High-resolution segmented EPI in a motor task fMRI study

A high-resolution gradient echo, multi-slice segmented echo planar imaging method was used for functional MRI (fMRI) using a motor task at 1.5 Tesla. Functional images with an in-plane resolution of 1 mm and slice thickness of 4 mm were obtained with good white-gray matter contrast. The multi-shot approach, combined with a short total readout period of 82 ms, limits blurring effects for short T(2)(*) tissues (such as gray matter), assuring truly high-resolution images. In all subjects, motor functions were clearly depicted in the contralateral central sulcus over several slices and sometimes activation was detected in the supplementary motor area and/or ipsilateral central sulcus. The average signal change of 11+/-3% was much higher than in standard low-resolution fMRI EPI experiments, as a result of larger relative blood fractions.     

Improving the resolution of functional brain imaging: analyzing functional data in anatomical space

The accurate mapping of functional magnetic resonance imaging (fMRI) activations to anatomical structures is critical for fMRI studies of brain organization. In the commonly used functional space analysis method, functional images are realigned to a functional reference image and processed in low-resolution functional space. The average functional activations are then projected into high-resolution anatomical space for visualization. Here, we describe a new technique, anatomical space analysis (ASA), whereby low-resolution functional images are first coregistered and resampled directly into high-resolution anatomical space with all subsequent data processing performed in high-resolution space. A major advantage of ASA is that minor scanner sampling instabilities and small head movements can increase spatial resolution by providing multiple samples of the relationship between functional and anatomical space. Both simulations and analyses of real fMRI data show that ASA improves the precision, objectivity and reproducibility of functional brain mapping.     

Quantitative NumART2* mapping in functional MRI studies at 1.5 T

Quantitative mapping of the effective transverse relaxation time, T₂* and proton density was performed in a motor activation functional MRI (fMRI) study using multi-echo, echo planar imaging (EPI) and NumART₂* (Numerical Algorithm for Real time T₂*). Comparisons between NumART₂* and conventional single echo EPI with an echo time of 64 ms were performed for five healthy participants examined twice. Simulations were also performed to address specific issues associated with the two techniques, such as echo time-dependent signal variation. While the single echo contrast varied with the baseline T₂* value, relative changes in T₂* remained unaffected. Statistical analysis of the T₂* maps yielded fMRI activation patterns with an improved statistical detection relative to conventional EPI but with less activated voxels, suggesting that NumART₂* has superior spatial specificity. Two effects, inflow and dephasing, that may explain this finding were investigated. Particularly, a statistically significant increase in proton density was found in a brain area that was detected as activated by conventional EPI but not by NumART₂* while no such changes were observed in brain areas that showed stimulus correlated signal changes on T₂* maps.     

Functional MRI of the motor cortex using a conventional gradient system: comparison of FLASH and EPI techniques

Gradient echo (GE) and echo planar imaging (EPI) techniques are two different approaches to functional MRI (fMRI). In contrast to GE sequences, the ultra short EPI technique facilitates fMRI experiments with high spatial and temporal resolution or mapping of the whole brain. Although it has become the method of choice for fMRI, EPI is generally restricted to modern scanners with a strong gradient system. The aim of our study was to evaluate the applicability of EPI for fMRI of the motor cortex using a 1.5 T scanner with a conventional gradient system of 10 mT/m (rise time: 1 ms). Therefore, EPI was compared with a well-established high resolution fast low angle shot (FLASH) technique (matrix size 128²). The FLASH technique was applied additionally with a 64² matrix size to exclude influences caused by different spatial resolution, because the EPI sequence was restricted to a 64² matrix size. A total of 35 healthy volunteers were included in this study. The task consisted of clenching and spreading of the right hand. FLASH and EPI techniques were compared regarding geometric distortions as well as qualitative and quantitative fMRI criteria: Mean signal increase between activation and rest and the area of activation were measured within the contralateral, ipsilateral, and supplementary motor cortex. The quality of subtraction images between activation and rest, as well as the quality of z-maps and time course within activated regions of interest, was evaluated visually. EPI revealed significant distortions of the anterior and postior brain margins; lateral distortions (relevant for the motor cortex) could be neglected in most cases. The mean signal increase was significantly higher using FLASH 128² compared to FLASH 64² and EPI 64², whereas the activated areas proved to be smaller in FLASH 128² functional images. Both results can be explained by well-documented partial volume effects, caused by different voxel size. Similar quality of the subtraction images and of the time courses in different regions of interest were found for all techniques under investigation, but slightly reduced quality of z-map in FLASH 128². Within the limits of reproducibility and measurement accuracy, the location of contralateral activation was similar using FLASH and EPI sequences. In conclusion, EPI proved to be a reliable technique for fMRI of the motor cortex, even on an MR scanner with a conventional gradient system.     

