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.     

Blind source separation of multichannel electroencephalogram based on wavelet transform and ICA

Combination of the wavelet transform and independent component analysis （ICA） was employed for blind source separation （BSS） of multichannel electroencephalogram （EEG）. After denoising the original signals by discrete wavelet transform, high frequency components of some noises and artifacts were removed from the original signals. The denoised signals were reconstructed again for the purpose of ICA, such that the drawback that ICA cannot distinguish noises from source signals can be overcome effectively. The practical processing results showed that this method is an effective way to BSS of multichannel EEG. The method is actually a combination of wavelet transform with adaptive neural network, so it is also useful for BBS of other complex signals.     

An empirical investigation of motion effects in eMRI of interictal epileptiform spikes

We recently developed a functional neuroimaging technique called encephalographic magnetic resonance imaging (eMRI). Our method acquires rapid single-shot gradient-echo echo-planar MRI (repetition time=47 ms); it attempts to measure an MR signal more directly linked to neuronal electromagnetic activity than existing methods. To increase the likelihood of detecting such an MR signal, we recorded concurrent MRI and scalp electroencephalography (EEG) during fast (20-200 ms), localized, high-amplitude (>50 μV on EEG) cortical discharges in a cohort of focal epilepsy patients. Seen on EEG as interictal spikes, these discharges occur in between seizures and induced easily detectable MR magnitude and phase changes concurrent with the spikes with a lag of milliseconds to tens of milliseconds. Due to the time scale of the responses, localized changes in blood flow or hemoglobin oxygenation are unlikely to cause the MR signal changes that we observed. While the precise underlying mechanisms are unclear, in this study, we empirically investigate one potentially important confounding variable — motion. Head motion in the scanner affects both EEG and MR recording. It can produce brief “spike-like” artifacts on EEG and induce large MR signal changes similar to our interictal spike-related signal changes. In order to explore the possibility that interictal spikes were associated with head motions (although such an association had never been reported), we had previously tracked head position in epilepsy patients during interictal spikes and explicitly demonstrated a lack of associated head motion. However, that study was performed outside the MR scanner, and the root-mean-square error in the head position measurement was 0.7 mm. The large inaccuracy in this measurement therefore did not definitively rule out motion as a possible signal generator. In this study, we instructed healthy subjects to make deliberate brief (<500 ms) head motions inside the MR scanner and imaged these head motions with concurrent EEG and MRI. We compared these artifactual MR and EEG data to genuine interictal spikes. While per-voxel MR and per-electrode EEG time courses for the motion case can mimic the corresponding time courses associated with a genuine interictal spike, head motion can be unambiguously differentiated from interictal spikes via scalp EEG potential maps. Motion induces widespread changes in scalp potential, whereas interictal spikes are localized and have a regional fall-off in amplitude. These findings make bulk head motion an unlikely generator of the large spike-related MR signal changes that we had observed. Further work is required to precisely identify the underlying mechanisms.     

Adaptive Filtration of Physiological Artifacts in EEG Signals in Humans Using Empirical Mode Decomposition

A new method for adaptive filtration of experimental EEG signals in humans and for removal of different physiological artifacts has been proposed. The algorithm of the method includes empirical mode decomposition of EEG, determination of the number of empirical modes that are considered, analysis of the empirical modes and search for modes that contains artifacts, removal of these modes, and reconstruction of the EEG signal. The method was tested on experimental human EEG signals and demonstrated high efficiency in the removal of different types of physiological EEG artifacts.     

