Reducing inhomogeneity artifacts in functional MRI of human brain activation-thin sections vs gradient compensation

We evaluated two methods for correcting inhomogeneity-induced signal losses in magnetic resonance gradient-echo imaging that either use gradient compensation or simply acquire thin sections. The strategies were tested in the human brain in terms of achievable quality of T2*-weighted images at the level of the hippocampus and of functional activation maps of the visual cortex. Experiments were performed at 2.0 T and based on single-shot echo-planar imaging at 2. 0 x 2.0 mm(2) resolution, 4 mm section thickness, and 2.0 s temporal resolution. Gradient compensation involved a sequential 16-step variation of the refocusing lobe of the slice-selection gradient (TR/TE = 125/53 ms, flip angle 15 degrees ), whereas thin sections divided the 4-mm target plane into either four 1-mm or eight 0.5-mm interleaved multislice acquisitions (TR/TE = 2000/54 ms, flip angle 70 degrees ). Both approaches were capable of alleviating the inhomogeneity problem for structures in the base of the brain. When compared to standard 4-mm EPI, functional mapping in the visual cortex was partially compromised because of a lower signal-to-noise ratio of inhomogeneity-corrected images by either method. Relative to each other, consistently better results were obtained with the use of contiguous thin sections, in particular for a thickness of 1 mm. Multislice acquisitions of thin sections require minimal technical adjustments.     

The cost of parallel imaging in functional MRI of the human brain

While the advantages of parallel acquisition techniques for echo-planar imaging (EPI) are well documented for studies affected by magnetic field inhomogeneities, this work focuses on the costs in functional MRI of brain regions without artifacts due to susceptibility effects. For a visual stimulation paradigm and relative to conventional EPI (2.9 T; TR/TE=2000/36 ms), the use of parallel acquisition at a reduction factor of 2 decreased the mean number of activated voxels by 21% at 2 x 2 x 2-mm(3) resolution (n=6) and by 15% at 3 x 3 x 3-mm(3) resolution (n=6). The loss of sensitivity reflects both a decreased signal-to-noise ratio of the native images due to a lower number of contributing gradient echoes and a decreased BOLD MRI sensitivity due to the coverage of a smaller range of TEs.     

Echo-shifted multislice EPI for high-speed fMRI

The advantages of event-related functional Magnetic Resonance Imaging (fMRI) and the increasing use of fMRI in cognitive experiments are both driving the development of techniques that allow images sensitive to the blood oxygen level-dependent effect to be acquired at ever-higher temporal resolution. Here, we present a technique based on the use of echo shifting (ES) in conjunction with a multislice (MS) echo planar imaging (EPI) readout, which allows T2*-weighted images to be generated with a repetition time per slice that is less than the echo time (TE). Using this ES-MS-EPI approach, it is shown that images with a TE of 40 ms can be acquired with an acquisition time per slice of only 27 ms. The utility of the MS-ES-EPI sequence is demonstrated in a visual-motor, event-related fMRI study in which nine-slice image volumes are acquired continuously at a rate of 4.1 Hz. The sequence is shown to produce reliable activation associated with both visual stimuli and motor actions.     

False positive control of activated voxels in single fMRI analysis using bootstrap resampling in comparison to spatial smoothing

Functional magnetic resonance imaging (fMRI) is an effective tool for the measurement of brain neuronal activities. To date, several statistical methods have been proposed for analyzing fMRI datasets to select true active voxels among all the voxels appear to be positively activated. Finding a reliable and valid activation map is very important and becomes more crucial in clinical and neurosurgical investigations of single fMRI data, especially when pre-surgical planning requires accurate lateralization index as well as a precise localization of activation map.Defining a proper threshold to determine true activated regions, using common statistical processes, is a challenging task. This is due to a number of variation sources such as noise, artifacts, and physiological fluctuations in time series of fMRI data which affect spatial distribution of noise in an expected uniform activated region. Spatial smoothing methods are frequently used as a preprocessing step to reduce the effect of noise and artifacts. The smoothing may lead to a shift and enlargement of activation regions, and in some extend, unification of distinct regions.In this article, we propose a bootstrap resampling technique for analyzing single fMRI dataset with the aim of finding more accurate and reliable activated regions. This method can remove false positive voxels and present high localization accuracy in activation map without any spatial smoothing and statistical threshold setting.     

