND METHODS

A clinically used MPRAGE sequence was modified to measure motion using the EM tracking system once per repetition time. A retrospective k-space based motion correction algorithm that corrects for phase ramps (translation in image domain) and rotation of 3D k-space (rotation in image domain) was developed, using the parameters recorded using an EM tracker. The accuracy of the EM tracker for the purpose of motion measurement and correction was tested in phantoms, volunteers, and pediatric patients.

RESULTS

Position localization was accurate to the order of 200 microns compared with registration localization in a phantom study. The quality of reconstructed images was assessed by computing the root mean square error, the structural similarity metric and average edge strength. Image quality improved consistently when motion correction was applied in both volunteer scans with deliberate head motion and in pediatric patient scans. In patients, the average edge strength improved significantly with retrospective motion correction, compared with images with no correction applied.

CONCLUSIONS

EM tracking was effective in measuring head motion in the MRI scanner with high accuracy, and enabled retrospective reconstruction to improve image quality by reducing motion artifacts.

Combining Prospective Acquisition CorrEction (PACE) with retrospective correction to reduce motion artifacts in resting state fMRI data

BACKGROUND

Head movement in the scanner causes spurious signal changes in the blood-oxygen-level-dependent (BOLD) signal, confounding resting state functional connectivity (RSFC) estimates obtained from functional magnetic resonance imaging (fMRI). We examined the effectiveness of Prospective Acquisition CorrEction (PACE) in reducing motion artifacts in BOLD data.

METHODS

Using PACE-corrected RS-fMRI data obtained from 44 subjects and subdividing them into low- and high-motion cohorts, we investigated voxel-wise motion-BOLD relationships, the distance-dependent functional connectivity artifact and the correlation between head motion and connectivity metrics such as posterior cingulate seed-based connectivity and network degree centrality.

RESULTS

Our results indicate that, when PACE is used in combination with standard retrospective motion correction strategies, it provides two principal advantages over conventional echo-planar imaging (EPI) RS-fMRI data: (a) PACE was effective in eliminating significant negative motion-BOLD relationships, shown to be associated with signal dropouts caused by head motion, and (b) Censoring with a lower threshold (framewise displacement >0.5 mm) and a smaller window around the motion corrupted time point provided qualitatively equivalent reductions in the motion artifact with PACE when compared to a more conservative threshold of 0.2 mm required with conventional EPI data.

CONCLUSIONS

PACE when used in conjunction with retrospective motion correction methods including nuisance signal and motion parameter regression, and censoring, did prove effective in almost eliminating head motion artifacts, even with a lower censoring threshold. Use of a lower censoring threshold could provide substantial savings in data that would otherwise be lost to censoring. Three-dimensional PACE has negligible overhead in terms of scan time, sequence modifications or additional and hence presents an attractive option for head motion correction in high-throughput resting-state BOLD imaging.

Prospective motion and B0 shim correction for MR spectroscopy in human brain at 7T

PURPOSE

To demonstrate feasibility and performance of prospective motion and B₀ shim correction for MRS in human brain at 7T.

METHODS

Prospective motion correction using an optical camera and linear B₀ shim correction using FASTMAP-like navigators were implemented into a semi-LASER sequence. The effect of motion on spectral quality was assessed without and with prospective correction in prefrontal cortex in 11 subjects.

RESULTS

Without prospective motion and shim correction, motion resulted in considerable degradation of MR spectra (broader linewidth, lower signal-to-noise ratio, degraded water suppression). With prospective motion and shim correction, spectral quality remained excellent despite motion. Prospective motion correction alone was not sufficient to prevent degradation of spectral quality.

CONCLUSION

Prospective motion and B₀ shim correction is feasible at 7T and should help improve the robustness of MRS, particularly in motion-prone populations.

