ABSTRACT
INTRODUCTION: Geometric distortions along the phase encoding direction caused by off-resonant spins are a major issue in EPI based functional and diffusion imaging. The widely used blip up/down approach estimates the underlying distortion field from a pair of images with inverted phase encoding direction. Typically, iterative methods are used to find a solution to the ill-posed problem of finding the displacement field that maps up/down acquisitions onto each other. Here, we explore the use of a deep convolutional network to estimate the displacement map from a pair of input images. METHODS: We trained a deep convolutional U-net architecture that was previously used to estimate optic flow between moving images to learn to predict the distortion map from an input pair of distorted EPI acquisitions. During the training step, the network minimizes a loss function (similarity metric) that is calculated from corrected input image pairs. This approach does not require the explicit knowledge of the ground truth distortion map, which is difficult to get for real life data. RESULTS: We used data from a total of Ntrain â= â22 healthy subjects to train our network. A separate dataset of Ntest â= â12 patients including some with abnormal findings and unseen acquisition modes, e.g. LR-encoding, coronal orientation) was reserved for testing and evaluation purposes. We compared our results to FSL's topup function with default parameters that served as the gold standard. We found that our approach results in a correction accuracy that is virtually identical to the optimum found by an iterative search, but with reduced computational time. CONCLUSION: By using a deep convolutional network, we can reduce the processing time to a few seconds per volume, which is significantly faster than iterative approaches like FSL's topup which takes around 10min on the same machine (but using only 1 CPU). This facilitates the use of a blip up/down scheme for all diffusion-weighted acquisitions and potential real-time EPI distortion correction without sacrificing accuracy.
Subject(s)
Diffusion Magnetic Resonance Imaging/methods , Echo-Planar Imaging/methods , Image Processing, Computer-Assisted/methods , Adult , Algorithms , Artifacts , Brain Mapping , Computer Simulation , Databases, Factual , Diffusion Magnetic Resonance Imaging/statistics & numerical data , Echo-Planar Imaging/statistics & numerical data , Humans , Machine Learning , Neural Networks, ComputerABSTRACT
PURPOSE: A new method for enhancing the sensitivity of diffusion MRI (dMRI) by combining the data from single (sPFG) and double (dPFG) pulsed field gradient experiments is presented. METHODS: This method uses our JESTER framework to combine microscopic anisotropy information from dFPG experiments using a new method called diffusion tensor subspace imaging (DiTSI) to augment the macroscopic anisotropy information from sPFG data analyzed using our guided by entropy spectrum pathways method. This new method, called joint estimation diffusion imaging (JEDI), combines the sensitivity to macroscopic diffusion anisotropy of sPFG with the sensitivity to microscopic diffusion anisotropy of dPFG methods. RESULTS: Its ability to produce significantly more detailed anisotropy maps and more complete fiber tracts than existing methods within both brain white matter (WM) and gray matter (GM) is demonstrated on normal human subjects on data collected using a novel fast, robust, and clinically feasible sPFG/dPFG acquisition. CONCLUSIONS: The potential utility of this method is suggested by an initial demonstration of its ability to mitigate the problem of gyral bias. The capability of more completely characterizing the tissue structure and connectivity throughout the entire brain has broad implications for the utility and scope of dMRI in a wide range of research and clinical applications.
Subject(s)
Diffusion Tensor Imaging , White Matter , Anisotropy , Brain/diagnostic imaging , Diffusion Magnetic Resonance Imaging , Humans , White Matter/diagnostic imagingABSTRACT
PURPOSE: Optical prospective motion correction substantially reduces sensitivity to motion in neuroimaging of human subjects. However, a major barrier to clinical deployment has been the time-consuming cross-calibration between the camera and MRI scanner reference frames. This work addresses this challenge. METHODS: A single camera was mounted onto the head coil for tracking head motion. Two new methods were developed: (1) a rapid calibration method for camera-to-scanner cross-calibration using a custom-made tool incorporating wireless active markers, and (2) a calibration adjustment method to compensate for table motion between scans. Both methods were tested at 1.5T and 3T in vivo. Simulations were performed to determine the required mechanical tolerance for repositioning of the camera. RESULTS: The rapid calibration method is completed in a short (<30 s) scan, which is carried out only once per installation. The calibration adjustment method requires no extra scan time and runs automatically whenever the system is used. The mechanical tolerance analysis indicates that most motion (90% reduction in voxel displacement) could be corrected even with far larger camera repositioning errors than are observed in practice. CONCLUSION: 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.
