Prospective real-time head motion correction using inductively coupled wireless NMR probes

Prospective head motion correction at 3 Tesla with wireless NMR markers and ultrashort echo navigators

PURPOSE

Prospective motion correction (PMC) with inductively-coupled wireless NMR markers has been shown to be an effective plug-and-play method for dealing with head motion at 7 Tesla [29,30]. However, technical challenges such as one-to-one identification of three wireless markers, generation of hyper-intense marker artifacts and low marker peak SNR in the navigators has limited the adoption of this technique. The goal of this work is to introduce solutions to overcome these issues and extend this technique to PMC for brain imaging at 3 Tesla.

METHODS

PMC with 6 degrees of freedom (DOF) was implemented using a novel ∼8 ms, ultrashort echo time (UTE) navigator in concert with optimally chosen MnCl2 marker samples to minimize marker artifacts. Distinct head coil sensitivities were leveraged to enable identification and tracking of individual markers and a variable flip angle (VFA) scheme and real time filtering were used to boost marker SNR. PMC was performed in 3D T1 weighted brain imaging at 3 Tesla with voluntary head motions in adult volunteers.

RESULTS

PMC with wireless markers improved image quality in 3D T1 weighted images in all subjects compared to non-motion corrected images for similar motions with no noticeable marker artifacts. Precision of motion tracking was found to be in the range of 0.01-0.06 mm/degrees. Navigator execution had minimal impact on sequence duration.

CONCLUSIONS

Wireless NMR markers provide an accurate, calibration-free and economical option for 6 DOF PMC in brain imaging across field strengths. Challenges in this technique can be addressed by combining navigator design, sample selection and real time data processing strategies.

Servo navigators: Linear regression and feedback control for rigid-body motion correction

PURPOSE

Navigator-based correction of rigid-body motion reconciling high precision with minimal acquisition, minimal calibration and simple, fast processing.

METHODS

A short orbital navigator (2.3 ms) is inserted in a three-dimensional (3D) gradient echo sequence for human head imaging. Head rotation and translation are determined by linear regression based on a complex-valued model built either from three reference navigators or in a reference-less fashion, from the first actual navigator. Optionally, the model is expanded by global phase and field offset. Run-time scan correction on this basis establishes servo control that maintains validity of the linear picture by keeping its expansion point stable in the head frame of reference. The technique is assessed in a phantom and demonstrated by motion-corrected imaging in vivo.

RESULTS

The proposed approach is found to establish stable motion control both with and without reference acquisition. In a phantom, it is shown to accurately detect motion mimicked by rotation of scan geometry as well as change in global B0 . It is demonstrated to converge to accurate motion estimates after perturbation well beyond the linear signal range. In vivo, servo navigation achieved motion detection with precision in the single-digit range of micrometers and millidegrees. Involuntary and intentional motion in the range of several millimeters were successfully corrected, achieving excellent image quality.

CONCLUSION

The combination of linear regression and feedback control enables prospective motion correction for head imaging with high precision and accuracy, short navigator readouts, fast run-time computation, and minimal demand for reference data.

Design of a 6-DoF Parallel Robotic Platform for MRI Applications

In this work, the design, analysis, and characterization of a parallel robotic motion generation platform with 6-degrees of freedom (DoF) for magnetic resonance imaging (MRI) applications are presented. The motivation for the development of this robot is the need for a robotic platform able to produce accurate 6-DoF motion inside the MRI bore to serve as the ground truth for motion modeling; other applications include manipulation of interventional tools such as biopsy and ablation needles and ultrasound probes for therapy and neuromodulation under MRI guidance. The robot is comprised of six pneumatic cylinder actuators controlled via a robust sliding mode controller. Tracking experiments of the pneumatic actuator indicates that the system is able to achieve an average error of 0.69 ± 0.14 mm and 0.67 ± 0.40 mm for step signal tracking and sinusoidal signal tracking, respectively. To demonstrate the feasibility and potential of using the proposed robot for minimally invasive procedures, a phantom experiment was performed in the benchtop environment, which showed a mean positional error of 1.20 ± 0.43 mm and a mean orientational error of 1.09 ± 0.57°, respectively. Experiments conducted in a 3T whole body human MRI scanner indicate that the robot is MRI compatible and capable of achieving positional error of 1.68 ± 0.31 mm and orientational error of 1.51 ± 0.32° inside the scanner, respectively. This study demonstrates the potential of this device to enable accurate 6-DoF motions in the MRI environment.