A Wireless Radio Frequency Triggered Acquisition Device (WRAD) for Self-Synchronised Measurements of the Rate of Change of the MRI Gradient Vector Field for Motion Tracking

In this paper, we present a device that is capable of wireless synchronization to the MRI pulse sequence time frame with sub-microsecond precision. This is achieved by detecting radio frequency pulses in the parent pulse sequence using a small resonant circuit. The device incorporates a 3-axis pickup coil, constructed using conventional printed circuit board (PCB) manufacturing techniques, to measure the rate of change of the gradient waveforms with respect to time. Using Maxwell's equations, assuming negligible rates of change of curl and divergence, a model of the expected gradient derivative (slew) vector field is presented. A 3-axis Hall effect magnetometer allows for the measurement of the direction of the static magnetic field in the device co-ordinate frame. By combining the magnetometer measurement with the pickup coil voltages and slew vector field model, the orientation and position can be determined to within a precision of 0.1 degrees and 0.1 mm, respectively, using a pulse series lasting 880 μs . The gradient pulses are designed to be sinusoidal, enabling the detection of a phase shift between the time frame of the pickup coil digitization circuit and the gradient amplifiers. The signal processing is performed by a low power micro-controller on the device and the results are transmitted out of the scanner bore using a low latency 2.4 GHz radio link. The device identified an unexpected 40 kHz oscillation relating to the pulse width modulation frequency of the gradient amplifiers that is predominantly in the direction of the static magnetic field. The proposed wireless radio frequency triggered acquisition device enables users to probe the scanner gradient slew vector field with minimal hardware set-up and shows promise for the future developments in the prospective motion correction.

Prospective motion correction in functional MRI using simultaneous multislice imaging and multislice-to-volume image registration

The sensitivity to subject motion is one of the major challenges in functional MRI (fMRI) studies in which a precise alignment of images from different time points is required to allow reliable quantification of brain activation throughout the scan. Especially the long measurement times and laborious fMRI tasks add to the amount of subject motion found in typical fMRI measurements, even when head restraints are used. In case of moving subjects, prospective motion correction can maintain the relationship between spatial image information and subject anatomy by constantly adapting the image slice positioning to follow the subject in real time. Image-based prospective motion correction is well-established in fMRI studies and typically computes the motion estimates based on a volume-to-volume image registration, resulting in low temporal resolution. This study combines fMRI using simultaneous multislice imaging with multislice-to-volume-based image registration to allow sub-TR motion detection with subsequent real-time adaption of the imaging system. Simultaneous multislice imaging is widely used in fMRI studies and, together with multislice-to-volume-based image registration algorithms, enables computing suitable motion states after only a single readout by registering the simultaneously excited slices to a reference volume acquired at the start of the measurement. The technique is evaluated in three human BOLD fMRI studies (n = 1, 5, and 1) to explore different aspects of the method. It is compared to conventional, volume-to-volume-based prospective motion correction as well as retrospective motion correction methods. Results show a strong reduction in retrospectively computed residual motion parameters of up to 50% when comparing the two prospective motion correction techniques. An analysis of temporal signal-to-noise ratio as well as brain activation results shows high consistency between the results before and after additional retrospective motion correction when using the proposed technique, indicating successful prospective motion correction. The comparison of absolute tSNR values does not show an improvement compared to using retrospective motion correction alone. However, the improved temporal resolution may provide improved tSNR in the presence of more exaggerated intra-volume motion.

Toward "plug and play" prospective motion correction for MRI by combining observations of the time varying gradient and static vector fields

PURPOSE

The efficacy of a Wireless Radio frequency triggered Acquisition Device (WRAD) is evaluated for high frequency (50 Hz) prospective motion correction in a 3-dimensional spoiled gradient echo pulse sequence.

METHODS

The device measures the rate of change in the gradient vector fields (slew) using a 3-dimensional assembly of Printed Circuit Board (PCB) inductors and the direction of the static magnetic field using a 3-axis Hall effect magnetometer. The slew vector encoding is highly efficient, because the Maxwell-term position encoding is observable, allowing overconstrained pose measurement using 3 sinusoidal gradient pulses lasting 880 μs. Since small offsets in the magnetometer can introduce bias into the pose estimates, sensor/system biases are tracked using a lightweight Kalman filter. The only calibration required is determining a geometric scaling factor for the pickup coils, which is specific to the device and will therefore be valid in any scanner.

RESULTS

The device was used to perform prospective motion correction in 3 subjects, resulting in an increase in Average Edge Strength (AES) for involuntary and deliberate motion.

CONCLUSIONS

The WRAD is simple to set up and use, with well-defined measurement variance. This could enable "plug and play" prospective motion correction if pulse sequence independence is achieved.