Evaluating gradient artifact correction of EEG data acquired simultaneously with fMRI

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has become a widely used application in spite of EEG perturbations due to electromagnetic interference in the MR environment. The most prominent and disturbing artifacts in the EEG are caused by the alternating magnetic fields (gradients) of the MR scanner. Different methods for gradient artifact correction have been developed. Here we propose an approach for the systematic evaluation and comparison of these gradient artifact correction methods. Exemplarily, we evaluate different algorithms all based on artifact template subtraction--the currently most established means of gradient artifact removal. We introduce indices for the degree of gradient artifact reduction and physiological signal preservation. The combination of both indices was used as a measure for the overall performance of gradient artifact removal and was shown to be useful in identifying problems during artifact removal. We demonstrate that the evaluation as proposed here allows to reveal frequency-band specific performance differences among the algorithms. This emphasizes the importance of carefully selecting the artifact correction method appropriate for the respective case.     

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.     

Choosing Strategies to Deal with Artifactual EEG Data in Children with Cognitive Impairment

Rett syndrome is a disease that involves acute cognitive impairment and, consequently, a complex and varied symptomatology. This study evaluates the EEG signals of twenty-nine patients and classify them according to the level of movement artifact. The main goal is to achieve an artifact rejection strategy that performs well in all signals, regardless of the artifact level. Two different methods have been studied: one based on the data distribution and the other based on the energy function, with entropy as its main component. The method based on the data distribution shows poor performance with signals containing high amplitude outliers. On the contrary, the method based on the energy function is more robust to outliers. As it does not depend on the data distribution, it is not affected by artifactual events. A double rejection strategy has been chosen, first on a motion signal (accelerometer or EEG low-pass filtered between 1 and 10 Hz) and then on the EEG signal. The results showed a higher performance when working combining both artifact rejection methods. The energy-based method, to isolate motion artifacts, and the data-distribution-based method, to eliminate the remaining lower amplitude artifacts were used. In conclusion, a new method that proves to be robust for all types of signals is designed.     

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.     

De-aliasing for signal restoration in Propeller MR imaging

PurposeObjects falling outside of the true elliptical field-of-view (FOV) in Propeller imaging show unique aliasing artifacts. This study proposes a de-aliasing approach to restore the signal intensities in Propeller images without extra data acquisition.Materials and methodsComputer simulation was performed on the Shepp-Logan head phantom deliberately placed obliquely to examine the signal aliasing. In addition, phantom and human imaging experiments were performed using Propeller imaging with various readouts on a 3.0 Tesla MR scanner. De-aliasing using the proposed method was then performed, with the first low-resolution single-blade image used to find out the aliasing patterns in all the single-blade images, followed by standard Propeller reconstruction. The Propeller images without and with de-aliasing were compared.ResultsComputer simulations showed signal loss at the image corners along with aliasing artifacts distributed along directions corresponding to the rotational blades, consistent with clinical observations. The proposed de-aliasing operation successfully restored the correct images in both phantom and human experiments.ConclusionThe de-aliasing operation is an effective adjunct to Propeller MR image reconstruction for retrospective restoration of aliased signals.     

A Fast Approach to Removing Muscle Artifacts for EEG with Signal Serialization Based Ensemble Empirical Mode Decomposition

An electroencephalogram (EEG) is an electrophysiological signal reflecting the functional state of the brain. As the control signal of the brain–computer interface (BCI), EEG may build a bridge between humans and computers to improve the life quality for patients with movement disorders. The collected EEG signals are extremely susceptible to the contamination of electromyography (EMG) artifacts, affecting their original characteristics. Therefore, EEG denoising is an essential preprocessing step in any BCI system. Previous studies have confirmed that the combination of ensemble empirical mode decomposition (EEMD) and canonical correlation analysis (CCA) can effectively suppress EMG artifacts. However, the time-consuming iterative process of EEMD may limit the application of the EEMD-CCA method in real-time monitoring of BCI. Compared with the existing EEMD, the recently proposed signal serialization based EEMD (sEEMD) is a good choice to provide effective signal analysis and fast mode decomposition. In this study, an EMG denoising method based on sEEMD and CCA is discussed. All of the analyses are carried out on semi-simulated data. The results show that, in terms of frequency and amplitude, the intrinsic mode functions (IMFs) decomposed by sEEMD are consistent with the IMFs obtained by EEMD. There is no significant difference in the ability to separate EMG artifacts from EEG signals between the sEEMD-CCA method and the EEMD-CCA method (p > 0.05). Even in the case of heavy contamination (signal-to-noise ratio is less than 2 dB), the relative root mean squared error is about 0.3, and the average correlation coefficient remains above 0.9. The running speed of the sEEMD-CCA method to remove EMG artifacts is significantly improved in comparison with that of EEMD-CCA method (p < 0.05). The running time of the sEEMD-CCA method for three lengths of semi-simulated data is shortened by more than 50%. This indicates that sEEMD-CCA is a promising tool for EMG artifact removal in real-time BCI systems.     