Increased BOLD sensitivity in the orbitofrontal cortex using slice-dependent echo times at 3 T

Functional magnetic resonance imaging (fMRI) exploits the blood oxygenation level dependent (BOLD) effect to detect neuronal activation related to various experimental paradigms. Some of these, such as reversal learning, involve the orbitofrontal cortex and its interaction with other brain regions like the amygdala, striatum or dorsolateral prefrontal cortex. These paradigms are commonly investigated with event-related methods and gradient echo-planar imaging (EPI) with short echo time of 27 ms. However, susceptibility-induced signal losses and image distortions in the orbitofrontal cortex are still a problem for this optimized sequence as this brain region consists of several slices with different optimal echo times. An EPI sequence with slice-dependent echo times is suitable to maximize BOLD sensitivity in all slices and might thus improve signal detection in the orbitofrontal cortex. To test this hypothesis, we first optimized echo times via BOLD sensitivity simulation. Second, we measured 12 healthy volunteers using a standard EPI sequence with an echo time of 27 ms and a modified EPI sequence with echo times ranging from 22 ms to 47 ms. In the orbitofrontal cortex, the number of activated voxels increased from 87±44 to 549±83 and the maximal t-value increased from 4.4±0.3 to 5.4±0.3 when the modified EPI was used. We conclude that an EPI with slice-dependent echo times may be a valuable tool to mitigate susceptibility artifacts in event-related whole-brain fMRI studies with a focus on the orbitofrontal cortex.     

Effects of spatial smoothing on fMRI group inferences

The analysis of functional magnetic resonance imaging (fMRI) data involves multiple stages of data pre-processing before the activation can be statistically detected. Spatial smoothing is a very common pre-processing step in the analysis of functional brain imaging data. This study presents a broad perspective on the influence of spatial smoothing on fMRI group activation results. The data obtained from 20 volunteers during a visual oddball task were used for this study. Spatial smoothing using an isotropic gaussian filter kernel with full width at half maximum (FWHM) sizes 2 to 30 mm with a step of 2 mm was applied in two levels — smoothing of fMRI data and/or smoothing of single-subject contrast files prior to general linear model random-effects group analysis generating statistical parametric maps. Five regions of interest were defined, and several parameters (coordinates of nearest local maxima, t value, corrected threshold, effect size, residual values, etc.) were evaluated to examine the effects of spatial smoothing. The optimal filter size for group analysis is discussed according to various criteria. For our experiment, the optimal FWHM is about 8 mm. We can conclude that for robust experiments and an adequate number of subjects in the study, the optimal FWHM for single-subject inference is similar to that for group inference (about 8 mm, according to spatial resolution). For less robust experiments and fewer subjects in the study, a higher FWHM would be optimal for group inference than for single-subject inferences.     

Optimizing T2-weighted magnetic resonance sequences for surface coil microimaging of the eye with regard to lid, eyeball and head moving artifacts

PURPOSE: To acquire high-resolution magnetic resonance (MR) images, we developed a new blinking artifact reduced pulse (BARP) sequence with a surface coil specialized for microscopic imaging (47 mm in diameter). MATERIALS AND METHODS: To reduce eye movement, we ascertained that the subjects' eyes were kept open and fixated to the target in the 1.5-T MR gantry. To reduce motion artifacts from blinking, we inserted rest periods for blinking (1.5 s within every 5 s) during MR scanning (T2-weighted fast spin echo; repetition time, 5 s; echo time, 100 ms; echo train, 11; matrix, 256 x 128; field of view, 5 cm; 1-mm thickness x 30 slices). Three scans (100 s x 3) were performed for each normal subject, and they were added together after automatic adjustment for location to reduce quality loss caused by head motion. RESULTS: T2-weighted MR images were acquired with a high resolution and a high signal-to-noise ratio. Motion artifacts were reduced with BARP, as compared with those with random blinking. Intraocular structures such as the iris and ciliary muscles were clearly visualized. Because the whole eye can be covered with a 1-mm thickness by this method, three-dimensional maps can easily be generated from the obtained images. CONCLUSION: The application of BARP with a surface coil of the human eye might become a useful and widely adopted procedure for MR microimaging.     