Comparison of functional MR-venography and EPI-BOLD fMRI at 1.5 t

Functional magnetic resonance imaging (fMRI) of the brain using blood oxygenation level dependent (BOLD) contrast relies on the changes of paramagnetic deoxyhemoglobin concentration, which affects brain parenchyma and draining venous vessels. These changes in deoxyhemoglobin concentration in venous vessels can also be monitored using a high-resolution susceptibility-based MR-venography technique. Four volunteers participated in the study in which functional MR-venograms were compared with conventional echo-planar imaging (EPI)-BOLD-fMRI. In all cases, small venous vessels could be identified close to the areas of activation detected by conventional fMRI. In the venograms, task performance (finger tapping) resulted in a loss of venous vessel contrast compared to the resting state, which is consistent with a local decrease of deoxyhemoglobin concentration. MR-venography allows a direct visualization of the BOLD-effect at high spatial resolution. In combination with conventional fMRI, this technique may help to separate the contribution of brain parenchyma and venous vessels in fMRI studies.     

Discussion on the choice of separated components in fMRI data analysis by spatial independent component analysis

By measuring the changes of magnetic resonance signals during a stimulation, the functional magnetic resonance imaging (fMRI) is able to localize the neural activation in the brain. In this report, we discuss the fMRI application of the spatial independent component analysis (spatial ICA), which maximizes statistical independence over spatial images. Included simulations show the possibility of the spatial ICA on discriminating asynchronous activations or different response patterns in an fMRI data set. An in vivo visual stimulation fMRI test was conducted, and the result shows a proper sum of the separated components as the final image is better than a single component, using fMRI data analysis by spatial ICA. Our result means that spatial ICA is a useful tool for the detection of different response activations and suggests that a proper sum of the separated independent components should be used for the imaging result of fMRI data processing.     

Functional magnetic resonance imaging of awake monkeys: some approaches for improving imaging quality

Functional magnetic resonance imaging (fMRI) at high magnetic field strength can suffer from serious degradation of image quality because of motion and physiological noise, as well as spatial distortions and signal losses due to susceptibility effects. Overcoming such limitations is essential for sensitive detection and reliable interpretation of fMRI data. These issues are particularly problematic in studies of awake animals. As part of our initial efforts to study functional brain activations in awake, behaving monkeys using fMRI at 4.7 T, we have developed acquisition and analysis procedures to improve image quality with encouraging results.We evaluated the influence of two main variables on image quality. First, we show how important the level of behavioral training is for obtaining good data stability and high temporal signal-to-noise ratios. In initial sessions, our typical scan session lasted 1.5 h, partitioned into short (<10 min) runs. During reward periods and breaks between runs, the monkey exhibited movements resulting in considerable image misregistrations. After a few months of extensive behavioral training, we were able to increase the length of individual runs and the total length of each session. The monkey learned to wait until the end of a block for fluid reward, resulting in longer periods of continuous acquisition. Each additional 60 training sessions extended the duration of each session by 60 min, culminating, after about 140 training sessions, in sessions that last about 4 h. As a result, the average translational movement decreased from over 500 μm to less than 80 μm, a displacement close to that observed in anesthetized monkeys scanned in a 7-T horizontal scanner.Another major source of distortion at high fields arises from susceptibility variations. To reduce such artifacts, we used segmented gradient-echo echo-planar imaging (EPI) sequences. Increasing the number of segments significantly decreased susceptibility artifacts and image distortion. Comparisons of images from functional runs using four segments with those using a single-shot EPI sequence revealed a roughly twofold improvement in functional signal-to-noise-ratio and 50% decrease in distortion. These methods enabled reliable detection of neural activation and permitted blood-oxygenation-level-dependent-based mapping of early visual areas in monkeys using a volume coil.In summary, both extensive behavioral training of monkeys and application of segmented gradient-echo EPI sequence improved signal-to-noise ratio and image quality. Understanding the effects these factors have is important for the application of high field imaging methods to the detection of submillimeter functional structures in the awake monkey brain.     