Non-invasive and low-artifact in vivo brain imaging by using a scanning acoustic-photoacoustic dual mode microscopy

Photoacoustic imaging is a potential candidate for in vivo brain imaging, whereas, its imaging performance could be degraded by inhomogeneous multi-layered media, consisted of scalp and skull. In this work, we propose a low-artifact photoacoustic microscopy (LAPAM) scheme, which combines conventional acoustic-resolution photoacoustic microscopy with scanning acoustic microscopy to suppress the reflection artifacts induced by multi-layers. Based on similar propagation characteristics of photoacoustic signals and ultrasonic echoes, the ultrasonic echoes can be employed as the filters to suppress the reflection artifacts to obtain low-artifact photoacoustic images. Phantom experiment is used to validate the effectiveness of this method. Furthermore, LAPAM is applied for in-vivo imaging mouse brain without removing the scalp and the skull. Experimental results show that the proposed method successfully achieves the low-artifact brain image, which demonstrates the practical applicability of LAPAM. This work might improve the photoacoustic imaging quality in many biomedical applications which involve tissues with complex acoustic properties, such as brain imaging through scalp and skull.     

Diet and gastrointestinal signal on T1-weighted magnetic resonance imaging of mice

In magnetic resonance (MR) imaging of small animals, the gastrointestinal contents may give rise to intense signals on T1-weighted images. The aim of this study was to determine the optimal dietary preparation to reduce gastrointestinal signals in mice and to evaluate the usefulness of this approach. Images of the mouse trunk were obtained using a T1-weighted, three-dimensional fast low-angle shot sequence under various dietary conditions and were compared with respect to the gastrointestinal signals and image quality. The dietary preparation studied included giving alternative diets for 24 h, intestinal cleansing, and 6-h fasting. Mice with and without dietary preparation underwent MR lymphography using gadofluorine 8, and the visualization of abdominal lymph nodes was compared. In the absence of dietary preparation, hyperintense areas were conspicuous in the gastrointestinal system, whereas on the images taken from mice fed potato or sweet potato for 24 h before imaging, gastrointestinal hyperintensity was less prominent. This preparation also reduced artifactual signals and resulted in higher-quality images of the kidneys. Intestinal cleansing, which consisted of 24-h fasting and laxative intake, did not reduce the gastrointestinal signals and caused signal changes that were indicative of fatty liver development. Some of the abdominal lymph nodes of the mice that did not receive dietary preparation were visualized on MR lymphography source images but not on maximum intensity projection (MIP) images. In contrast, on the MIP images of mice fed potato, all the lymph nodes delineated on the source images were successfully visualized. In conclusion, feeding mice potato or sweet potato for 24 h before MR imaging reduces the gastrointestinal signals and image degradation due to artifacts. Appropriate dietary preparations facilitate the display of target structures on MIP images and are expected to enhance the capabilities of small animal MR imaging.     