Tracking of rigid head motion during MRI using an EEG system

Purpose

To demonstrate a novel method for tracking of head movements during MRI using electroencephalography (EEG) hardware for recording signals induced by native imaging gradients.

Theory and Methods

Gradient switching during simultaneous EEG–fMRI induces distortions in EEG signals, which depend on subject head position and orientation. When EEG electrodes are interconnected with high‐impedance carbon wire loops, the induced voltages are linear combinations of the temporal gradient waveform derivatives. We introduce head tracking based on these signals (CapTrack) involving 3 steps: (1) phantom scanning is used to characterize the target sequence and a fast calibration sequence; (2) a linear relation between changes of induced signals and head pose is established using the calibration sequence; and (3) induced signals recorded during target sequence scanning are used for tracking and retrospective correction of head movement without prolonging the scan time of the target sequence. Performance of CapTrack is compared directly to interleaved navigators.

Results

Head‐pose tracking at 27.5 Hz during echo planar imaging (EPI) was demonstrated with close resemblance to rigid body alignment (mean absolute difference: [0.14 0.38 0.15]‐mm translation, [0.30 0.27 0.22]‐degree rotation). Retrospective correction of 3D gradient‐echo imaging shows an increase of average edge strength of 12%/−0.39% for instructed/uninstructed motion with CapTrack pose estimates, with a tracking interval of 1561 ms and high similarity to interleaved navigator estimates (mean absolute difference: [0.13 0.33 0.12] mm, [0.28 0.15 0.22] degrees).

Conclusion

Motion can be estimated from recordings of gradient switching with little or no sequence modification, optionally in real time at low computational burden and synchronized to image acquisition, using EEG equipment already found at many research institutions.

Suppressing motion artefacts in MRI using an Inception-ResNet network with motion simulation augmentation

The suppression of motion artefacts from MR images is a challenging task. The purpose of this paper was to develop a standalone novel technique to suppress motion artefacts in MR images using a data-driven deep learning approach. A simulation framework was developed to generate motion-corrupted images from motion-free images using randomly generated motion profiles. An Inception-ResNet deep learning network architecture was used as the encoder and was augmented with a stack of convolution and upsampling layers to form an encoder-decoder network. The network was trained on simulated motion-corrupted images to identify and suppress those artefacts attributable to motion. The network was validated on unseen simulated datasets and real-world experimental motion-corrupted in vivo brain datasets. The trained network was able to suppress the motion artefacts in the reconstructed images, and the mean structural similarity (SSIM) increased from 0.9058 to 0.9338. The network was also able to suppress the motion artefacts from the real-world experimental dataset, and the mean SSIM increased from 0.8671 to 0.9145. The motion correction of the experimental datasets demonstrated the effectiveness of the motion simulation generation process. The proposed method successfully removed motion artefacts and outperformed an iterative entropy minimization method in terms of the SSIM index and normalized root mean squared error, which were 5-10% better for the proposed method. In conclusion, a novel, data-driven motion correction technique has been developed that can suppress motion artefacts from motion-corrupted MR images. The proposed technique is a standalone, post-processing method that does not interfere with data acquisition or reconstruction parameters, thus making it suitable for routine clinical practice.