High-resolution diffusion imaging using phase-corrected segmented echo-planar imaging

Diffusion magnetic resonance imaging (MRI) was performed with a high-resolution segmented echo-planar imaging technique, which provided images with substantially less susceptibility artifacts than images obtained with single-shot echo-planar imaging (EPI). Diffusion imaging performed with any multishot pulse sequence is inherently sensitive to motion artifacts and in order to reduce motion artifacts, the presented method utilizes navigator echo phase corrections, performed after a one-dimensional Fourier transform along the frequency-encoding direction. Navigator echo phases were fitted to a straight line prior to phase correction to avoid errors from internal motion. In vivo imaging was performed using electro cardiographic (ECG) triggering. Apparent diffusion coefficient (ADC) maps were calculated on a pixel-by-pixel basis using up to seven diffusion sensitivities, ranging from b = 0 to 1129 x 10(6) s/m(2).     

小动物高分辨扩散加权成像在临床 MRI 上的实现

在临床用MRI系统上对小动物扩散加权成像一般采用回波平面成像序列,但是回波平面成像易受偏共振效应的影响,得到的图像伪影大、几何变形严重、图像分辨率低,无法探究微小的生物组织结构. 该文报道了在临床用3 T MRI系统上采用自旋回波序列实现了高分辨扩散加权成像. 为减少运动伪影,序列中整合了导航回波矫正技术. 对脑缺血模型大鼠脑部的扫描结果显示,自旋回波扩散加权序列获得的图像基本没有发生形变,并且具有较高的分辨率和较好的信噪比.     

Distortion correction for a double inversion-recovery sequence with an echo-planar imaging readout

A double inversion-recovery (DIR) sequence with an echo-planar imaging (EPI) readout can be used to image selectively the grey matter of the brain, and this has previously been applied to improve the sensitivity of the statistical analysis of functional magnetic resonance imaging (fMRI) data. If a procedure were to be implemented to remove the distortions that are inherent in the EPI-based fMRI data set, then a similar technique would have to be applied to the DIR-EPI image also to ensure that it matches the geometry of the functional data. A comparison of candidate methodologies for correcting distortions in DIR-EPI images, based on the reversed-gradient method, is presented. A corrected image could be calculated from two DIR-EPI images acquired with k-space traversal in opposite directions, but that method was not able to cope with the large regions of low signal intensity corresponding to the nulled white matter. It was found that the optimal procedure to apply the reversed-gradient method to DIR-EPI images was to acquire two additional EPI images (without the two inversion pulses) with opposite-direction k-space traversal; the distortion-correction information calculated from those EPI images was then applied to the DIR-EPI data.     

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.     

Fast spectroscopic imaging strategies for potential applications in fMRI

Technical aspects of two general fast spectroscopic imaging (SI) strategies, one based on gradient echo trains and the other on spin echo trains, are reviewed within the context of potential applications in the field of functional magnetic resonance imaging (fMRI). Fast spectroscopic imaging of water may prove useful for identifying mechanisms underlying the blood oxygenation level dependence (BOLD) of the water signal during brain activation studies. Reasonably rapid mapping of changes in proton signals from brain metabolites, like lactate, creatine or even neurotransmitter associated metabolites like GABA, is substantially more challenging but technically feasible particularly as higher field strengths become available. Fast spectroscopic methods directed towards the ³¹P signals from phosphocreatine (PCr) and adenosine tri-phosphates (ATP) are also technically feasible and may prove useful for studying cerebral energetics within fMRI contexts.     

High-resolution, multiple gradient-echo functional MRI at 1.5 T

A multiple gradient echo, high resolution imaging method is proposed to better visualize different sources of activation in functional magnetic resonance imaging (fMRI) experiments. Eight echoes are collected from 30 ms to 205 ms with an echo spacing of 25 ms. All echoes show significant activation, but each echo reveals its own pattern of activation. From this variability, it appears that large vessel contributions can be separated from small vessel contributions using a fuzzy cluster analysis across echo times. The results demonstrate the importance of a multiple gradient echo data acquisition approach in localizing various vascular contributions to brain activation in fMRI.     