Evaluation and optimization of fMRI single-subject processing pipelines with NPAIRS and second-level CVA

In functional magnetic resonance imaging (fMRI) analysis, although the univariate general linear model (GLM) is currently the dominant approach to brain activation detection, there is growing interest in multivariate approaches such as principal component analysis, canonical variate analysis (CVA), independent component analysis and cluster analysis, which have the potential to reveal neural networks and functional connectivity in the brain. To understand the effect of processing options on performance of multivariate model-based fMRI processing pipelines with real fMRI data, we investigated the impact of commonly used fMRI preprocessing steps and optimized the associated multivariate CVA-based, single-subject processing pipelines with the NPAIRS (nonparametric prediction, activation, influence and reproducibility resampling) performance metrics [prediction accuracy and statistical parametric image (SPI) reproducibility] on the Fiswidgets platform. We also compared the single-subject SPIs of univariate GLM with multivariate CVA-based processing pipelines from SPM, FSL.FEAT, NPAIRS.GLM and NPAIRS.CVA software packages (or modules) using a novel second-level CVA. We found that for the block-design data, (a) slice timing correction and global intensity normalization have little consistent impact on the fMRI processing pipeline, but spatial smoothing, temporal detrending or high-pass filtering, and motion correction significantly improved pipeline performance across all subjects; (b) the combined optimization of spatial smoothing, temporal detrending and CVA model parameters on average improved between-subject reproducibility; and (c) the most important pipeline choices include univariate or multivariate statistical models and spatial smoothing. This study suggests that considering options other than simply using GLM with a fixed spatial filter may be of critical importance in determining activation patterns in BOLD fMRI studies.     

A simple and fast technique for on-line fMRI data analysis

In the present work a simple technique for fMRI data analysis is presented. Artifacts due to random and stimulus-correlated motions are corrected without image registration procedures. The first step of our procedure is the calculation of the raw activation map by correlation analysis. The task related motion artifacts arise at the tissue interfaces, including vessels: when image intensity gradient is calculated the high values correspond to interface regions. To eliminate stimulus-correlated motion artifacts the intensity gradient image, obtained from the fMRI data set, is compared to the raw activation map. Since small random motions decrease the value of the correlation coefficient (R) of the external pixels of the activation areas, in the last step of our analysis procedures the clusters are extended to connected pixels having R values smaller than the defined threshold. Each cluster is expanded until the R value of the cluster average intensity is kept constant. The procedure has been tested with both GRE and EPI studies. The presented approach is a fast and robust technique useful for preliminary or on-line analysis of fMRI data.     

Synthetic signal injection using inductive coupling

The limited bandwidths of volume selective RF pulses in localized in vivo MRS experiments introduce spatial artifacts that complicate spectral quantification of J-coupled metabolites. These effects are commonly referred to as a spatial interference or "four compartment" artifacts and are more pronounced at higher field strengths. The main focus of this study is to develop a generalized approach to numerical simulations that combines full density matrix calculations with 3D localization to investigate the spatial artifacts and to provide accurate prior knowledge for spectral fitting. Full density matrix calculations with 3D localization using experimental pulses were carried out for PRESS (TE=20, 70 ms), STEAM (TE=20, 70 ms) and LASER (TE=70 ms) pulse sequences and compared to non-localized simulations and to phantom solution data at 4 T. Additional simulations at 1.5 and 7 T were carried out for STEAM and PRESS (TE=20 ms). Four brain metabolites that represented a range from weak to strong J-coupling networks were included in the simulations (lactate, N-acetylaspartate, glutamate and myo-inositol). For longer TE, full 3D localization was necessary to achieve agreement between the simulations and phantom solution spectra for the majority of cases in all pulse sequence simulations. For short echo time (TE=20 ms), ideal pulses without localizing gradients gave results that were in agreement with phantom results at 4 T for STEAM, but not for PRESS (TE=20). Numerical simulations that incorporate volume localization using experimental RF pulses are shown to be a powerful tool for generation of accurate metabolic basis sets for spectral fitting and for optimization of experimental parameters.     

