Restoration of electrophysiological signals distorted by inductive effects of magnetic field gradients during MR sequences

Visual evoked potentials recovered from fMRI scan periods

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) may allow functional imaging of the brain at high temporal and spatial resolution. Artifacts generated in the EEG signal during MR acquisition, however, continue to pose a major challenge. Due to these artifacts, an interleaved modus has often been used for "evoked potential" experiments, i.e., only EEG signals recorded between MRI scan periods were assessed. An obvious disadvantage of this approach is the loss of a portion of the EEG information, which might be relevant for the specific scientific issue. In this study, continuous, simultaneous EEG-fMRI measurements were carried out. Visual evoked potentials (VEPs) could be reconstructed reliably from periods during MR scanning and in between successive scans. No significant differences between both VEPs were detected. This indicates sufficient artifact removal as well as physiological correspondence of VEPs in both periods. Simultaneous continuous VEP-fMRI recordings are thus shown to be feasible.

Reference signal extraction from corrupted ECG using wavelet decomposition for MRI sequence triggering: application to small animals

BACKGROUND

Present developments in Nuclear Magnetic Resonance (NMR) imaging techniques strive for improved spatial and temporal resolution performances. However, trying to achieve the shortest gradient rising time with high intensity gradients has its drawbacks: It generates high amplitude noises that get superimposed on the simultaneously recorded electrophysiological signals, needed to synchronize moving organ images. Consequently, new strategies have to be developed for processing these collected signals during Magnetic Resonance Imaging (MRI) examinations. The aim of this work is to extract an efficient reference signal, from an electrocardiogram (ECG) that was contaminated by the NMR artefacts. This may be used for image triggering and/or cardiac rhythm monitoring.

METHODS

Our method, based on sub-band decomposition using wavelet filters, is tested on various ECG signals recorded during three imaging sequences: Gradient Echo (GE), Fast Spin Echo (FSE) and Inversion Recovery with Spin Echo (IRSE). In order to define the most adapted wavelet functions to use according to the excitation protocols, noise generated by each imaging sequence is recorded and analysed. After exploring noise models along with information found in the literature, a group of 14 wavelets, members of three families (Daubechies, Coiflets, Symlets), is selected for the study. The extraction process is carried out by decomposing the contaminated ECG signals into 8 scales using a given wavelet function, then combining the sub-bands necessary for cardiac synchronization, i.e. those containing the essential part of the QRS energy, to construct a reference signal.

RESULTS

The efficiency of the presented method has been tested on a group of quite representative signals containing: highly contaminated (mean SNR<--5 dB) simulated ECGs that replicate normal and pathological human heart beats, as well as some pathological and healthy rodents' actual ECG records. Despite the weak SNR of the contaminated ECG, the performances were quite satisfactory. When comparing the wavelet performances, one may notice that for a given sequence, some wavelets are more efficient for processing than others; for GE, FSE and IRSE sequence, good synchronisation condition is accomplished with coif5, sym8, and sym4 respectively.

CONCLUSION

Sub-band decomposition proved to be very suitable for extracting a reference signal from a corrupted ECG for MRI triggering. An appropriate choice of the wavelet function, in accordance with the image sequence type, could considerably improve the quality of the reference signal for better image synchronization.

Real-time gating system for mouse cardiovascular MR imaging

Mouse cardiac MR gating using ECG is affected by the hostile MR environment. It requires appropriate signal processing and correct QRS detection, but gating software methods are currently limited. In this study we sought to demonstrate the feasibility of digital real-time automatically updated gating methods, based on optimizing a signal-processing technique for different mouse strains. High-resolution MR images of mouse hearts and aortic arches were acquired using a chain consisting of ECG signal detection, digital signal processing, and gating signal generation modeled using Simulink (The MathWorks, Inc., Natick, MA, USA). The signal-processing algorithms used were respectively low-pass filtering, nonlinear passband, and wavelet decomposition. Both updated and nonupdated gating signal generation methods were tested. Noise reduction was assessed by comparison of the ECG signal-to-noise ratio (SNR) before and after each processing step. Gating performance was assessed by measuring QRS detection accuracy before and after online trigger-level adjustments. Low-pass filtering with trigger-level adjustment gave the best performance for mouse cardiovascular imaging using gradient-echo (GE), spin-echo (SE), and fast SE (FSE) sequences with minimum induced delay and maximum gating efficiency (99% sensitivity and R-peak detection). This simple digital gating interface will allow various gating strategies to be optimized for cardiovascular MR explorations in mice.