Subject(s)
Adenoma/diagnostic imaging , Cerebrovascular Circulation , Magnetic Resonance Imaging/methods , Neuroimaging/methods , Optical Devices , Pituitary Neoplasms/diagnostic imaging , Algorithms , Brain/diagnostic imaging , Calibration , Computer Simulation , Equipment Design , Female , Head/diagnostic imaging , Humans , Imaging, Three-Dimensional , Male , Motion , Patient Positioning , Reproducibility of Results , Software , Stress, MechanicalABSTRACT
INTRODUCTION: Geometric distortions along the phase encode direction caused by off-resonant spins are still a major issue in EPI based functional and diffusion imaging. If the off-resonance map is known it is possible to correct for distortions. Most correction methods operate as a post-processing step on the reconstructed magnitude images. THEORY AND METHODS: Here, we present an algebraic reconstruction method (hybrid-space SENSE) that incorporates a physics based model of off-resonances, phase inconsistencies between k-space segments, and T2*-decay during the acquisition. The method can be used to perform a joint reconstruction of interleaved acquisitions with normal (blip-up) and inverted (blip-down) phase encode direction which results in reduced g-factor penalty. RESULTS: A joint blip-up/down simultaneous multi slice (SMS) reconstruction for SMS-factor 4 in combination with twofold in-plane acceleration leads to a factor of two decrease in maximum g-factor penalty while providing off-resonance and eddy-current corrected images. CONCLUSION: We provide an algebraic framework for reconstructing diffusion weighted EPI data that in addition to the general applicability of hybrid-space SENSE to 2D-EPI, SMS-EPI and 3D-EPI with arbitrary k-space coverage along z, allows for a modeling of arbitrary spatio-temporal effects during the acquisition period like off-resonances, phase inconsistencies and T2*-decay. The most immediate benefit is a reduction in g-factor penalty if an interleaved blip-up/down acquisition strategy is chosen which facilitates eddy current estimation and ensures no loss in k-space encoding in regions with strong off-resonance gradients.
Subject(s)
Brain Mapping/methods , Brain/anatomy & histology , Brain/physiology , Echo-Planar Imaging , Artifacts , Diffusion Magnetic Resonance Imaging/methods , Humans , Image Processing, Computer-Assisted , Models, Neurological , Signal Processing, Computer-AssistedABSTRACT
PURPOSE: Prospective motion correction for MRI and other imaging modalities are commonly based on the assumption of affine motion, i.e., rotations, shearing, scaling and translations. In addition it often involves transformations between different reference frames, especially for applications with an external tracking device. The goal of this work is to develop a computational framework for motion correction based on homogeneous transforms. THEORY AND METHODS: The homogeneous representation of affine transformations uses 4 × 4 transformation matrices applied to four-dimensional augmented vectors. It is demonstrated how homogenous transforms can be used to describe the motion of slice objects during an MRI scan. Furthermore, we extend the concept of homogeneous transforms to gradient and k-space vectors, and show that the fourth dimension of an augmented k-space vector encodes the complex phase of the corresponding signal sample due to translations. RESULTS: The validity of describing motion tracking in real space and k-space using homogeneous transformations only is demonstrated on phantom experiments. CONCLUSION: Homogeneous transformations allows for a conceptually simple, consistent and computationally efficient theoretical framework for motion correction applications.