Recent Advances in Radio-Frequency Coil Technologies: Flexible, Wireless, and Integrated Coil Arrays

Radio-frequency (RF) coils are to magnetic resonance imaging (MRI) scanners what eyes are to the human body. Because of their critical importance, there have been constant innovations driving the rapid development of RF coil technologies. Over the past four decades, the breadth and depth of the RF coil technology evolution have far exceeded the space allowed for this review article. However, these past developments have laid the very foundation on which some of the recent technical breakthroughs are built upon. Here, we narrow our focus on some of the most recent RF coil advances, specifically, on flexible, wireless, and integrated coil arrays. To provide a detailed review, we discuss the theoretical underpinnings, experimental implementations, promising results, as well as future outlooks covering these exciting topics. These recent innovations have greatly improved patient comfort and ease of scan, while also increasing the signal-to-noise ratio, image resolution, temporal throughput, and diagnostic and treatment accuracy. Together with advances in other MRI subfields, they will undoubtedly continue to drive the field forward and lead us to an ever more exciting future. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 1.

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.

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.

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.

Closed Loop Control of an MR-Conditional Robot with Wireless Tracking Coil Feedback

This paper presents a hardware and software system to implement the task space control of an MR-conditional robot by integrating inductively coupled wireless coil based tracking feedback into the control loop. The main motivation of this work is to increase the accuracy performance and address the system uncertainties in the practical scenarios. We present the MR-conditional robot hardware design, wireless tracking method, and custom-designed communication software for real-time tracking data transfer. Based on these working principles, we fabricate the robot platform and evaluate the complete system with respect to various performance indices, i.e. data communication speed, targeting accuracy, tracking coil resolution, image quality, temperature variation, and task space control accuracy for static and dynamic targeting inside MRI scanner. The in-scanner targeting results show that the MR-conditional robot with wireless tracking coil feedback achieves the targeting error of 0.17 ± 0.08 mm, while the error calculated from the joint space optical encoder feedback is 0.68 ± 0.19 mm.

Markerless motion tracking and correction for PET, MRI, and simultaneous PET/MRI

OBJECTIVE

We demonstrate and evaluate the first markerless motion tracker compatible with PET, MRI, and simultaneous PET/MRI systems for motion correction (MC) of brain imaging.

METHODS

PET and MRI compatibility is achieved by careful positioning of in-bore vision extenders and by placing all electronic components out-of-bore. The motion tracker is demonstrated in a clinical setup during a pediatric PET/MRI study including 94 pediatric patient scans. PET MC is presented for two of these scans using a customized version of the Multiple Acquisition Frame method. Prospective MC of MRI acquisition of two healthy subjects is demonstrated using a motion-aware MRI sequence. Real-time motion estimates are accompanied with a tracking validity parameter to improve tracking reliability.

RESULTS

For both modalities, MC shows that motion induced artifacts are noticeably reduced and that motion estimates are sufficiently accurate to capture motion ranging from small respiratory motion to large intentional motion. In the PET/MRI study, a time-activity curve analysis shows image improvements for a patient performing head movements corresponding to a tumor motion of ±5-10 mm with a 19% maximal difference in standardized uptake value before and after MC.

CONCLUSION

The first markerless motion tracker is successfully demonstrated for prospective MC in MRI and MC in PET with good tracking validity.

SIGNIFICANCE

As simultaneous PET/MRI systems have become available for clinical use, an increasing demand for accurate motion tracking and MC in PET/MRI scans has emerged. The presented markerless motion tracker facilitate this demand.

MR-conditional steerable needle robot for intracerebral hemorrhage removal

BACKGROUND

Intracerebral hemorrhage (ICH) is one of the deadliest forms of stroke in the USA. Conventional surgical techniques such as craniotomy or stereotactic aspiration disrupt a large volume of healthy brain tissue in their attempts to reach the surgical site. Consequently, the surviving patients suffer from debilitating complications.

METHODS

We fabricated a novel MR-conditional steerable needle robot for ICH treatment. The robot system is powered by a custom-designed high power and low-cost pneumatic motor. We tested the robot's targeting accuracy and MR-conditionality performance, and performed phantom evacuation experiment under MR image guidance.

RESULTS

Experiments demonstrate that the robotic hardware is MR-conditional; the robot has the targeting accuracy of 1.26 ± 1.22 mm in bench-top tests. With real-time MRI guidance, the robot successfully reached the desired target and evacuated an 11.3 ml phantom hematoma in 9 min.

