Hemodynamic response (BOLD/fMRI) in focal epilepsy with reference to benzodiazepine effect

We studied a new procedure of BOLD/fMRI acquisition in epilepsy. They use the benzodiazepine effect to achieve a more reliable baseline for statistical analysis. The method works only in the MR domain without EEG correlation. It compares the EPI images during interictal epileptic discharges and the images “inactivated” by benzodiazepine.

The results in five out of eight patients show that this procedure in comparison with the EEG/fMRI method gives a net improvement of spatial definition of BOLD areas. These preliminary results seem to confirm the hypothesis that the better BOLD/fMRI procedure in epilepsy is to make use of physical features of MR that, unlike EEG, is not influenced by the distance of intercerebral sources and consequently allows a more complete and undistorted display of BOLD areas.     

Simultaneous EEG-fMRI acquisition: how far is it from being a standardized technique?

Simultaneous EEG–fMRI is a powerful tool to study spontaneous and evoked brain activity because of the complementary advantages of the two techniques in terms of temporal and spatial resolution. In recent years, a significant number of scientific works have been published on this subject. However, many technical problems related to the intrinsic incompatibility of EEG and MRI methods are still not fully solved. Furthermore, simultaneous acquisition of EEG and event-related fMRI requires precise synchronization of all devices involved in the experimental setup. Thus, timing issue must be carefully considered in order to avoid significant methodological errors.

The aim of the present work is to highlight and discuss some of technical and methodological open issues associated with the combined use of EEG and fMRI. These issues are presented in the context of preliminary data regarding simultaneous acquisition of event-related evoked potentials and BOLD images during a visual odd-ball paradigm.     

EEG quality during simultaneous functional MRI of interictal epileptiform discharges

This article concerns the evaluation of the quality of interictal epileptiform EEG discharges recorded throughout simultaneous echo planar imaging (EPI). BOLD (blood oxygen level dependent) functional MRI (fMRI) images were acquired continuously on a patient with intractable epilepsy. EEG was sampled simultaneously, during and after imaging, with removal of pulse and imaging artifacts by subtraction of channel-specific running averages. Contiguous EEG epochs recorded with and without fMRI (fMRI+ve vs. fMRI−ve) were next randomized and presented to two blinded observers. Epileptiform discharges were identified retrospectively, and comparison was made in terms of the number of identified events, their amplitude, and spatiotemporal distribution. A spectral analysis was also performed on the EEG. In the randomized comparison of EEG segments, 80 (fMRI+ve) vs. 69 (fMRI−ve) discharges were noted with good interobserver agreement (69%). There were no significant differences in amplitude or spatio-temporal distribution. Comparison of the events detected and measured by two expert observers demonstrated that the Interictal Epileptiform Discharge (IED) characteristics were indistinguishable with and without scanning. We review briefly the existing literature on EEG recording quality for combined EEG/fMRI.     

Simultaneous EEG and fMRI in the macaque monkey at 4.7 Tesla

Simultaneous electroencephalography (EEG)/functional magnetic resonance imaging (fMRI) acquisition can identify the brain networks involved in generating specific EEG patterns. Yet, the combination of these methodologies is hampered by strong artifacts that arise due to electromagnetic interference during magnetic resonance (MR) image acquisition. Here, we report corrections of the gradient-induced artifact in phantom measurements and in experiments with an awake behaving macaque monkey during fMRI acquisition at a magnetic field strength of 4.7 T. Ninety-one percent of the amplitude of a 10 microV, 10 Hz phantom signal could successfully be recovered without phase distortions. Using this method, we were able to extract the monkey EEG from scalp recordings obtained during MR image acquisition. Visual evoked potentials could also be reliably identified. In conclusion, simultaneous EEG/fMRI acquisition is feasible in the macaque monkey preparation at 4.7 T and holds promise for investigating the neural processes that give rise to particular EEG patterns.     