Subject(s)
Algorithms , Artifacts , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging/methods , Magnetic Resonance Imaging/instrumentation , Motion , Movement , Numerical Analysis, Computer-Assisted , Phantoms, Imaging , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
PURPOSE: We present a volumetric sampling method that rotates the spiral interleaves of a stack of spirals (SOSP) trajectory for reduced aliasing artifacts using parallel imaging with undersampling. METHODS: The aliasing pattern in an undersampled SOSP acquisition was modified by consecutively rotating spiral interleaves in each phase-encoding plane. This allows a sampling scheme with a high reduction factor when using a volumetric multireceiver array. Phantom and in vivo brain images at a resolution of 1 × 1 × 2 mm(3) were acquired at 3T using a 32-channel coil. Images reconstructed with a reduction factor of 16 were compared for aliasing artifacts and geometry factor (g-factor). RESULTS: Phantom and in vivo brain image results revealed that the rotated SOSP acquisition with a reduction factor of 16 produces images with reduced aliasing and lower g-factors than images acquired without rotation. CONCLUSION: The proposed rotated SOSP sampling method is a highly efficient way to maximize the encoding power of volumetric receiver arrays in parallel imaging and is applicable to rapid volumetric scanning, including susceptibility-weighted imaging and functional MRI. Magn Reson Med 76:127-135, 2016. © 2015 Wiley Periodicals, Inc.
Subject(s)
Algorithms , Brain/anatomy & histology , Data Compression/methods , Image Interpretation, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging/methods , Signal Processing, Computer-Assisted , Data Interpretation, Statistical , Humans , Image Enhancement/methods , Magnetic Resonance Imaging/instrumentation , Phantoms, Imaging , Reproducibility of Results , Sample Size , Sensitivity and SpecificityABSTRACT
PURPOSE: One potential barrier for using prospective motion correction (PMC) in the clinic is the unpredictable nature of a scan because of the direct interference with the imaging sequence. We demonstrate that a second set of "de-corrected" images can be reconstructed from a scan with PMC that show how images would have appeared without PMC enabled. THEORY AND METHODS: For three-dimensional scans, the effects of PMC can be undone by performing a retrospective reconstruction based on the inverse of the transformation matrix used for real time gradient feedback. Retrospective reconstruction is performed using a generalized SENSE approach with continuous head motion monitored using a single-marker optical camera system. RESULTS: Reverse retrospective reconstruction is demonstrated for phantom and in vivo scans using an magnetization-prepared rapid gradient echo (MPRAGE) sequence including parallel and Partial Fourier acceleration. CONCLUSION: Reverse retrospective reconstruction can almost perfectly undo the effects of prospective feedback, and thereby provide a second image data set with the effects of motion correction removed. In case of correct feedback, one can directly compare the quality of the corrected with that of the uncorrected scan. Additionally, because erroneous feedback during PMC may introduce artifacts, it is possible to eliminate artifacts in a corrupted scan by reversing the false gradient updates. Magn Reson Med 75:2341-2349, 2016. © 2015 Wiley Periodicals, Inc.
Subject(s)
Head Movements/physiology , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging/methods , Artifacts , Brain/diagnostic imaging , Humans , Phantoms, Imaging , Reproducibility of ResultsABSTRACT
PURPOSE: Recently, a new algorithm was introduced to combine segments of under-sampled diffusion weighted data using multiplexed sensitivity encoding. While the algorithm provides good results in cooperative volunteers, motion during the data acquisition is not accounted for. In this work, the continuous prospective motion correction of a segmented diffusion weighted acquisition is combined with multiplexed sensitivity encoding. METHODS: Simulations investigate the influence of motion on the reconstruction. Additionally, the change in coil sensitivities due to patient motion is taken into consideration. Finally, in vivo experiments display the effects of motion and its prospective correction on high resolution diffusion weighted imaging. RESULTS: Inconsistencies of the imaging plane lead to artifacts and blurring in the reconstructed dataset. Additionally, motion during the diffusion weighting period can lead to substantial image artifacts and signal dropouts. The change in coil sensitivities shows minor effect for the simulated range of motion (5°). Prospective motion correction is shown to improve image quality in the case of large motion (5°) and to reliably correct for small motion (1°). CONCLUSION: The combination of prospective motion correction and multiplexed sensitivity encoding allows for high resolution diffusion weighted imaging even in the presence of substantial head motion.