Activation of area V5 by visual perception of motion demonstrated with echoplanar MR imaging

Cortical activation in visual association areas known to be responsible for the perception of motion was investigated in two volunteers who viewed a projected animated cartoon periodically “run” and “frozen” during collection of echoplanar MR images. Ten axial, contiguous, 5 mm thick, T₂-weighted, gradient-echo images (TE 40 ms, TR 3000 ms) depicting BOLD contrast were acquired through the occipital lobe using a GE Signa 1.5 T system with an advanced NMR operating console. Images were analysed by time series regression modelling estimating power in the MR signal at the ON-OFF frequency of motion. Highly significant activation in response to motion perception was identified in both subjects bilaterally in area V5.     

A conditional Granger causality model approach for group analysis in functional magnetic resonance imaging

Granger causality model (GCM) derived from multivariate vector autoregressive models of data has been employed to identify effective connectivity in the human brain with functional magnetic resonance imaging (fMRI) and to reveal complex temporal and spatial dynamics underlying a variety of cognitive processes. In the most recent fMRI effective connectivity measures, pair-wise GCM has commonly been applied based on single-voxel values or average values from special brain areas at the group level. Although a few novel conditional GCM methods have been proposed to quantify the connections between brain areas, our study is the first to propose a viable standardized approach for group analysis of fMRI data with GCM. To compare the effectiveness of our approach with traditional pair-wise GCM models, we applied a well-established conditional GCM to preselected time series of brain regions resulting from general linear model (GLM) and group spatial kernel independent component analysis of an fMRI data set in the temporal domain. Data sets consisting of one task-related and one resting-state fMRI were used to investigate connections among brain areas with the conditional GCM method. With the GLM-detected brain activation regions in the emotion-related cortex during the block design paradigm, the conditional GCM method was proposed to study the causality of the habituation between the left amygdala and pregenual cingulate cortex during emotion processing. For the resting-state data set, it is possible to calculate not only the effective connectivity between networks but also the heterogeneity within a single network. Our results have further shown a particular interacting pattern of default mode network that can be characterized as both afferent and efferent influences on the medial prefrontal cortex and posterior cingulate cortex. These results suggest that the conditional GCM approach based on a linear multivariate vector autoregressive model can achieve greater accuracy in detecting network connectivity than the widely used pair-wise GCM, and this group analysis methodology can be quite useful to extend the information obtainable in fMRI.     

Functional MR imaging of visual and motor cortex stimulation at high temporal resolution using a flash technique on a standard 1.5 tesla scanner

Functional magnetic resonance imaging (fMRI) was performed on a conventional 1.5 T scanner by means of a modified FLASH-technique at temporal resolutions of 80 and 320 ms. The method's stability was assessed by phantom measurements and by investigation of three volunteers resulting in a low amplitude (3%) periodic (4 s) signal modulation for the in vivo measurements, which was not observable in the phantom experiments. fMRI activation studies of motor and visual cortices of four adjacent slices were carried out on 12 healthy right-handed volunteers. Stimulation was performed by a triggered single white light flash or single finger-to-thumb opposition movement, respectively. Event-related response of visual and motor activation was traced over 10.24 s with a temporal resolution of 320 ms for the four slice measurements. Brain activation maps were calculated by correlation of measured signal time courses with a time-shifted boxcar function. Activation was quantified by calculation of percentual signal change in relation to the baseline. Observed signal magnitudes were about 5–7% in visual and about 8–12% in primary motor cortex. While photic response was delayed by about 2 s, motor stimulation showed an instantaneous increase of the MR signal. MR signal responses for both stimuli had decayed completely after about 5 s. Our results show that event-related fMRI enables mapping of brain function at sufficient spatial resolution with a temporal resolution of up to 80 ms on a conventional scanner.     

Compensation of susceptibility-induced signal loss in echo-planar imaging for functional applications

Functional magnetic resonance imaging favors the use of multi-slice gradient-recalled echo-planar imaging due to its short image acquisition times, whole brain coverage and sensitivity to BOLD contrast. However, despite its advantages, gradient-recalled echo-planar imaging also is sensitive to static magnetic field gradients arising primarily from air-tissue interfaces. This can lead to image artifacts such as voxel shifts and complete signal loss. A method to recover signal loss by adjusting the refocusing gradient amplitude in the slice-select direction, preferably axially, is proposed. This method is implemented as an automated computer algorithm that partitions echo-planar images into regions of recoverable signal intensities using a histogram analysis and determines each region's proper refocusing gradient amplitude. As an example, different refocusing gradient amplitudes are interleaved in a fMRI acquisition to maximize the signal to noise ratio and obtain functional activation in normal and dropout regions. The effectiveness of this method is demonstrated by recovering signal voids in the orbitofrontal cortex, parahippocampal/amygdala region, and inferior visual association cortex near the cerebellum.     