Quantification of patellofemoral cartilage deformation and contact area changes in response to static loading via high-resolution MRI with prospective motion correction

BACKGROUND

Higher-resolution MRI of the patellofemoral cartilage under loading is hampered by subject motion since knee flexion is required during the scan.

PURPOSE

To demonstrate robust quantification of cartilage compression and contact area changes in response to in situ loading by means of MRI with prospective motion correction and regularized image postprocessing.

STUDY TYPE

Cohort study.

SUBJECTS

Fifteen healthy male subjects.

FIELD STRENGTH

3 T.

SEQUENCE

Spoiled 3D gradient-echo sequence augmented with prospective motion correction based on optical tracking. Measurements were performed with three different loads (0/200/400 N).

ASSESSMENT

Bone and cartilage segmentation was performed manually and regularized with a deep-learning approach. Average patellar and femoral cartilage thickness and contact area were calculated for the three loading situations. Reproducibility was assessed via repeated measurements in one subject.

STATISTICAL TESTS

Comparison of the three loading situations was performed by Wilcoxon signed-rank tests.

RESULTS

Regularization using a deep convolutional neural network reduced the variance of the quantified relative load-induced changes of cartilage thickness and contact area compared to purely manual segmentation (average reduction of standard deviation by ∼50%) and repeated measurements performed on the same subject demonstrated high reproducibility of the method. For the three loading situations (0/200/400 N), the patellofemoral cartilage contact area as well as the mean patellar and femoral cartilage thickness were significantly different from each other (P < 0.05). While the patellofemoral cartilage contact area increased under loading (by 14.5/19.0% for loads of 200/400 N), patellar and femoral cartilage thickness exhibited a load-dependent thickness decrease (patella: -4.4/-7.4%, femur: -3.4/-7.1% for loads of 200/400 N).

DATA CONCLUSION

MRI with prospective motion correction enables quantitative evaluation of patellofemoral cartilage deformation and contact area changes in response to in situ loading. Regularizing the manual segmentations using a neural network enables robust quantification of the load-induced changes.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1561-1570.

Markerless high-frequency prospective motion correction for neuroanatomical MRI

PURPOSE

To integrate markerless head motion tracking with prospectively corrected neuroanatomical MRI sequences and to investigate high-frequency motion correction during imaging echo trains.

METHODS

A commercial 3D surface tracking system, which estimates head motion by registering point cloud reconstructions of the face, was used to adapt the imaging FOV based on head movement during MPRAGE and T₂ SPACE (3D variable flip-angle turbo spin-echo) sequences. The FOV position and orientation were updated every 6 lines of k-space (< 50 ms) to enable "within-echo-train" prospective motion correction (PMC). Comparisons were made with scans using "before-echo-train" PMC, in which the FOV was updated only once per TR, before the start of each echo train (ET). Continuous-motion experiments with phantoms and in vivo were used to compare these high-frequency and low-frequency correction strategies. MPRAGE images were processed with FreeSurfer to compare estimates of brain structure volumes and cortical thickness in scans with different PMC.

RESULTS

The median absolute pose differences between markerless tracking and MR image registration were 0.07/0.26/0.15 mm for x/y/z translation and 0.06º/0.02º/0.12° for rotation about x/y/z. The PMC with markerless tracking substantially reduced motion artifacts. The continuous-motion experiments showed that within-ET PMC, which minimizes FOV encoding errors during ETs that last over 1 second, reduces artifacts compared with before-ET PMC. T₂ SPACE was found to be more sensitive to motion during ETs than MPRAGE. FreeSurfer morphometry estimates from within-ET PMC MPRAGE images were the most accurate.

CONCLUSION

Markerless head tracking can be used for PMC, and high-frequency within-ET PMC can reduce sensitivity to motion during long imaging ETs.