Subject(s)
Artifacts , Brain/anatomy & histology , Diffusion Magnetic Resonance Imaging/methods , Echo-Planar Imaging/methods , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Adult , Algorithms , Humans , Male , Motion , Reproducibility of Results , Sensitivity and Specificity , Signal Processing, Computer-AssistedABSTRACT
PURPOSE: Simultaneous multislice (SMS) acquisitions play an important role in the challenge of increasing single-shot imaging speed. We show that sensitivity encoding in two spatial dimensions (two-dimensional sensitivity encoding [2D-SENSE]) can be used to reconstruct SMS acquisitions with periodic but otherwise arbitrary undersampling patterns. THEORY AND METHODS: By adopting a 3D k-space representation of the SMS sampling process, the accelerated in-plane and slice-encoding directions form a 2D-reconstruction problem that is equivalent to volumetric controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA). 2D-SENSE does not otherwise distinguish between standard volumetric and SMS imaging with arbitrary CAIPIRINHA sampling. RESULTS: Use of the SENSE algorithm is demonstrated for in vivo brain data obtained with blipped-CAIPRINHA sampling in 2D SMS-echo planar imaging (EPI) and rapid acquisition with relaxation enhancement (RARE) acquisitions as well as 3D-EPI with various in-plane and through-plane acceleration factors and CAIPIRINHA shifts. The proposed SENSE reconstruction works for any combination of SMS-factor and CAIPIRINHA shift by the addition of "dummy slices" that allow for noninteger undersampling in the slice direction. Images with commonly used slice-generalized autocalibrating partially parallel acquisitions reconstruction are shown for reference. CONCLUSION: SENSE is conceptually simple and provides a one-step reconstruction along both undersampled dimensions. It also provides a contrast-independent parallel imaging reconstruction for SMS.
Subject(s)
Echo-Planar Imaging/methods , Image Processing, Computer-Assisted/methods , Signal Processing, Computer-Assisted , Algorithms , Brain/anatomy & histology , Humans , Signal-To-Noise Ratio , SoftwareABSTRACT
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.
Subject(s)
Brain Mapping/methods , Fiducial Markers , Head Movements , Image Enhancement/methods , Magnetic Resonance Imaging/methods , Optical Devices , Artifacts , Forehead , Humans , Phantoms, ImagingABSTRACT
Parallel imaging methods using multi-coil receiver arrays have been shown to be effective for increasing MRI acquisition speed. However parallel imaging methods for fMRI with 2D sequences show only limited improvements in temporal resolution because of the long echo times needed for BOLD contrast. Recently, Simultaneous Multi-Slice (SMS) imaging techniques have been shown to increase fMRI temporal resolution by factors of four and higher. In SMS fMRI multiple slices can be acquired simultaneously using Echo Planar Imaging (EPI) and the overlapping slices are un-aliased using a parallel imaging reconstruction with multiple receivers. The slice separation can be further improved using the "blipped-CAIPI" EPI sequence that provides a more efficient sampling of the SMS 3D k-space. In this paper a blipped-spiral SMS sequence for ultra-fast fMRI is presented. The blipped-spiral sequence combines the sampling efficiency of spiral trajectories with the SMS encoding concept used in blipped-CAIPI EPI. We show that blipped spiral acquisition can achieve almost whole brain coverage at 3mm isotropic resolution in 168 ms. It is also demonstrated that the high temporal resolution allows for dynamic BOLD lag time measurement using visual/motor and retinotopic mapping paradigms. The local BOLD lag time within the visual cortex following the retinotopic mapping stimulation of expanding flickering rings is directly measured and easily translated into an eccentricity map of the cortex.