CONCLUSION

MRI-guided steerable needle robotic system is a potentially feasible approach for ICH treatment by providing accurate needle guidance and intraoperative surgical outcome evaluation.

Stereotactic Systems for MRI-Guided Neurosurgeries: A State-of-the-Art Review

Recent technological developments in magnetic resonance imaging (MRI) and stereotactic techniques have significantly improved surgical outcomes. Despite the advantages offered by the conventional MRI-guided stereotactic neurosurgery, the robotic-assisted stereotactic approach has potential to further improve the safety and accuracy of neurosurgeries. This review aims to provide an update on the potential and continued growth of the MRI-guided stereotactic neurosurgical techniques by describing the state of the art in MR conditional stereotactic devices including manual and robotic-assisted. The paper also presents a detailed overview of MRI-guided stereotactic devices, MR conditional actuators and encoders used in MR conditional robotic-assisted stereotactic devices. The review concludes with several research challenges and future perspectives, including actuator and sensor technique, MR image guidance, and robot design issues.

Hybrid PET/MRI Methodology

The hybrid PET/MR scanner represents the first implementation of the effective integration of two modalities allowing truly synchronous/simultaneous acquisition of their imaging signals. This integration, resulting from the innovation and development of specific hardware components has paved the way for new approaches in the study of neurodegenerative diseases. This chapter will describe the hardware development that has led to the availability of different clinical solutions for PET/MR imaging as well as the still-open technological challenges and opportunities related to the processing and exploitation of the simultaneous acquisition in neurological studies.

Image reconstruction algorithm for motion insensitive MR Fingerprinting (MRF): MORF

PURPOSE

The purpose of this study is to increase the robustness of MR fingerprinting (MRF) toward subject motion.

METHODS

A novel reconstruction algorithm, MOtion insensitive MRF (MORF), was developed, which uses an iterative reconstruction based retrospective motion correction approach. Each iteration loops through the following steps: pattern recognition, metric based identification of motion corrupted frames, registration based motion estimation, and motion compensated data consistency verification. The proposed algorithm was validated using in vivo 2D brain MRF data with retrospective in-plane motion introduced at different stages of the acquisition. The validation was performed using qualitative and quantitative comparisons between results from MORF, the iterative multi-scale (IMS) algorithm, and with the IMS results using data without motion for a ground truth comparison. Additionally, the MORF algorithm was evaluated in prospectively motion corrupted in vivo 2D brain MRF datasets.

RESULTS

For datasets corrupted by in-plane motion both prospectively and retrospectively, MORF noticeably reduced motion artifacts compared with iterative multi-scale and closely resembled the results from data without motion, even when ∼54% of data was motion corrupted during different parts of the acquisition.

CONCLUSIONS

MORF improves the insensitivity of MRF toward rigid-body motion occurring during any part of the MRF acquisition.

Prospective motion correction with NMR markers using only native sequence elements

PURPOSE

To develop a method of tracking active NMR markers that requires no alterations of common imaging sequences and can be used for prospective motion correction (PMC) in brain MRI.

METHODS

Localization of NMR markers is achieved by acquiring short signal snippets in rapid succession and evaluating them jointly. To spatially encode the markers, snippets are timed such that signal phase is accrued during sequence intervals with suitably diverse gradient actuation. For motion tracking and PMC in brain imaging, the markers are mounted on a lightweight headset. PMC is then demonstrated with high-resolution T₂ *- and T₁ -weighted imaging sequences in the presence of instructed as well as residual unintentional head motion.

RESULTS

With both unaltered sequences, motion tracking was achieved with precisions on the order of 10 µm and 0.01° and temporal resolution of 48 and 39 ms, respectively. On this basis, PMC improved image quality significantly throughout.