Neu3CA-RT: A framework for real-time fMRI analysis

Real-time functional magnetic resonance imaging (rtfMRI) allows visualisation of ongoing brain activity of the subject in the scanner. Denoising algorithms aim to rid acquired data of confounding effects, enhancing the blood oxygenation level-dependent (BOLD) signal. Further image processing and analysis methods, like general linear models (GLM) or multivariate analysis, then present application-specific information to the researcher. These processes are typically applied to regions of interest but, increasingly, rtfMRI techniques extract and classify whole brain functional networks and dynamics as correlates for brain states or behaviour, particularly in neuropsychiatric and neurocognitive disorders. We present Neu³CA-RT: a Matlab-based rtfMRI analysis framework aiming to advance scientific knowledge on real-time cognitive brain activity and to promote its translation into clinical practice. Design considerations are listed based on reviewing existing rtfMRI approaches. The toolbox integrates established SPM preprocessing routines, real-time GLM mapping of fMRI data to a basis set of spatial brain networks, correlation of activity with 50 behavioural profiles from the BrainMap database, and an intuitive user interface. The toolbox is demonstrated in a task-based experiment where a subject executes visual, auditory and motor tasks inside a scanner. In three out of four experiments, resulting behavioural profiles agreed with the expected brain state.

Real-time simultaneous shim and motion measurement and correction in glycoCEST MRI using double volumetric navigators (DvNavs)

PURPOSE

CEST MRI allows for indirect detection of molecules with exchangeable protons, measured as a reduction in water signal because of continuous transfer of saturated protons. CEST requires saturation pulses on the order of a second, as well as repeated acquisitions at different offset frequencies. The resulting extended scan time makes CEST susceptible to subject motion, which introduces field inhomogeneity, shifting offset frequencies and causing distortions in CEST spectra that resemble true CEST effects. This is a particular problem for molecules that resonate close to water, such as hydroxyl group in glycogen. To address this, a technique for real-time measurement and correction of motion and field inhomogeneity is proposed.

METHODS

A CEST sequence was modified to include double volumetric navigators (DvNavs) for real-time simultaneous motion and shim correction. Phantom tests were conducted to investigate the effects of motion and shim changes on CEST quantification and to validate the accuracy of DvNav motion and shim estimates. To evaluate DvNav shim and motion correction in vivo, acquisitions including 5 experimental conditions were performed in the calf muscle of 2 volunteers.

RESULTS

Phantom data show that DvNav-CEST accurately estimates frequency and linear gradient changes because of motion and corrects resulting image distortions. In addition, DvNav-CEST improves CEST quantification in vivo in the presence of motion.

CONCLUSION

The proposed technique allows for real-time simultaneous motion and shim correction with no additional scanning time, enabling accurate CEST quantification even in the presence of motion and field inhomogeneity.

Exploring the sensitivity of magnetic resonance fingerprinting to motion

PURPOSE

To explore the motion sensitivity of magnetic resonance fingerprinting (MRF), we performed experiments with different types of motion at various time intervals during multiple scans. Additionally, we investigated the possibility to correct the motion artifacts based on redundancy in MRF data.

METHODS

A radial version of the FISP-MRF sequence was used to acquire one transverse slice through the brain. Three subjects were instructed to move in different patterns (in-plane rotation, through-plane wiggle, complex movements, adjust head position, and pretend itch) during different time intervals. The potential to correct motion artifacts in MRF by removing motion-corrupted data points from the fingerprints and dictionary was evaluated.

RESULTS

Morphological structures were well preserved in multi-parametric maps despite subject motion. Although the bulk T1 values were not significantly affected by motion, fine structures were blurred when in-plane motion was present during the first part of the scan. On the other hand, T2 values showed a considerable deviation from the motion-free results, especially when through-plane motion was present in the middle of the scan (-44% on average). Explicitly removing the motion-corrupted data from the scan partially restored the T2 values (-10% on average).

CONCLUSION

Our experimental results showed that different kinds of motion have distinct effects on the precision and effective resolution of the parametric maps measured with MRF. Although MRF-based acquisitions can be relatively robust to motion effects occurring at the beginning or end of the sequence, relying on redundancy in the data alone is not sufficient to assure the accuracy of the multi-parametric maps in all cases.

Pros and cons of ultra-high-field MRI/MRS for human application

Magnetic resonance imaging and spectroscopic techniques are widely used in humans both for clinical diagnostic applications and in basic research areas such as cognitive neuroimaging. In recent years, new human MR systems have become available operating at static magnetic fields of 7 T or higher (≥300 MHz proton frequency). Imaging human-sized objects at such high frequencies presents several challenges including non-uniform radiofrequency fields, enhanced susceptibility artifacts, and higher radiofrequency energy deposition in the tissue. On the other side of the scale are gains in signal-to-noise or contrast-to-noise ratio that allow finer structures to be visualized and smaller physiological effects to be detected. This review presents an overview of some of the latest methodological developments in human ultra-high field MRI/MRS as well as associated clinical and scientific applications. Emphasis is given to techniques that particularly benefit from the changing physical characteristics at high magnetic fields, including susceptibility-weighted imaging and phase-contrast techniques, imaging with X-nuclei, MR spectroscopy, CEST imaging, as well as functional MRI. In addition, more general methodological developments such as parallel transmission and motion correction will be discussed that are required to leverage the full potential of higher magnetic fields, and an overview of relevant physiological considerations of human high magnetic field exposure is provided.