Subject(s)
Brain Mapping/methods , Cerebral Cortex/physiology , Image Interpretation, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging/methods , Movement/physiology , Visual Perception/physiology , Algorithms , Connectome/methods , Humans , Image Enhancement/methods , Multimodal Imaging/methods , Photic Stimulation/methods , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
EEG-fMRI is a unique method to combine the high temporal resolution of EEG with the high spatial resolution of MRI to study generators of intrinsic brain signals such as sleep grapho-elements or epileptic spikes. While the standard EPI sequence in fMRI experiments has a temporal resolution of around 2.5-3s a newly established fast fMRI sequence called MREG (Magnetic-Resonance-Encephalography) provides a temporal resolution of around 100ms. This technical novelty promises to improve statistics, facilitate correction of physiological artifacts and improve the understanding of epileptic networks in fMRI. The present study compares simultaneous EEG-EPI and EEG-MREG analyzing epileptic spikes to determine the yield of fast MRI in the analysis of intrinsic brain signals. Patients with frequent interictal spikes (>3/20min) underwent EEG-MREG and EEG-EPI (3T, 20min each, voxel size 3×3×3mm, EPI TR=2.61s, MREG TR=0.1s). Timings of the spikes were used in an event-related analysis to generate activation maps of t-statistics. (FMRISTAT, |t|>3.5, cluster size: 7 voxels, p<0.05 corrected). For both sequences, the amplitude and location of significant BOLD activations were compared with the spike topography. 13 patients were recorded and 33 different spike types could be analyzed. Peak T-values were significantly higher in MREG than in EPI (p<0.0001). Positive BOLD effects correlating with the spike topography were found in 8/29 spike types using the EPI and in 22/33 spikes types using the MREG sequence. Negative BOLD responses in the default mode network could be observed in 3/29 spike types with the EPI and in 19/33 with the MREG sequence. With the latter method, BOLD changes were observed even when few spikes occurred during the investigation. Simultaneous EEG-MREG thus is possible with good EEG quality and shows higher sensitivity in regard to the localization of spike-related BOLD responses than EEG-EPI. The development of new methods of analysis for this sequence such as modeling of physiological noise, temporal analysis of the BOLD signal and defining appropriate thresholds is required to fully profit from its high temporal resolution.
Subject(s)
Brain Mapping , Brain/physiopathology , Electroencephalography , Epilepsy/physiopathology , Magnetic Resonance Imaging , Nerve Net/physiopathology , Adolescent , Adult , Aged , Child , Data Interpretation, Statistical , Female , Humans , Male , Middle AgedABSTRACT
PURPOSE: Prospective motion correction of MRI scans using an external tracking device (such as a camera) is becoming increasingly popular, especially for imaging of the head. In order for external tracking data to be transformed into the MR scanner reference frame, the pose (i.e., position and orientation) of the camera relative to the scanner--or cross-calibration--must be accurate. In this study, we investigated how errors in cross-calibration affect the accuracy of motion correction feedback in MRI. THEORY AND METHODS: An operator equation is derived describing how calibration errors relate to errors in applied motion compensation. By taking advantage of spherical symmetry and performing a Taylor approximation for small rotation angles, a closed form expression and upper limit for the residual tracking error is provided. RESULTS: Experiments confirmed theoretical predictions of a bilinear dependence of the residual rotational component on the calibration error and the motion performed, modulated by a sinusoidal dependence on the angle between the calibration error axis and motion axis. The residual translation error is bounded by the sum of the rotation angle multiplied by the translational calibration error plus the linear head displacement multiplied by the calibration error angle. CONCLUSION: The results make it possible to calculate the required cross-calibration accuracy for external tracking devices for a range of motions. Scans with smaller expected movements require less accuracy in cross-calibration than scans involving larger movements. Typical clinical applications require that the calibration accuracy is substantially below 1 mm and 1°.
