Patient motion during an MRI exam can result in major degradation of image quality, and is of increasing concern due to the aging population and its associated diseases. This work presents a general strategy for real-time, intraimage compensation of rigidbody motion that is compatible with multiple imaging sequences. Image quality improvements are established for structural brain MRI acquired during volunteer motion. A headband integrated with three active markers is secured to the forehead. Prospective correction is achieved by interleaving a rapid track-and-update module into the imaging sequence. For every repetition of this module, a short tracking pulse-sequence remeasures the marker positions; during head motion, the rigid-body transformation that realigns the markers to their initial positions is fed back to adaptively update the image-plane-maintaining it at a fixed orientation relative to the head-before the next imaging segment of k-space is acquired. In cases of extreme motion, corrupted lines of kspace are rejected and reacquired with the updated geometry. Patient movement is a fundamental problem in virtually all in vivo MR applications. Motion induces local field variations, causes erroneous positional encoding of k-space data, and corrupts the spin-excitation history between slices; these phenomena manifest in image-space as misregistrations, blurring, and ghosting. Even a few millimeters of movement during scanning can produce severe artifacts in reconstructed data, thus rendering images unusable. Often, it is subject populations with the highest potential diagnostic benefit in which the utility of MRI is curtailed by motion artifacts. In a study of 17 patients with frontoparietal tumors, data from five had to be rejected due to gross motion artifacts (1). Even among a healthy elderly population, our experience suggests that significant artifacts may appear in 10% to 20% of high-resolution structural brain scans; typically used for diagnostic and morphological analysis, such scans are especially prone to motion artifact due to their longer duration. To address these concerns, a motion-correction strategy for brain MRI is presented.The fact that the head is a rigid-body (to a very close approximation) allows an arbitrary motion to be described by six degrees-of-freedom (6-DOF)-three rotations about a three-dimensional (3D) orthogonal coordinate-system, and three translations. Retrospective motion-compensation methods, such as those used to coregister multiple image volumes in functional MRI (fMRI) studies, are well established. The most popular algorithms (2) determine the 6-DOF via minimization of a least-squares cost function and only correct for interimage motion. Retrospective correction involves interpolation, which can cause image blurring, and is further limited by its inability to fully correct for the influences of through-plane motion on local spin-history.In contrast, prospective strategies compensate for motion in the acquisition stage by keeping the image-plane at a fixed orientation ...

Purpose A novel prospective motion correction technique for brain MRI is presented that uses miniature wireless radio-frequency (RF) coils, or “wireless markers”, for position tracking. Methods Each marker is free of traditional cable connections to the scanner. Instead, its signal is wirelessly linked to the MR receiver via inductive coupling with the head coil. Real-time tracking of rigid head motion is performed using a pair of glasses integrated with three wireless markers. A tracking pulse-sequence, combined with knowledge of the markers’ unique geometrical arrangement, is used to measure their positions. Tracking data from the glasses is then used to prospectively update the orientation and position of the image-volume so that it follows the motion of the head. Results Wireless-marker position measurements were comparable to measurements using traditional wired RF tracking coils, with the standard deviation of the difference < 0.01 mm over the range of positions measured inside the head coil. RF safety was verified with B1 maps and temperature measurements. Prospective motion correction was demonstrated in a 2D spin-echo scan while the subject performed a series of deliberate head rotations. Conclusion Prospective motion correction using wireless markers enables high quality images to be acquired even during bulk motions. Wireless markers are small, avoid RF safety risks from electrical cables, are not hampered by mechanical connections to the scanner, and require minimal setup times. These advantages may help to facilitate adoption in the clinic.

Head motion is a fundamental problem in functional magnetic resonance imaging and is often a limiting factor in its clinical implementation. This work presents a rigid-body motion correction strategy for echo-planar imaging sequences that uses micro radiofrequency coil ''active markers'' for real-time, slice-by-slice prospective correction. Before the acquisition of each echo-planar imaging-slice, a short tracking pulsesequence measures the positions of three active markers integrated into a headband worn by the subject; the rigidbody transformation that realigns these markers to their initial positions is then fed back to dynamically update the scanplane, maintaining it at a fixed orientation relative to the head. Using this method, prospectively-corrected echo-planar imaging time series are acquired on volunteers performing in-plane and through-plane head motions, with results demonstrating increased image stability over conventional retrospective image-realignment. The benefit of this improved image stability is assessed in a blood oxygenation level dependent functional magnetic resonance imaging application. Finally, a non-rigid-body distortion-correction algorithm is introduced to reduce the remaining signal variation. Magn Reson Med 66:73-81,