Functional magnetic resonance imaging reference phantom

Functional magnetic resonance imaging (fMRI) is widely used to pinpoint active brain areas. Changes in neuronal activity modulate the local blood oxygenation level, and the associated modulation of the magnetic field homogeneity can be detected with magnetic resonance imaging. Thus, the blood oxygenation level-dependent (BOLD) fMRI indirectly measures neuronal activity. Similar modulation of magnetic field homogeneity was here elicited by other means to generate a BOLD-like change in a new phantom constructed to provide reference activations during fMRI. Magnetic inhomogeneities were produced by applying current to coils located near the phantom containing 1.5 ml of Gd-doped water. The signal-to-noise ratio of the images, produced by gradient-recalled echo-planar imaging, varied between 104 and 107 at a selected voxel when the field was and was not inhomogenized, respectively. The contrast of signals between homogeneous and inhomogeneous conditions was generally stable, except in 3% of time points. During the periods of greatest deviations an observable change would have been detected in a simultaneously measured BOLD signal. Such changes could result from the imaging method or occur through glitches in hardware or alterations in the measurement environment. With identical measurement setups, the phantom could allow comparing intersession or intersubject brain activations.     

Functional magnetic resonance imaging of tonic pain and vasopressor effects in rats

In functional magnetic resonance imaging (fMRI) studies, an elevation in blood pressure (BP) in individuals with a poor autoregulatory response may increase cerebral blood flow, potentially enhancing the blood oxygenation level dependent response. To investigate the role of BP changes, the cerebral activation to either tonic pain or the infusion of the vasopressor norepinephrine was correlated with the accompanying BP changes in alpha-chloralose anesthetized rats. Immediately after formalin (2%) injection into the forepaw, fMRI detected an activation that was correlated with the BP increase and additional activations that were independent of blood pressure changes 5–40 minutes later. The activation detected with the administration of the vasopressor norepinephrine, which does not cross the blood-brain barrier was correlated to both the amount and rate of increase in BP. The response ranged from being sparse, localized within cortex or widespread during modest, moderate or severe elevations in BP, respectively. The cerebral circulatory effects of hypertension should be considered as contributing to changes in cerebral blood oxygenation in fMRI studies involving increases in BP.     

Preoperative fast MRI of brain tumors using three-dimensional segmented echo planar imaging compared to three-dimensional gradient echo technique

The purpose of this study was to compare the diagnostic efficacy of a newly developed T(1)-weighted three-dimensional segmented echo planar imaging (3D EPI) sequence versus a conventional T(1)-weighted three dimensional spoiled gradient echo (3D GRE) sequence in the evaluation of brain tumors. Forty-four patients with cerebral tumors and infections were examined on a 1.0 T MR unit with 23 mT/m gradient strength. The total scan time for the T(1) 3D EPI sequence was 2 min 12 s, and for a conventional 3D GRE sequence it was 4 min 59 s. Both sequences were performed after administration of a contrast agent. The images were analyzed by three radiologists. Image assessment criteria included lesion conspicuity, contrast between different types of normal tissue, and image artifacts. In addition, signal-to-noise and contrast-to-noise-ratio (C/N) were calculated. The gray-white differentiation and C/N ratio of 3D EPI were found to be inferior to conventional 3D GRE images, but the difference was not statistically significant. In the qualitative comparison, lesion detection and conspicuity of 3D EPI images and conventional 3D GRE images were similar, but a tow-fold reduction of the scanning time was obtained. With the 3D EPI technique, a 50% scan time reduction could be achieved with acceptable image quality compared to conventional 3D GRE. Thus, the 3D EPI technique could replace conventional 3D GRE in the preoperative imaging of brain.     

Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas

In previous works, boosting aggregation of classifier outputs from discrete brain areas has been demonstrated to reduce dimensionality and improve the robustness and accuracy of functional magnetic resonance imaging (fMRI) classification. However, dimensionality reduction and classification of mixed activation patterns of multiple classes remain challenging. In the present study, the goals were (a) to reduce dimensionality by combining feature reduction at the voxel level and backward elimination of optimally aggregated classifiers at the region level, (b) to compare region selection for spatially aggregated classification using boosting and partial least squares regression methods and (c) to resolve mixed activation patterns using probabilistic prediction of individual tasks. Brain activation maps from interleaved visual, motor, auditory and cognitive tasks were segmented into 144 functional regions. Feature selection reduced the number of feature voxels by more than 50%, leaving 95 regions. The two aggregation approaches further reduced the number of regions to 30, resulting in more than 75% reduction of classification time and misclassification rates of less than 3%. Boosting and partial least squares (PLS) were compared to select the most discriminative and the most task correlated regions, respectively. Successful task prediction in mixed activation patterns was feasible within the first block of task activation in real-time fMRI experiments. This methodology is suitable for sparsifying activation patterns in real-time fMRI and for neurofeedback from distributed networks of brain activation.     