Subject(s)
Algorithms , Artifacts , Fiducial Markers/standards , Image Interpretation, Computer-Assisted/instrumentation , Image Interpretation, Computer-Assisted/standards , Magnetic Resonance Imaging/instrumentation , Magnetic Resonance Imaging/standards , Calibration , Equipment Design , Equipment Failure Analysis , Humans , Image Enhancement/instrumentation , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Motion , Phantoms, Imaging , Reproducibility of Results , Sensitivity and Specificity , United StatesABSTRACT
PURPOSE: Simultaneous multislice (SMS) acquisitions have recently received much attention as a means of increasing single-shot imaging speed. SMS acquisitions combine the advantages of single-shot sampling and acceleration along the slice dimension which was previously limited to three-dimensional (3D) volumetric acquisitions. A two-dimensional description of SMS sampling and reconstruction has become established in the literature. Here, we present a more general 3D Fourier encoding and reconstruction formalism for SMS acquisitions that can easily be applied to non-Cartesian SMS acquisitions. THEORY AND METHODS: An "SMS 3D" k-space is defined in which the field of view along the slice select direction is equal to the number of excited slices times their separation. In this picture, SMS acceleration can be viewed as an undersampling of SMS 3D k-space that can be freely distributed between the in-plane and slice directions as both are effective phase-encoding directions. RESULTS: Use of the SMS 3D k-space picture is demonstrated in phantom and in vivo brain acquisitions including data obtained with blipped-controlled aliasing in parallel imaging sampling. SMS sensitivity encoding reconstruction is demonstrated as well as non-Cartesian SMS imaging using blipped spiral trajectories. CONCLUSIONS: The full framework of reconstruction methods can be applied to SMS acquisitions by employing a 3D k-space approach. The blipped-controlled aliasing in parallel imaging method can be viewed as a special case of undersampling an SMS 3D k-space. The extension of SMS methods to non-Cartesian 3D sampling and reconstruction is straightforward.
Subject(s)
Image Enhancement/methods , Image Processing, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging/methods , Brain Mapping/methods , Echo-Planar Imaging , Fourier Analysis , Healthy Volunteers , Humans , Phantoms, ImagingABSTRACT
PURPOSE: Prospective motion correction of magnetic resonance (MR) scans commonly uses an external device, such as a camera, to track the pose of the organ of interest. However, in order for external tracking data to be translated into the MR scanner reference frame, the pose of the camera relative to the MR scanner must be known accurately. Here, we describe a fast, accurate, non-iterative technique to determine the position of an external tracking device de novo relative to the MR reference frame. THEORY AND METHODS: The method relies on imaging a sparse object that allows simultaneous tracking of arbitrary rigid body transformations in the reference frame of the magnetic resonance imaging (MRI) machine and that of the external tracking device. RESULTS: Large motions in the MRI reference frame can be measured using a sparse phantom with an accuracy of 0.2 mm, or approximately 1/10 of the voxel size. By using a dual quaternion algorithm to solve the calibration problem, a good camera calibration can be achieved with fewer than six measurements. Further refinements can be achieved by applying the method iteratively and using motion correction feedback. CONCLUSION: Independent tracking of a series of movements in two reference frames allows for an analytical solution to the hand-eye-calibration problem for various motion tracking setups in MRI.
Subject(s)
Artifacts , Fiducial Markers , Image Enhancement/instrumentation , Image Enhancement/methods , Magnetic Resonance Imaging/instrumentation , Magnetic Resonance Imaging/methods , Motion , Algorithms , Calibration , Equipment Design , Equipment Failure Analysis , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
PURPOSE: Respiration induced dynamic field map changes in the brain are quantified and the influence on the magnitude signal (physiological noise) is investigated. Dynamic off-resonance correction allows to reduce the signal fluctuations overlaying the blood oxygenation level dependent signal in T2*-weighted functional imaging. THEORY AND METHODS: A single-shot whole brain imaging technique with 100 ms temporal resolution was used to measure dynamic off-resonance maps that were calculated from the incremental changes of the image phase. These off-resonance maps are then used to dynamically update the off-resonance corrected reconstruction. RESULTS: A global resonance offset and a pronounced gradient in head-foot direction were identified as the main components of the change during a respiration cycle. On average, correction for these fluctuations decreases the magnitude fluctuations by around 30%. CONCLUSION: Single shot 3D imaging allows for a robust quantification of dynamic off-resonance changes in the brain. Correction for these fluctuations removes the physiological noise component associated with dynamic point spread function changes.