Ultra-fast imaging

The relatively long scan times with currently available technology restrict the range of MRI applications, increase the cost of scanning by limiting throughput, and lead to image artifacts from patient motion during scans. Ultrafast imaging, in several guises, is now poised for introduction into clinical practice. With the Instascan method, a descendant of the echo-planar technique, complete MR images may be obtained hundreds to thousands of times faster than in conventional approaches and now yield spatial resolution and contrast directly comparable to standard MRI. "Single-shot" imaging methods, such as Instascan, are utilized in the study of dynamic processes, in the direct evaluation of motion (as in diffusion sensitive imaging), and in dramatic new applications, including the interactive control of intraparenchymal laser surgery. Improvements to the small flip-angle method, FLASH, have also pushed scan times into the subsecond domain; this method may be implemented on presently available imaging equipment but yields contrast behavior different from the traditional spin-echo techniques and displays signal-to-noise ratios significantly lower than single-shot imaging. Ultimately, incorporating ultra-fast MR imaging techniques into the armamentarium of the radiologist will likely require changes to many aspects of the MRI practice, from expanded involvement with the scan process to management of the increased data load, and may lead to dramatic changes in the scope of the MRI practice.     

Real-time MR artifacts filtering during continuous EEG/fMRI acquisition

The purpose of this study was the development of a real-time filtering procedure of MRI artifacts in order to monitor the EEG activity during continuous EEG/fMRI acquisition. The development of a combined EEG and fMRI technique has increased in the past few years. Preliminary “spike-triggered” applications have been possible because in this method, EEG knowledge was only necessary to identify a trigger signal to start a delayed fMRI acquisition. In this way, the two methods were used together but in an interleaved manner. In real simultaneous applications, like event-related fMRI study, artifacts induced by MRI events on EEG traces represent a substantial obstacle for a right analysis. Up until now, the methods proposed to solve this problem are mainly based on procedures to remove post-processing artifacts without the possibility to control electrophysiological behavior of the patient during fMRI scan. Moreover, these methods are not characterized by a strong “prior knowledge” of the artifact, which is an imperative condition to avoid any loss of information on the physiological signals recovered after filtering. In this work, we present a new method to perform simultaneous EEG/fMRI study with real-time artifacts filtering characterized by a procedure based on a preliminary analytical study of EPI sequence parameters-related EEG-artifact shapes. Standard EEG equipment was modified in order to work properly during ultra-fast MRI acquisitions. Changes included: high-performance acquisition device; electrodes/cap/wires/cables materials and geometric design; shielding box for EEG signal receiver; optical fiber link; and software. The effects of the RF pulse and time-varying magnetic fields were minimized by using a correct head cap wires-locked environment montage and then removed during EEG/fMRI acquisition with a subtraction algorithm that takes in account the most significant EPI sequence parameters. The on-line method also allows a further post-processing utilization.     

Restoration of MR-induced artifacts in simultaneously recorded MR/EEG data

During a Magnetic Resonance sequence, simultaneously acquired ElectroEncephaloGraphy (EEG) data are compromised by severe pollution due to artifacts originating from the switching of the magnetic field gradients. In this work, it is shown how these artifacts can be strongly reduced or even removed through application of an adaptive artifact restoration scheme. The method has proved to be fully automatic and to retain high frequency EEG information, which is indispensable for many EEG applications.     

A hybrid technique for spectroscopic imaging with reduced truncation artifact

Traditionally, Fourier spectroscopic imaging is associated with a small k-space coverage which leads to truncation artifacts such as "bleeding" and ringing in the resultant image. Because substantial truncation artifacts mainly arise from regions having intense signals, such as the subcutaneous lipid in the head, effective reduction of truncation artifacts can be achieved by obtaining an extended k-space coverage for these regions. In this paper, a hybrid technique which employs phase-encoded spectroscopic imaging (SI) to cover the central portion of the k-space and echo-planar spectroscopic imaging (EPSI) to measure the peripheral portion of the k-space is developed. EPSI, despite its inherently low SNR characteristics, provides a sufficient SNR for outer high-spatial frequency components of the aforementioned high signal regions and supplies an extended k-space coverage of these regions for the reduction of truncation artifacts. The data processing includes steps designed to remove inconsistency between the two types of data and a previously described technique for selectively retaining only outer k-space information for the high signal regions during the reconstruction. Experimental studies, in both phantoms and normal volunteers, demonstrate that the hybrid technique provides significant reduction in truncation artifacts.     