Quantifying and Comparing Region-of-Interest Activation Patterns in Functional Brain MR Imaging: Methodology Considerations

The general aims of functional brain magnetic resonance imaging (fMRI) studies are to ascertain which areas of the brain are activated during a specific task, the extent of this activation, whether different groups of subjects demonstrate different patterns of activation, and how these groups behave in different tasks. Many steps are involved in answering such questions and if each step is not carefully controlled the results may be influenced. This work has three objectives. Firstly, to present a technique for quantitatively evaluating methods used in functional imaging data analysis. While receiver-operator-characteristic (ROC) analysis has been used effectively to evaluate the ability of post-processing algorithms to detect true activations while rejecting false activations, it is difficult to adapt such a technique for comparisons of methods for quantitating activations. We present a technique based on the ANOVA, between two or more regions of interest (ROIs), subject groups, or activation tasks, over a range of statistical thresholds, which reveals the sensitivity of different activation quantification metrics to noise and other variables. Secondly, we use this technique to compare two methods of quantifying localized brain activation. There are numerous ways of quantifying the amount of activation present in a specific region of the brain in an individual subject. We compare the pixel count approach, which simply counts the number of pixels above an arbitrary statistical threshold, with an approach based on the sum of t-values above the same arbitrary t-value threshold. Finally, we examine the sensitivity of the results from an analysis of variance, to user defined parameters such as threshold and region of interest size. Both simulated and real functional magnetic resonance data are used to demonstrate these techniques.     

Accurate and sensitive measurements of magnetic susceptibility using echo planar imaging

Susceptibility differences are common causes for artifacts in magnetic resonance (MR); therefore, it is important to choose phantom materials in a way that these artifacts are kept at a minimum. In this study, a previously proposed MR imaging (MRI) method [Beuf O, Briguet A, Lissac M, Davis R. Magnetic resonance imaging for the determination of magnetic susceptibility of materials. J Magn Reson 1996; Series B(112):111-118] was improved to facilitate sensitive in-house measurements of different phantom materials so that such artifacts can more easily be minimized. Using standard MRI protocols and distilled water as reference, we measured magnetic volume susceptibility differences with a clinical MR system. Two imaging techniques, echo planar imaging (EPI) and spin echo, were compared using liquid samples whose susceptibilities were verified by MR spectroscopy. The EPI sequence has a very narrow bandwidth in the phase-encoding direction, which gives an increased sensitivity to magnetic field inhomogeneities. All MRI measurements were evaluated in two ways: (1) manual image analysis and (2) model fitting. The narrow bandwidth of the EPI made it possible to detect very small susceptibility differences (equivalent susceptibility difference, Deltachi(e)> or =0.02 ppm), and even plastics could be measured. Model fitting yielded high accuracy and high sensitivity and was less sensitive to other image artifacts as compared with manual image analysis.     

Derivative temporal clustering analysis: detecting prolonged neuronal activity

Temporal clustering analysis (TCA) and independent component analysis (ICA) are promising data-driven techniques in functional magnetic resonance imaging (fMRI) experiments to obtain brain activation maps in conditions with unknown temporal information regarding the neuronal activity. Although comparable to ICA in detecting transient neuronal activities, TCA fails to detect prolonged plateau brain activations. To eliminate this pitfall, a novel derivative TCA (DTCA) method was introduced and its algorithms with different subtraction intervals were tested on simulated data with a pattern of prolonged plateau brain activation. It was found that the best performance of DTCA method in generating functional maps could be obtained if the subtraction interval is equal to or larger than the length of the rising time of the fMRI response. The DTCA method and its theoretical predication were further investigated and validated using in vivo fMRI data sets. By removing the limitations in the previous TCA, DTCA has shown its powerful capability in detecting prolonged plateau neuronal activities.