Subject(s)
Artifacts , Brain Mapping/methods , Brain/physiopathology , Magnetic Resonance Imaging/methods , Respiratory Mechanics , Respiratory-Gated Imaging Techniques/methods , Algorithms , Humans , Image Enhancement/methods , Imaging, Three-Dimensional/methods , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
Current resting-state network analysis often looks for coherent spontaneous BOLD signal fluctuations at frequencies below 0.1 Hz in a multiple-minutes scan. However hemodynamic signal variation can occur at a faster rate, causing changes in functional connectivity at a smaller time scale. In this study we proposed to use MREG technique to increase the temporal resolution of resting-state fMRI. A three-dimensional single-shot concentric shells trajectory was used instead of conventional EPI, with a TR of 100 ms and a nominal spatial resolution of 4 × 4 × 4 mm(3). With this high sampling rate we were able to resolve frequency components up to 5 Hz, which prevents major physiological noises from aliasing with the BOLD signal of interest. We used a sliding-window method on signal components at different frequency bands, to look at the non-stationary connectivity maps over the course of each scan session. The aim of the study paradigm was to specifically observe visual and motor resting-state networks. Preliminary results have found corresponding networks at frequencies above 0.1 Hz. These networks at higher frequencies showed better stability in both spatial and temporal dimensions from the sliding-window analysis of the time series, which suggests the potential of using high temporal resolution MREG sequences to track dynamic resting-state networks at sub-minute time scale.
Subject(s)
Brain Mapping/methods , Brain/physiology , Magnetic Resonance Imaging/methods , Neural Pathways/physiology , Rest/physiology , Adult , Female , Humans , Image Interpretation, Computer-Assisted/methods , Male , Middle Aged , Young AdultABSTRACT
MR-encephalography allows the observation of functional signal in the brain at a frequency of 10 Hz, permitting filtering of physiological "noise" and the detection of single event activations. High temporal resolution is achieved by the use of undersampled non-Cartesian trajectories, parallel imaging and regularized image reconstruction. MR-encephalography is based on 3D-encoding, allowing undersampling in two dimensions and providing advantages in terms of signal to noise ratio. Long readout times, which are necessary for single shot whole brain imaging (up to 75 ms), cause off-resonance artifacts. To meet this issue, a spherical stack of spirals trajectory is proposed in this work. By examining the trajectories in local k-space, it is shown that in areas of strong susceptibility gradients spatial information is fundamentally lost, making a meaningful image reconstruction impossible in the affected areas. It is shown that the loss of spatial information is reduced when using a stack of spirals trajectory compared to concentric shells.
Subject(s)
Brain/anatomy & histology , Magnetic Resonance Imaging/methods , Algorithms , Artifacts , Computer Simulation , Electromagnetic Fields , Humans , Image Processing, Computer-Assisted/methods , Imaging, Three-Dimensional , Signal-To-Noise Ratio , Whole Body ImagingABSTRACT
MR-encephalography is a technique that allows real-time observation of functional changes in the brain with a time-resolution of 100 ms. The high sampling rate is enabled by the use of undersampled image acquisition with regularized reconstruction. The article describes a novel imaging method for fast three-dimensional-MR-encephalography whole brain coverage based on undersampled, single-shot concentric shells trajectories and the use of multiple small receiver coils. The technique allows the observation of changes in blood oxygenation level dependent signal as a measure of brain physiology at very high temporal resolution.
Subject(s)
Brain Mapping/methods , Brain/physiology , Evoked Potentials/physiology , Image Interpretation, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging/methods , Humans , Image Enhancement/methods , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
MR-Encephalography (MREG) is a technique that allows real time observation of functional changes in the brain that appears within 100 msec. The high sampling rate is achieved at the cost of some spatial resolution. The article describes a novel imaging method for fast three-dimensional-MR-encephalography whole brain coverage based on rosette trajectories and the use of multiple small receiver coils. The technique allows the observation of changes in brain physiology at very high temporal resolution. A highly undersampled three-dimensional rosette trajectory is chosen, to perform single shot acquisition of k-space data within 23 msec. By using a 32-channel head coil array and regularized nonuniform Fourier transformation reconstruction, the spatial resolution is sufficient to detect even subtle centers of activation (e.g. human MT+). The method was applied to visual block design paradigms and compared with echo planar imaging-based functional MRI. As a proof-of-principle of the method's ability to detect local differences in the hemodynamic response functions, the analyzed MR-encephalography data revealed a spatially dependent delay of the arrival of the blood oxygenation level dependent response within the visual cortex.