Simultaneous EEG–fMRI

Acquisition of electroencephalogram (EEG) during functional magnetic resonance imaging (fMRI) provides an additional monitoring tool for the analysis of brain state fluctuations. The exploration of brain responses following inputs or in the context of state changes is crucial for a better understanding of the basic principles governing large-scale neuronal dynamics. State-of-the-art techniques allow EEG activity-from DC (direct current) up to high frequencies in the gamma range-to be acquired simultaneously with fMRI data. In the interleaved mode, spiking activities can also be assessed during concurrent fMRI. The utilization of fMRI evidence to better constrain solutions of the inverse problem of source localization of EEG activity is an exciting possibility. Nonetheless, this approach should be applied cautiously since the degree of overlap between underlying neuronal activity sources is variable and, for the most part, unknown. The ultimate goal is to make joint inferences about the activity, dynamics, and functions by exploiting complementary information from multimodal data sets.

Removal of FMRI environment artifacts from EEG data using optimal basis sets

The combination of functional magnetic resonance imaging (FMRI) and electroencephalography (EEG) has received much recent attention, since it potentially offers a new tool for neuroscientists that makes simultaneous use of the strengths of the two modalities. However, EEG data collected in such experiments suffer from two kinds of artifact. First, gradient artifacts are caused by the switching of magnetic gradients during FMRI. Second, ballistocardiographic (BCG) artifacts related to cardiac activities further contaminate the EEG data. Here we present new methods to remove both kinds of artifact. The methods are based primarily on the idea that temporal variations in the artifacts can be captured by performing temporal principal component analysis (PCA), which leads to the identification of a set of basis functions which describe the temporal variations in the artifacts. These basis functions are then fitted to, and subtracted from, EEG data to produce artifact-free results. In addition, we also describe a robust algorithm for the accurate detection of heart beat peaks from poor quality electrocardiographic (ECG) data that are collected for the purpose of BCG artifact removal. The methods are tested and are shown to give superior results to existing methods. The methods also demonstrate the feasibility of simultaneous EEG/FMRI experiments using the relatively low EEG sampling frequency of 2048 Hz.

P300 recordings during event-related fMRI: a feasibility study

Analysis of combined event-related potentials (ERP) and functional magnetic resonance imaging (fMRI) can provide a high temporal and high spatial resolution to study functional cerebral processes. However, EEG data recorded inside an MR scanner is heavily distorted by artifacts. It is important in cognitive studies to ensure that recorded data reflect the same brain activity, and this is achieved through interleaved electroencephalographic (EEG) and fMRI measurements. Here, we demonstrate the feasibility of recording P300 ERPs during fMRI using a three-stimulus visual oddball task and involving a small number of trials for each stimulus. Ten EEG channels were acquired interleaved with fMRI images in five healthy subjects. The stimuli, including rare targets "X," frequent repetitive distractors "O," and rare distractors referred to as novels, were randomly presented every 2 +/- 1 s. The post hoc filter presented here was designed and applied to EEG data to remove the cardiac pulse artifact. Interleaved EEG/fMRI acquisition evidenced two P300 ERPs evoked at Fz, Cz, and Pz by targets and novels. Novel-related ERPs were of higher amplitude than their target-related counterparts. The fMRI maps acquired concurrently showed stronger BOLD response for target condition. We have shown that interleaved acquisition allows to obtain reliable P300 data and fMRI results, likely to shed light on the anatomical location of brain regions involved in cognitive ERPs relevant to many disorders affecting CNS functions. These noninvasive multimodal neuroimaging techniques can be used to explore and better understand processes underlying the functional brain organization.

Suppression of MR gradient artefacts on electrophysiological signals based on an adaptive real-time filter with LMS coefficient updates

Electrocardiogram (ECG) acquisition is still a challenge as gradient artefacts superimposed on the electrophysiological signal can only be partially removed. The signal shape of theses artefacts can be similar to the QRS-complex, causing possible misinterpretation during patient monitoring and false triggering/gating of the MRI. For their real-time suppression, an adaptive filter is proposed. The adaptive filter is based on the noise-canceller configuration with LMS coefficient updates. The references of the noise canceller are the three gradient signals that are acquired simultaneously with the noisy ECG. Tests were done on patients, on volunteers and using an MR-safe ECG simulator. The noise canceller's performance was measured offline, simulating real-time processing by point-by-point operations. To create worst-case scenarios, clinical sequences with strong- and fast-switching gradients have been chosen. The noise-cancelling filter reduces the gradient artefacts' peak amplitudes by 80-99% after adaptation, without changing the desired ECG signal shape. The estimated reduction of total average power of the MR gradient artefacts is 62-98%. The proposed filter is capable of reducing artefacts due to strong- and fast-switching gradients in real-time applications and worst-case situations. The quality of the ECG is sufficiently high that a standard one-lead QRS-detector can be used for gating/triggering the MRI. For permanent patient monitoring, further improvements are needed.