Bayesian wavelet-based analysis of functional magnetic resonance time series

Wavelet methods for image regularization offer a data-driven alternative to Gaussian smoothing in functional magnetic resonance (fMRI) analysis. Their impact has been limited by the difficulties in integrating regularization in the wavelet domain and inference in the image domain, precluding the probabilistic decision on which areas are activated by a task. Here we present an integrated framework for Bayesian estimation and regularization in wavelet space that allows the usual voxelwise hypothesis testing. This framework is flexible, being an adaptation to fMRI time series of a more general wavelet-based functional mixed-effect model. Through testing on a combination of simulated and real fMRI data, we show evidence of improved signal recovery, without compromising test accuracy in image space.     

Functional magnetic resonance imaging in a stereotactic setup

The localization of critical structures within the brain is important for the planning of therapeutic strategies. Functional MRI is capable to assess functional response of cortical structures to certain stimuli. The authors present two techniques for functional MRI (fMRI) in a stereotactic set-up. The skull of the patients has been immobilized for stereotactic treatment planning either with a self developed stereotactic ceramic frame and bony fixation or with an individual precision mask system made of light cast. It has been shown that this frame does not produce any image distortion. fMRI was performed using a modified FLASH sequence on a conventional 1.5 T MRI scanner with a specially developed linear polarized head coil. The imaging technique used was an optimized conventional 2D and 3D, first order flow rephased, gradient echo sequence (FLASH) with fat-suppression and reduce bandwidth (16–28 Hz/pixel) and TR = 80–120 ms, TE = 60 ms, flip angle = 40°, matrix = 128 × 128, FOV = 150–250 mm, slice-thickness = 2–5 mm, NEX = 1, and a total single scan time for one image of about 7 sec. The motor cortex stimulation was achieved by touching each finger to thumb in a sequential, self-paced, and repetitive manner. Statistical parametric maps based on student's test were calculated. Pixels with a highly significant signal increase (p < 0.001) are overlaid on T1w SE images. The primary motor and sensory cortex could be visualized with this method in all 10 patients that were imaged in this study. Due to tight fixation of the patient's skull there have been no motion artifacts. These results show that functional MRI is feasible in an stereotactic set-up with an standard 1.5 T scanner. This is a prerequisite for the exact pre therapeutic assessment of the function of cortical centers.     

Sensitivity limitations of high-resolution perfusion-based human fMRI at 7 Tesla

The study of the brain's functional organization at laminar and columnar level of the cortex with blood oxygenation-level dependent (BOLD) functional MRI (fMRI) is affected by the contribution of large veins downstream from the microvascular response to brain activity. Blood volume- and especially perfusion-based techniques may reduce this problem because of their reduced sensitivity to venous effects, but may not allow the same spatial resolution because of smaller signal changes associated with brain activity. Here we investigated the practical resolution limits of perfusion-weighted fMRI in human visual stimulation experiments. For this purpose, we used a highly sensitive, single-shot perfusion labeling (SSPL) technique at 7 T and compared sensitivity to detect visual activation at low (2 mm, n = 10) and high (1 mm, n = 8) nominal isotropic spatial, and 3 s temporal, resolution with BOLD in 5½-minute-long experiments. Despite the smaller absolute signal change with activation, 2 mm resolution SSPL yielded comparable sensitivity to BOLD. This was attributed to a superior suppression of physiological noise with SSPL. However, at 1 mm nominal resolution, SSPL sensitivity fell on average at least 42% below that of BOLD, and detection of visual activation was compromised. This is explained by the fact that at high resolution, with both techniques, typically thermal noise rather than physiological noise dominates sensitivity. The observed sensitivity loss implies that to perform 1-mm resolution, perfusion weighted fMRI with a robustness similar to BOLD, scan times that are almost 3 times longer than the comparable BOLD experiment are required. This is in line with or slightly better than previous comparisons between perfusion-weighted fMRI and BOLD. The lower sensitivity has to be weighed against the spatial fidelity advantages of high-resolution perfusion-weighted fMRI.     