Despite rigid-body realignment to compensate for head motion during an echo-planar imaging (EPI) time-series scan, non-rigid image deformations remain due to changes in the effective shim within the brain as the head moves through the B0 field. The current work presents a combined prospective/retrospective solution to reduce both rigid and non-rigid components of this motion-related image misalignment. Prospective rigid-body correction, where the scan-plane orientation is dynamically updated to track with the subject’s head, is performed using an active marker setup. Retrospective distortion correction is then applied to unwarp the remaining non-rigid image deformations caused by motion-induced field changes. Distortion correction relative to a reference time-frame does not require any additional field mapping scans or models, but rather uses the phase information from the EPI time-series itself. This combined method is applied to compensate EPI scans of volunteers performing in-plane and through-plane head motions, resulting in increased image stability beyond what either prospective or retrospective rigid-body correction alone can achieve. The combined method is also assessed in a BOLD fMRI task, resulting in improved Z-score statistics.

Purpose To develop and implement a clinical DTI technique suitable for the pediatric setting that retrospectively corrects for large motion without the need for rescanning and/or reacquisition strategies, and to deliver high quality DTI images (both in the presence and absence of large motion) using procedures that reduce image noise and artifacts. Materials and Methods We implemented an in-house built GRAPPA-accelerated diffusion tensor (DT)-EPI sequence on 1600 patients between 1 month and 18 years old at 1.5T and 3T. To reconstruct the data, we developed a fully-automated tailored reconstruction software that selects the best GRAPPA and ghost calibration weights; does 3D rigid-body realignment with importance weighting; and which employs phase correction and complex averaging to lower Rician noise and reduce phase artifacts. For select cases we investigated the use of an additional volume rejection criterion and b-matrix correction for large motion. Results The DTI image reconstruction procedures developed here were extremely robust in correcting for motion, failing on only 3 subjects, while providing the radiologists high quality data for routine evaluation. Conclusion This work suggests that, apart from in the rare instance of continuous motion throughout the scan, high quality DTI brain data can be acquired using our proposed integrated sequence and reconstruction that uses a retrospective approach to motion correction. In addition, we demonstrate a substantial improvement in overall image quality by combining phase correction with complex averaging – which reduces the Rician noise that biases noisy data.

Purpose B0 eddy currents are a subtle but important source of artifacts in spiral MRI. This study illustrates the importance of addressing these artifacts and presents a system response‐based eddy current correction strategy using B0 eddy current phase measurements on a phantom. Methods B0 and linear eddy current system response measurements were estimated from phantom‐based measurement and used to predict residual eddy current effects in spiral acquisitions. The measurements were evaluated across multiple systems and gradient sets. The corresponding eddy current corrections were studied in both axial spiral‐in/out TSE and sagittal spiral‐out MPRAGE volunteer data. Results Correction of B0 eddy currents using the proposed method mitigated blurriness in the axial spiral‐in/out images and artifacts in the sagittal spiral‐out images. The system response measurement was found to yield repeatable results over time with some variation in the B0 eddy current responses measured between different systems. Conclusions The proposed eddy current correction framework was effective in mitigating the effects of residual B0 and linear eddy currents. Any spiral acquisition should take residual eddy currents into account. This is particularly important in spiral‐in/out acquisitions.

The methods presented here allow calibration of sufficient quality to be carried out and maintained with no additional technologist workload. Magn Reson Med 79:1911-1921, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Group level statistical maps of blood oxygenation level dependent (BOLD) signals acquired using functional magnetic resonance imaging (fMRI) have become a basic measurement for much of systems, cognitive and social neuroscience. A challenge in making inferences from these statistical maps is the noise and potential confounds that arise from the head motion that occurs within and between acquisition volumes. This motion results in the scan plane being misaligned during acquisition, ultimately leading to reduced statistical power when maps are constructed at the group level. In most cases, an attempt is made to correct for this motion through the use of retrospective analysis methods. In this paper, we use a prospective active marker motion correction (PRAMMO) system that uses radio frequency markers for real-time tracking of motion, enabling on-line slice plane correction. We show that the statistical power of the activation maps is substantially increased using PRAMMO compared to conventional retrospective correction. Analysis of our results indicates that the PRAMMO acquisition reduces the variance without decreasing the signal component of the BOLD (beta). Using PRAMMO could thus improve the overall statistical power of fMRI based BOLD measurements, leading to stronger inferences of the nature of processing in the human brain.