CONCLUSION

The proposed approach permits high-precision motion tracking and PMC with standard imaging sequences. It does so without altering sequence design and thus overcomes a key hindrance to routine motion tracking with NMR markers. Magn Reson Med 79:2046-2057, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Prospective motion correction in functional MRI

Due to the intrinsic low sensitivity of BOLD-fMRI long scanning is required. Subject motion during fMRI scans reduces statistical significance of the activation maps and increases the prevalence of false activations. Motion correction is therefore an essential tool for a successful fMRI data analysis. Retrospective motion correction techniques are now commonplace and are incorporated into a wide range of fMRI analysis toolboxes. These techniques are advantageous due to robustness, sequence independence and have minimal impact on the fMRI study setup. Retrospective techniques however, do not provide an accurate intra-volume correction, nor can these techniques correct for the spin-history effects. The application of prospective motion correction in fMRI appears to be effective in reducing false positives and increasing sensitivity when compared to retrospective techniques, particularly in the cases of substantial motion. Especially advantageous in this regard is the combination of prospective motion correction with dynamic distortion correction. Nevertheless, none of the recent methods are able to recover activations in presence of motion that are comparable to no-motion conditions, which motivates further research in the area of adaptive dynamic imaging.

Motion-Robust Diffusion-Weighted Brain MRI Reconstruction Through Slice-Level Registration-Based Motion Tracking

This work proposes a novel approach for motion-robust diffusion-weighted (DW) brain MRI reconstruction through tracking temporal head motion using slice-to-volume registration. The slice-level motion is estimated through a filtering approach that allows tracking the head motion during the scan and correcting for out-of-plane inconsistency in the acquired images. Diffusion-sensitized image slices are registered to a base volume sequentially over time in the acquisition order where an outlier-robust Kalman filter, coupled with slice-to-volume registration, estimates head motion parameters. Diffusion gradient directions are corrected for the aligned DWI slices based on the computed rotation parameters and the diffusion tensors are directly estimated from the corrected data at each voxel using weighted linear least squares. The method was evaluated in DWI scans of adult volunteers who deliberately moved during scans as well as clinical DWI of 28 neonates and children with different types of motion. Experimental results showed marked improvements in DWI reconstruction using the proposed method compared to the state-of-the-art DWI analysis based on volume-to-volume registration. This approach can be readily used to retrieve information from motion-corrupted DW imaging data.

Design and Fabrication of MR-Tracked Metallic Stylet for Gynecologic Brachytherapy

Active magnetic resonance (MR) tracking for gynecologic brachytherapy was made possible by attaching the micro radiofrequency coils to the brachytherapy applicator. The rectangular planar micro coil was fabricated using flexible printed circuits with dimensions of 8mm×1.5mm. A 5-Fr (1.6mm) tungsten brachytherapy stylet was custom-machined to incorporate the micro coils. The finite element analysis and the phantom tissue studies show that the proposed device enables in situ, real-time guidance of access routes to the target anatomy safely and accurately. The setup was tested in a Siemens 3T MR scanner. The micro coils can be localized rapidly (up to 40 Hz) and precisely (resolution: 0.6×0.6×0.6mm³) using an MR-tracking sequence.

Motion correction in MRI of the brain

Subject motion in MRI is a relevant problem in the daily clinical routine as well as in scientific studies. Since the beginning of clinical use of MRI, many research groups have developed methods to suppress or correct motion artefacts. This review focuses on rigid body motion correction of head and brain MRI and its application in diagnosis and research. It explains the sources and types of motion and related artefacts, classifies and describes existing techniques for motion detection, compensation and correction and lists established and experimental approaches. Retrospective motion correction modifies the MR image data during the reconstruction, while prospective motion correction performs an adaptive update of the data acquisition. Differences, benefits and drawbacks of different motion correction methods are discussed.

Additional sampling directions improve detection range of wireless radiofrequency probes

Purpose

While MRI is enhancing our knowledge about the structure and function of the human brain, subject motion remains a problem in many clinical applications. Recently, the use of wireless radiofrequency markers with three one‐dimensional (1D) navigators for prospective correction was demonstrated. This method is restricted in the range of motion that can be corrected, however, because of limited information in the 1D readouts.