Cognitive neuroscience using wearable magnetometer arrays: Non-invasive assessment of language function

Recent work has demonstrated that Optically Pumped Magnetometers (OPMs) can be utilised to create a wearable Magnetoencephalography (MEG) system that is motion robust. In this study, we use this system to map eloquent cortex using a clinically validated language lateralisation paradigm (covert verb generation: 120 trials, ∼10 min total duration) in healthy adults (n = 3). We show that it is possible to lateralise and localise language function on a case by case basis using this system. Specifically, we show that at a sensor and source level we can reliably detect a lateralising beta band (15-30 Hz) desynchronization in all subjects. This is the first study of human cognition using OPMs and not only highlights this technology's utility as tool for (developmental) cognitive neuroscience but also its potential to contribute to surgical planning via mapping of eloquent cortex, especially in young children.

Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects

The Human Connectome Projects in Development (HCP-D) and Aging (HCP-A) are two large-scale brain imaging studies that will extend the recently completed HCP Young-Adult (HCP-YA) project to nearly the full lifespan, collecting structural, resting-state fMRI, task-fMRI, diffusion, and perfusion MRI in participants from 5 to 100+ years of age. HCP-D is enrolling 1300+ healthy children, adolescents, and young adults (ages 5-21), and HCP-A is enrolling 1200+ healthy adults (ages 36-100+), with each study collecting longitudinal data in a subset of individuals at particular age ranges. The imaging protocols of the HCP-D and HCP-A studies are very similar, differing primarily in the selection of different task-fMRI paradigms. We strove to harmonize the imaging protocol to the greatest extent feasible with the completed HCP-YA (1200+ participants, aged 22-35), but some imaging-related changes were motivated or necessitated by hardware changes, the need to reduce the total amount of scanning per participant, and/or the additional challenges of working with young and elderly populations. Here, we provide an overview of the common HCP-D/A imaging protocol including data and rationales for protocol decisions and changes relative to HCP-YA. The result will be a large, rich, multi-modal, and freely available set of consistently acquired data for use by the scientific community to investigate and define normative developmental and aging related changes in the healthy human brain.

Integrated radio-frequency/wireless coil design for simultaneous MR image acquisition and wireless communication

PURPOSE

An innovative radio-frequency (RF) coil design that allows RF currents both at the Larmor frequency and in a wireless communication band to flow on the same coil is proposed to enable simultaneous MRI signal reception and wireless data transfer, thereby minimizing the number of wired connections in the scanner without requiring any modifications or additional hardware within the scanner bore.

METHODS

As a first application, the proposed integrated RF/wireless coil design was further combined with an integrated RF/shim coil design to perform not only MR image acquisition and wireless data transfer, but also localized B₀ shimming with a single coil. Proof-of-concept phantom experiments were conducted with such a coil to demonstrate its ability to simultaneously perform these three functions, while maintaining the RF performance, wireless data integrity, and B₀ shimming performance.

RESULTS

Performing wirelessly controlled shimming of localized B₀ inhomogeneities with the coil substantially reduced the B₀ root-mean-square error (>70%) and geometric distortions in echo-planar images without degrading the image quality, signal-to-noise ratio (<1.7%), or wireless data throughput (maximum variance = 0.04 Mbps) of the coil.

CONCLUSIONS

The RF/wireless coil design can provide a solution for wireless data transfer that can be easily integrated into existing MRI scanners for a variety of applications.