Fast T2-weighted MR imaging: impact of variation in pulse sequence parameters on image quality and artifacts

The purpose of this study was to quantitatively evaluate in a phantom model the practical impact of alteration of key imaging parameters on image quality and artifacts for the most commonly used fast T(2)-weighted MR sequences. These include fast spin-echo (FSE), single shot fast spin-echo (SSFSE), and spin-echo echo-planar imaging (EPI) pulse sequences. We developed a composite phantom with different T1 and T2 values, which was evaluated while stationary as well as during periodic motion. Experiments involved controlled variations in key parameters including effective TE, TR, echo spacing (ESP), receive bandwidth (BW), echo train length (ETL), and shot number (SN). Quantitative analysis consisted of signal-to-noise ratio (SNR), image nonuniformity, full-width-at-half-maximum (i.e., blurring or geometric distortion) and ghosting ratio. Among the fast T(2)-weighted sequences, EPI was most sensitive to alterations in imaging parameters. Among imaging parameters that we tested, effective TE, ETL, and shot number most prominently affected image quality and artifacts. Short T(2) objects were more sensitive to alterations in imaging parameters in terms of image quality and artifacts. Optimal clinical application of these fast T(2)-weighted imaging pulse sequences requires careful attention to selection of imaging parameters.     

Functional MR imaging in the awake monkey: effects of motion on dynamic off-resonance and processing strategies

Functional MR imaging of the alert, behaving monkey is being used more and more often to detect activation patterns and guide electrophysiological research investigating the neural basis of behavior. Several labs have reported fMRI data from the awake monkey, but none of them has studied and systematically corrected the effects of monkeys' motion on fMRI time series. In this study, a significant refinement of acquisition and correction strategies is reported that can be used to minimize magnetic susceptibility artifacts induced by respiration and by jaw and body movement. Real-time acquisition of sensor signals (e.g., signals induced by jaw and body movement) and MR navigator data were combined to optimize fMRI signal-correction strategies. Within trials, the artifact-induced off-resonance changes were small and mainly reflected the effects of respiration; between trials, movements caused major changes of global frequency and shim (>20 Hz/cm). Several methods were used to assess the stability of the fMRI series: k-space analysis ('dynamic intensity and off-resonance changes in k-space', dubbed DICK and DORK) and image analysis using a Laplace operator and a center-of-mass metric. The variability between trials made it essential to correct for inter-trial variations. On the other hand, images were sufficiently stable with our approach to perform fMRI evaluations on single trials before averaging of trials. Different motion correction strategies were compared: DORK, McFLIRT (rigid body model with three translations and three rotations) and 2D image alignment based on a center-of-mass detection (in-plane translation). The latter yielded the best results and proved to be fast and robust for intra- and inter-trial alignment. Finally, fMRI in the behaving monkey was tested for spatial and temporal reproducibility on a trial-to-trial basis. Highly activated voxels also displayed good reproducibility between trials. On average, the BOLD amplitude response to a short 3-s visual stimulus was close to 2%.     

Functional MRI of the human motor cortex using single-shot, multiple gradient-echo spiral imaging

In this study, we combined the advantages of a fast multi-slice spiral imaging approach with a multiple gradient-echo sampling scheme at high magnetic field strength to improve quantification of BOLD and inflow effects and to estimate T2* relaxation times in functional brain imaging. Eight echoes are collected with echo time (TE) ranging from 5 to 180 ms. Acquisition time per slice and echo time is 25 ms for a nominal resolution of 4 x 4 x 4 mm3. Evaluation of parameter images during rest and stimulation yields no significant activation on the inflow sensitive spin-density images (rho or I0-maps) whereas clear activation patterns in primary human motor cortex (M1) and supplementary motor area (SMA) are detected on BOLD sensitive T2*-maps. The calculation of relaxation times and rates of the activated areas over all subjects yields an average T2* +/- standard deviation (SD) of 46.1+/-4.5 ms (R2* of 21.8+/-2.2 s(-1)) and an average increase (deltaT2* +/- SD) of 0.93+/-0.47 ms (deltaR2* of -0.4+/-0.14 s(-1)). Our findings demonstrate the usefulness of a multiple gradient echo data acquisition approach in separating various vascular contributions to brain activation in fMRI.