Methods

Here, the limitation of techniques for disambiguating marker locations was investigated. It was shown that including more sampling directions extends the tracking range for head rotations. The efficiency of trading readout resolution for speed was explored.

Results

Tracking of head rotations was demonstrated from −19.2 to 34.4°, −2.7 to 10.0°, and −60.9 to 70.9° in the x‐, y‐, and z‐directions, respectively. In the presence of excessive head motion, the deviation of marker estimates from SPM8 was reduced by 17.1% over existing three‐projection methods. This was achieved by using an additional seven directions, extending the time needed for readouts by a factor of 3.3. Much of this increase may be circumvented by reducing resolution, without compromising accuracy.

Conclusion

Including additional sampling directions extends the range in which markers can be used, for patients who move a lot. Magn Reson Med 76:913–918, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Functional Magnetic Resonance Imaging Methods

Since its inception in 1992, Functional Magnetic Resonance Imaging (fMRI) has become an indispensible tool for studying cognition in both the healthy and dysfunctional brain. FMRI monitors changes in the oxygenation of brain tissue resulting from altered metabolism consequent to a task-based evoked neural response or from spontaneous fluctuations in neural activity in the absence of conscious mentation (the "resting state"). Task-based studies have revealed neural correlates of a large number of important cognitive processes, while fMRI studies performed in the resting state have demonstrated brain-wide networks that result from brain regions with synchronized, apparently spontaneous activity. In this article, we review the methods used to acquire and analyze fMRI signals.

Optical tracking with two markers for robust prospective motion correction for brain imaging

OBJECTIVE

Prospective motion correction (PMC) during brain imaging using camera-based tracking of a skin-attached marker may suffer from problems including loss of marker visibility due to the coil and false correction due to non-rigid-body facial motion, such as frowning or squinting. A modified PMC system is introduced to mitigate these problems and increase the robustness of motion correction.

MATERIALS AND METHODS

The method relies on simultaneously tracking two markers, each providing six degrees of freedom, that are placed on the forehead. This allows us to track head motion when one marker is obscured and detect skin movements to prevent false corrections. Experiments were performed to compare the performance of the two-marker motion correction technique to the previous single-marker approach.

RESULTS

Experiments validate the theory developed for adaptive marker tracking and skin movement detection, and demonstrate improved image quality during obstruction of the line-of-sight of one marker when subjects squint or when subjects squint and move simultaneously.

CONCLUSION

The proposed methods eliminate two common failure modes of PMC and substantially improve the robustness of PMC, and they can be applied to other optical tracking systems capable of tracking multiple markers. The methods presented can be adapted to the use of more than two markers.

Motion artifacts in MRI: A complex problem with many partial solutions

Subject motion during magnetic resonance imaging (MRI) has been problematic since its introduction as a clinical imaging modality. While sensitivity to particle motion or blood flow can be used to provide useful image contrast, bulk motion presents a considerable problem in the majority of clinical applications. It is one of the most frequent sources of artifacts. Over 30 years of research have produced numerous methods to mitigate or correct for motion artifacts, but no single method can be applied in all imaging situations. Instead, a "toolbox" of methods exists, where each tool is suitable for some tasks, but not for others. This article reviews the origins of motion artifacts and presents current mitigation and correction methods. In some imaging situations, the currently available motion correction tools are highly effective; in other cases, appropriate tools still need to be developed. It seems likely that this multifaceted approach will be what eventually solves the motion sensitivity problem in MRI, rather than a single solution that is effective in all situations. This review places a strong emphasis on explaining the physics behind the occurrence of such artifacts, with the aim of aiding artifact detection and mitigation in particular clinical situations.