基于投影寻踪的超声彩色血流成像杂波抑制方法

为抑制超声彩色血流成像(CFI)中杂波信号对血流速度估计的影响,提出一种基于投影寻踪(PP)的杂波抑制方法。根据回波信号的时域特性,采用投影寻踪法提取主元以降低主元对非血流区域的高强度杂波的敏感度;然后在特征向量空间去除估计得到的杂波成分,从而获得血流信号。将本方法用于计算机仿真信号和人体实测信号。结果表明:与传统的高通滤波器法相比,本方法能更好地保持流速剖面的完整性和血流轮廓;与特征向量法相比,在近似的流速完整度下本方法在非血流区域产生的误差较少,血管内外能量比高出特征向量法约5dB,能够有效地提高彩色血流成像的质量。      

Interactive reduced FOV imaging for projection reconstruction and spiral acquisition.

MR fluoroscopy is likely to gain increasing importance for the visualization of dynamic processes such as cardiac function and for the guidance of interventional procedures. In many applications the dynamic processes are restricted to a part of the object under study making reduced field of view (rFOV) imaging desirable. The restriction to a smaller FOV can either be used to increase the spatial or the temporal resolution. In projection reconstruction (PR) and spiral imaging severe backfolding artifacts occur if a rFOV is used. In this paper efficient suppression schemes are proposed for PR- and spiral imaging to avoid backfolding artifacts. Evaluation of the proposed schemes was done on an interactive real-time MR-scanner. Cardiac function studies clearly showed the potential of this technique for PR- and spiral imaging.     

Reduced aliasing artifacts using shaking projection k-space sampling trajectory

Radial imaging techniques, such as projection-reconstruction （PR）, are used in magnetic resonance imaging （MRI） for dynamic imaging, angiography, and short-T2 imaging. They are less sensitive to flow and motion artifacts, and support fast imaging with short echo times. However, aliasing and streaking artifacts are two main sources which degrade radial imaging quality. For a given fixed number of k-space projections, data distributions along radial and angular directions will influence the level of aliasing and streaking artifacts. Conventional radial k-space sampling trajectory introduces an aliasing artifact at the first principal ring of point spread function （PSF）. In this paper, a shaking projection （SP） k-space sampling trajectory was proposed to reduce aliasing artifacts in MR images. SP sampling trajectory shifts the projection alternately along the k-space center, which separates k-space data in the azimuthal direction. Simulations based on conventional and SP sampling trajectories were compared with the same number projections. A significant reduction of aliasing artifacts was observed using the SP sampling trajectory. These two trajectories were also compared with different sampling frequencies. ASP trajectory has the same aliasing character when using half sampling frequency （or half data） for reconstruction. SNR comparisons with different white noise levels show that these two trajectories have the same SNR character. In conclusion, the SP trajectory can reduce the aliasing artifact without decreasing SNR and also provide a way for undersampling recon- struction. Furthermore, this method can be applied to three-dimensional （3D） hybrid or spherical radial k-space sampling for a more efficient reduction of aliasing artifacts.     

The motion artifact suppression technique (MAST) in magnetic resonance imaging: clinical results

The Motion Artifact Suppression Technique (MAST) is a method which uses a series of gradient echos that are computed to cancel velocity, acceleration and pulsatility components of involuntary motion in MR imaging. A total of 916 patient studies were performed over a nine month period using MAST sequences with a TE 40, 60, 80, 100, 120, and 26/112. There was considerable improvement in long TR, long TE images. Cerebrospinal fluid flow artifacts were reduced. Body and spine images had reduced flow and respiratory artifacts. Spin rephasing in blood vessels caused increase intraluminal signal. This might be useful for cardiovascular imaging.