Special designed RF-antenna with integrated non-invasive carbon electrodes for simultaneous magnetic resonance imaging and electroencephalography acquisition at 7T

The construction of a high quality MR RF-antenna with incorporated EEG electrodes for simultaneous MRI and EEG acquisition is presented. The antenna comprises an active decoupled surface coil for receiving the MR signal and a whole body coil for transmitting the excitation RF pulses. The surface coil offers a high signal-to-noise ratio required for fMRI application and the whole body coil has a good B(1) excitation profile, which enables the application of homogeneous RF pulses. Non-invasive carbon electrodes are used in order to minimise the magnetic susceptibility artefacts that occur upon application of conductive materials. This dedicated set-up is compared to a standard set-up being a linear birdcage coil and commercially available Ag/AgCl electrodes. As the acquired EEG signals are heavily disturbed by the gradient switching, intelligent filtering is applied to obtain a clean EEG signal.     

How the NPX data format handles EEG data acquired simultaneously with fMRI

There is a growing interest in combining EEG and (f)MRI data as they provide complementary information: EEG is characterized by a high temporal resolution but poor spatial one, while fMRI is characterized by a high spatial resolution but low temporal one. However, while a standard file format for storing EEG data is available since over a decade, it does not fulfill the needs of modern protocols and devices such as those involved in simultaneous EEG and fMRI recordings. The main reasons are the limited bit resolution, some difficulties encountered in handling and storing acquisition events or trace markers for off-line analyses and the impossibility to add some protocol-specific information that is not considered in the actual data formats. This, among others, hinders the release of free analysis software and makes it difficult to share data across different laboratories as every research unit develops its own tools according to its needs, stores data in proprietary formats and a lot of time is spent building software applications for converting data from one format to another. The NPX (NeuroPhysiological signals in eXtensible Markup Language) data format was defined to overcome these and other limitations, and here its main characteristics are reported as well as how some typical problems occurring in simultaneous EEG-fMRI recordings are also treated. Many tools based on the NPX technology can be freely downloaded, including a tool for removing artifacts occurring during simultaneous EEG-fMRI recordings.     

On the origin of respiratory artifacts in BOLD-EPI of the human brain

BOLD-based functional MRI (fMRI) can be used to explicitly measure hemodynamic aspects and functions of human neuro-physiology. As fMRI measures changes in regional cerebral blood flow and volume as well as blood oxygenation, rather than neuronal brain activity directly, other processes that may change the above parameters have to be examined closely to assess sensitivity and specificity of fMRI results. Physiological processes that can cause artifacts include cardiac action, breathing and vasomotion. Although there has been substantial research on physiological artifacts and appropriate compensation methods, controversy still remains on the mechanisms that cause the fMRI signal fluctuations. Respiratory-correlated fluctuations may either be induced by changes of the magnetic field homogeneity due to moving organs, intra-thoracic pressure differences, respiration-dependent vasodilation or oxygenation differences. The aim of this study was to characterize the impact of different breathing patterns by varying respiration frequency and/or tidal volume on EPI time courses of the resting human brain. The amount of respiration-related oscillations during three respiration patterns was quantified, and statistically significant differences were obtained in white matter only: p < 0.03 between 6 vs. 12 ml/kg body weight end tidal volume at a respiration frequency of 15/min, p < 0.03 between 12 vs. 6 ml/kg body weight and 15 vs. 10 respiration cycles/min. There was no significant difference between 15 vs. 10 respiration cycles/min at an end tidal volume of 6 ml/kg body weight (p = 0.917). In addition, the respiration-affected brain regions were very similar with EPI readout in the a-p and l-r direction. Based on our results and published literature we hypothesize that venous oxygenation oscillations due to changing intra-thoracic pressure represent a major factor for respiration-related signal fluctuations and increase significantly with increasing end tidal volume in white matter only.     