A survey of patient motion in disorders of consciousness and optimization of its retrospective correction

Functional magnetic resonance imaging (fMRI) can be seriously impaired by patient motion. The purpose of this study was to characterize the typical motion in a clinical population of patients in disorders of consciousness and compare the performance of retrospective correction with rigid-body realignment as implemented in widely used software packages. 63 subjects were scanned with an fMRI visual checkerboard paradigm using a 3T scanner. Time series were corrected for motion, and the resulting transformations were used to calculate a motion score. SPM, FSL, AFNI and AIR were evaluated by comparing the motion obtained by re-running the tool on the corrected data. A publicly available sample fMRI dataset was modified with the motion detected in each patient with each tool. The performance of each tool was measured by comparing the number of supra-threshold voxels after standard fMRI analysis, both in the sample dataset and in simulated fMRI data. We assessed the effect of user-changeable parameters on motion correction in SPM. We found the equivalent motion in the patient population to be 1.4mm on average. There was no significant difference in performance between SPM, FSL and AFNI. AIR was considerably worse, and took more time to run. We found that in SPM the quality factor and interpolation method have no effect on the cluster size, while higher separation and smoothing reduce it. We showed that the main packages SPM, FSL and AFNI are equally suitable for retrospective motion correction of fMRI time series. We show that typically only 80% of activated voxels are recovered by retrospective motion correction.

MR-based motion correction for PET imaging using wired active MR microcoils in simultaneous PET-MR: phantom study

PURPOSE

Artifacts caused by head motion present a major challenge in brain positron emission tomography (PET) imaging. The authors investigated the feasibility of using wired active MR microcoils to track head motion and incorporate the measured rigid motion fields into iterative PET reconstruction.

METHODS

Several wired active MR microcoils and a dedicated MR coil-tracking sequence were developed. The microcoils were attached to the outer surface of an anthropomorphic(18)F-filled Hoffman phantom to mimic a brain PET scan. Complex rotation/translation motion of the phantom was induced by a balloon, which was connected to a ventilator. PET list-mode and MR tracking data were acquired simultaneously on a PET-MR scanner. The acquired dynamic PET data were reconstructed iteratively with and without motion correction. Additionally, static phantom data were acquired and used as the gold standard.

RESULTS

Motion artifacts in PET images were effectively removed by wired active MR microcoil based motion correction. Motion correction yielded an activity concentration bias ranging from -0.6% to 3.4% as compared to a bias ranging from -25.0% to 16.6% if no motion correction was applied. The contrast recovery values were improved by 37%-156% with motion correction as compared to no motion correction. The image correlation (mean ± standard deviation) between the motion corrected (uncorrected) images of 20 independent noise realizations and static reference was R(2) = 0.978 ± 0.007 (0.588 ± 0.010, respectively).

CONCLUSIONS

Wired active MR microcoil based motion correction significantly improves brain PET quantitative accuracy and image contrast.

Motion compensation for brain PET imaging using wireless MR active markers in simultaneous PET-MR: phantom and non-human primate studies

Brain PET scanning plays an important role in the diagnosis, prognostication and monitoring of many brain diseases. Motion artifacts from head motion are one of the major hurdles in brain PET. In this work, we propose to use wireless MR active markers to track head motion in real time during a simultaneous PET-MR brain scan and incorporate the motion measured by the markers in the listmode PET reconstruction. Several wireless MR active markers and a dedicated fast MR tracking pulse sequence module were built. Data were acquired on an ACR Flangeless PET phantom with multiple spheres and a non-human primate with and without motion. Motions of the phantom and monkey's head were measured with the wireless markers using a dedicated MR tracking sequence module. The motion PET data were reconstructed using list-mode reconstruction with and without motion correction. Static reference was used as gold standard for quantitative analysis. The motion artifacts, which were prominent on the images without motion correction, were eliminated by the wireless marker based motion correction in both the phantom and monkey experiments. Quantitative analysis was performed on the phantom motion data from 24 independent noise realizations. The reduction of bias of sphere-to-background PET contrast by active marker based motion correction ranges from 26% to 64% and 17% to 25% for hot (i.e., radioactive) and cold (i.e., non-radioactive) spheres, respectively. The motion correction improved the channelized Hotelling observer signal-to-noise ratio of the spheres by 1.2 to 6.9 depending on their locations and sizes. The proposed wireless MR active marker based motion correction technique removes the motion artifacts in the reconstructed PET images and yields accurate quantitative values.