Robust Motion Correction Strategy for Structural MRI in Unsedated Children Demonstrated with Three-dimensional Radial MPnRAGE

Purpose To develop and evaluate a retrospective method to minimize motion artifacts in structural MRI. Materials and Methods The motion-correction strategy was developed for three-dimensional radial data collection and demonstrated with MPnRAGE, a technique that acquires high-resolution volumetric magnetization-prepared rapid gradient-echo, or MPRAGE, images with multiple tissue contrasts. Forty-four pediatric participants (32 with autism spectrum disorder [mean age ± standard deviation, 13 years ± 3] and 12 age-matched control participants [mean age, 12 years ± 3]) were imaged without sedation. Images with and images without retrospective motion correction were scored by using a Likert scale (0-4 for unusable to excellent) by two experienced neuroradiologists. The Tenengrad metric (a reference-free measure of image sharpness) and statistical analyses were performed to determine the effects of performing retrospective motion correction. Results MPnRAGE T1-weighted images with retrospective motion correction were all judged to have good or excellent quality. In some cases, retrospective motion correction improved the image quality from unusable (Likert score of 0) to good (Likert score of 3). Overall, motion correction improved mean Likert scores from 3.0 to 3.8 and reduced standard deviations from 1.1 to 0.4. Image quality was significantly improved with motion correction (Mann-Whitney U test; P < .001). Intraclass correlation coefficients for absolute agreement of Tenengrad scores with reviewers 1 and 2 were 0.92 and 0.88 (P < .0005 for both), respectively. In no cases did the retrospective motion correction induce severe image degradation. Conclusion Retrospective motion correction of MPnRAGE data were shown to be highly effective for consistently improving image quality of T1-weighted MRI in unsedated pediatric participants, while also enabling multiple tissue contrasts to be reconstructed for structural analysis. © RSNA, 2018 Online supplemental material is available for this article.

Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T

In MRI, subject motion results in image artifacts. High-resolution 3D scans, like MPRAGE, are particularly susceptible to motion because of long scan times and acquisition of data over multiple-shots. Such motion related artifacts have been shown to cause a bias in cortical measures extracted from segmentation of high-resolution MPRAGE images. Prospective motion correction (PMC) techniques have been developed to help mitigate artifacts due to subject motion. In this work, high-resolution MPRAGE images are acquired during intentional head motion to evaluate the effectiveness of navigator-based PMC techniques to improve both the accuracy and reproducibility of cortical morphometry measures obtained from image segmentation. The contribution of reacquiring segments of k-space affected by motion to the overall performance of PMC is assessed. Additionally, the effect of subject motion on subcortical structure volumes is investigated. In the presence of head motion, navigator-based PMC is shown to improve both the accuracy and reproducibility of cortical and subcortical measures. It is shown that reacquiring segments of k-space data that are corrupted by motion is an essential part of navigator-based PMC performance. Subcortical structure volumes are not affected by motion in the same way as cortical measures; there is not a consistent underestimation.

Markerless motion estimation for motion-compensated clinical brain imaging

Motion-compensated brain imaging can dramatically reduce the artifacts and quantitative degradation associated with voluntary and involuntary subject head motion during positron emission tomography (PET), single photon emission computed tomography (SPECT) and computed tomography (CT). However, motion-compensated imaging protocols are not in widespread clinical use for these modalities. A key reason for this seems to be the lack of a practical motion tracking technology that allows for smooth and reliable integration of motion-compensated imaging protocols in the clinical setting. We seek to address this problem by investigating the feasibility of a highly versatile optical motion tracking method for PET, SPECT and CT geometries. The method requires no attached markers, relying exclusively on the detection and matching of distinctive facial features. We studied the accuracy of this method in 16 volunteers in a mock imaging scenario by comparing the estimated motion with an accurate marker-based method used in applications such as image guided surgery. A range of techniques to optimize performance of the method were also studied. Our results show that the markerless motion tracking method is highly accurate (<2 mm discrepancy against a benchmarking system) on an ethnically diverse range of subjects and, moreover, exhibits lower jitter and estimation of motion over a greater range than some marker-based methods. Our optimization tests indicate that the basic pose estimation algorithm is very robust but generally benefits from rudimentary background masking. Further marginal gains in accuracy can be achieved by accounting for non-rigid motion of features. Efficiency gains can be achieved by capping the number of features used for pose estimation provided that these features adequately sample the range of head motion encountered in the study. These proof-of-principle data suggest that markerless motion tracking is amenable to motion-compensated brain imaging and holds good promise for a practical implementation in clinical PET, SPECT and CT systems.