Parallel EPI artifact correction (PEAC) for N/2 ghost suppression in neuroimaging applications

Echo Planar Imaging (EPI) is a neuroimaging tool for clinical practice and research investigation. Due to odd-even echo phase inconsistencies, however, EPI suffers from Nyquist N/2 ghost artifacts. In standard neuroimaging protocols, EPI artifacts are suppressed using phase correction techniques that require reference data collected from a reference scan. Because reference-scan based techniques are sensitive to subject motion, EPI performance is sub-optimal in neuroimaging applications. In this technical note, we present a novel EPI data processing technique which we call Parallel EPI Artifact Correction (PEAC). By introducing an implicit data constraint associated with multi-coil sensitivity in parallel imaging, PEAC converts phase correction into a constrained problem that can be resolved using an iterative algorithm. This enables “reference-less” EPI that can improve neuroimaging performance. In the presented work, PEAC is investigated using a standard functional magnetic resonance imaging (fMRI) protocol with multi-slice 2D EPI. It is demonstrated that PEAC can suppress ghost artifacts as effectively as the standard reference-scan based phase correction technique used on a clinical MRI system. We also found that PEAC can achieve dynamic phase correction when motion occurs.     

An independent component analysis-based approach on ballistocardiogram artifact removing

Interest about simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data acquisition has rapidly increased during the last years because of the possibility that the combined method offers to join temporal and spatial resolution, providing in this way a powerful tool to investigate spontaneous and evoked brain activities. However, several intrinsic features of MRI scanning become sources of artifacts on EEG data. Noise sources of a highly predictable nature such as those related to the pulse MRI sequence and those determined by magnetic gradient switching during scanning do not represent a major problem and can be easily removed. On the contrary, the ballistocardiogram (BCG) artifact, a large signal visible on all EEG traces and related to cardiac activity inside the magnetic field, is determined by sources that are not fully stereotyped and causing important limitations in the use of artifact-removing strategies. Recently, it has been proposed to use independent component analysis (ICA) to remove BCG artifact from EEG signals. ICA is a statistical algorithm that allows blind separation of statistically independent sources when the only available information is represented by their linear combination. An important drawback with most ICA algorithms is that they exhibit a stochastic behavior: each run yields slightly different results such that the reliability of the estimated sources is difficult to assess. In this preliminary report, we present a method based on running the FastICA algorithm many times with slightly different initial conditions. Clustering structure in the signal space of the obtained components provides us with a new way to assess the reliability of the estimated sources.     

Functional MRI using super-resolved spatiotemporal encoding

Recently, new ultrafast imaging sequences such as rapid acquisition by sequential excitation and refocusing (RASER) and hybrid spatiotemporal encoding (SPEN) magnetic resonance imaging (MRI) have been proposed, in which the phase encoding of conventional echo planar imaging (EPI) is replaced with a SPEN. In contrast to EPI, SPEN provides significantly higher immunity to frequency heterogeneities including those caused by B₀ inhomogeneities and chemical shift offsets. Utilizing the inherent robustness of SPEN, it was previously shown that RASER can be used to successfully perform functional MRI (fMRI) experiments in the orbitofrontal cortex — a task which is challenging using EPI due to strong magnetic susceptibility variation near the air-filled sinuses. Despite this superior performance, systematic analyses have shown that, in its initial implementation, the use of SPEN was penalized by lower signal-to-noise ratio (SNR) and higher radiofrequency power deposition as compared to EPI-based methods. A recently developed reconstruction algorithm based on super-resolution principles is able to alleviate both of these shortcomings; the use of this algorithm is hereby explored within an fMRI context. Specifically, a series of fMRI measurements on the human visual cortex confirmed that the super-resolution algorithm retains the statistical significance of the blood oxygenation level dependent (BOLD) response, while significantly reducing the power deposition associated with SPEN and restoring the SNR to levels that are comparable with those of EPI.     

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.     

An unsupervised deep learning technique for susceptibility artifact correction in reversed phase-encoding EPI images

Echo planar imaging (EPI) is a fast and non-invasive magnetic resonance imaging technique that supports data acquisition at high spatial and temporal resolutions. However, susceptibility artifacts, which cause the misalignment to the underlying structural image, are unavoidable distortions in EPI. Traditional susceptibility artifact correction (SAC) methods estimate the displacement field by optimizing an objective function that involves one or more pairs of reversed phase-encoding (PE) images. The estimated displacement field is then used to unwarp the distorted images and produce the corrected images. Since this conventional approach is time-consuming, we propose an end-to-end deep learning technique, named S-Net, to correct the susceptibility artifacts the reversed-PE image pair. The proposed S-Net consists of two components: (i) a convolutional neural network to map a reversed-PE image pair to the displacement field; and (ii) a spatial transform unit to unwarp the input images and produce the corrected images. The S-Net is trained using a set of reversed-PE image pairs and an unsupervised loss function, without ground-truth data. For a new image pair of reversed-PE images, the displacement field and corrected images are obtained simultaneously by evaluating the trained S-Net directly. Evaluations on three different datasets demonstrate that S-Net can correct the susceptibility artifacts in the reversed-PE images. Compared with two state-of-the-art SAC methods (TOPUP and TISAC), the proposed S-Net runs significantly faster: 20 times faster than TISAC and 369 times faster than TOPUP, while achieving a similar correction accuracy. Consequently, S-Net accelerates the medical image processing pipelines and makes the real-time correction for MRI scanners feasible. Our proposed technique also opens up a new direction in learning-based SAC.     

Gradient induced artifacts in simultaneous EEG-fMRI: Effect of synchronization on spiral and EPI k-space trajectories

The nature of the gradient induced electroencephalography (EEG) artifact is analyzed and compared for two functional magnetic resonance imaging (fMRI) pulse sequences with different k-space trajectories: echo planar imaging (EPI) and spiral. Furthermore, the performance of the average artifact subtraction algorithm (AAS) to remove the gradient artifact for both sequences is evaluated. The results show that the EEG gradient artifact for spiral sequences is one order of magnitude higher than for EPI sequences due to the chirping spectrum of the spiral sequence and the dB/dt of its crusher gradients. However, in the presence of accurate synchronization, the use of AAS yields the same artifact suppression efficiency for both pulse sequences below 80 Hz. The quality of EEG signal after AAS is demonstrated for phantom and human data. EEG spectrogram and visual evoked potential (VEP) are compared outside the scanner and use both EPI and spiral pulse sequences. MR related artifact residues affect the spectra over 40 Hz (less than 0.2 μV up to 120 Hz) and modify the amplitude of P1, N2 and P300 in the VEP. These modifications in the EEG signal have to be taken into account when interpreting EEG data acquired in simultaneous EEG-fMRI experiments.     

Image reconstruction of sequentially sampled echo-planar data

For echo-planar imaging (EPI), failure to time-reverse alternate echoes results in aliasing in the image. We encountered image artifacts in EPI acquired on a system with sequential sampling. After examining the source of these image artifacts, we concluded that the artifacts were a result of the type of sampling method used in data acquisition and the way the time-reversal of alternate echoes was carried out prior to Fourier transformation. Two methods are demonstrated to obtain artifact-free EPI with sequential data sampling.     

High spatial resolution BOLD fMRI using simultaneous multislice excitation with echo-shifting gradient echo at 7 Tesla

We introduce an accelerated gradient echo (GRE) sequence combining simultaneous multislice excitation (SMS) with echo-shifting technique for high spatial resolution blood oxygen level dependent (BOLD) functional MRI (fMRI). The simulation was conducted to optimize scan parameters. To validate the feasibility of the proposed technique, the visual and motor task experiments were performed at 7.0 Tesla (T). The single-shot EPI sequence was also applied in comparison with the proposed technique. The simulation results showed that an optimized flip angle of 9° provided maximal BOLD contrast for our scanning scheme, allowing low power deposition and SMS acceleration factor of 5. Additionally, parallel acquisition imaging with acceleration factor of 2 was utilized, which allowed a total acceleration factor of 10 in volunteer study. The experiment results showed that geometric distortion-free BOLD images with voxel size of 1.0 × 1.0 × 2.5 mm³ were obtained. Significant brain activation was identified in both visual and motor task experiments, which were in accordance with previous investigations. The proposed technique has potential for high spatial resolution fMRI at ultra-high field because of its sufficient BOLD sensitivity as well as improved acquisition speed over conventional GRE-based techniques.     

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.     

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.     

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.     

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.