Assessment of motion gating strategies for mouse magnetic resonance at high magnetic fields

PURPOSE

To assess the performance of motion gating strategies for mouse cardiac magnetic resonance (MR) at high magnetic fields by quantifying the levels of motion artifact observed in images and spectra in vivo.

MATERIALS AND METHODS

MR imaging (MRI) of the heart, diaphragm, and liver; MR angiography of the aortic arch; and slice-selective 1H-spectroscopy of the heart were performed on anesthetized C57Bl/6 mice at 11.75 T. Gating signals were derived using a custom-built physiological motion gating device, and the gating strategies considered were no gating, cardiac gating, conventional gating (i.e., blanking during respiration), automatic gating, and user-defined gating. Both automatic and user-defined modes used cardiac and respiratory gating with steady-state maintenance during respiration. Gating performance was assessed by quantifying the levels of motion artifact observed in images and the degree of amplitude and phase stability in spectra.

RESULTS

User-defined gating with steady-state maintenance during respiration gave the best performance for mouse cardiac imaging, angiography, and spectroscopy, with a threefold increase in signal intensity and a sixfold reduction in noise intensity compared to cardiac gating only.

CONCLUSION

Physiological gating with steady-state maintenance during respiration is essential for mouse cardiac MR at high magnetic fields.

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.

Functional MRI with simultaneous EEG recording: feasibility and application to motor and visual activation

The possibility of combining the high spatial resolution of functional magnetic resonance imaging (fMRI) with the high temporal resolution of electroencephalography (EEG) may provide a new tool in cognitive neurophysiology, as well as in clinical applications such as epilepsy. However, the simultaneous recording of EEG and fMRI raises important practical problems: 1) the patients' safety, in particular the risk of skin burns due to electrodes heating; 2) the impairment of the EEG recording by the static magnetic field, as well as by RF and magnetic field gradients used during MRI; and 3) the quality of MR images, which may be affected by the presence of conductors and electronic devices in the MRI bore. Here we present our experiences on 19 normal volunteers who underwent combined fMRI and 16-channel EEG examination. Consistent with previous reports, safety could be assured when performing EEG recordings during fMRI acquisition. Electrophysiological signals recorded with surface EEG were similar inside and outside the 1.5 T magnet. Furthermore, fMRI using motor or visual tasks revealed similar areas of activation when performed with and without 16-channel EEG recording. J. Magn. Reson. Imaging 2001;13:943-948.

Electroencephalography during functional echo-planar imaging: detection of epileptic spikes using post-processing methods

EEG has been used to trigger functional MRI of patients with focal epilepsy, but EEG can be obscured by artifacts during MR data acquisition, and no continuous correlation of EEG and MRI has been possible without limiting the image time. Artifacts caused by an MRI sequence were investigated in five healthy subjects, and an EEG of five patients with epileptic discharges was recorded during echo-planar imaging. All interfering frequencies in the EEG were discrete and defined by loop structures in the MRI sequence. In post-processing of the EEG interfering frequencies were automatically detected by comparing the frequency spectra of the EEG recorded before and during imaging. After elimination of interfering frequencies by filters in the time domain or by Fourier transform, reliable spike detection in the EEG recorded during MR data acquisition became feasible, without loss of EEG quality.

Reduction of ECG and gradient related artifacts in simultaneously recorded human EEG/MRI data

Nowadays, electroencephalography signals can be acquired from a patient lying in a magnetic resonance imaging system. It is even possible to acquire EEG signals during an MR imaging sequence. However, such EEG signals are severely distorted by artifacts originating from various effects (e.g., MR gradients, ECG). In this paper, a simple method is presented to reduce such artifacts. Thereby, special attention is focused on artifacts related to the patient's electrocardiogram. The method is shown to be effective, adaptive, and automatic.

A method for removing imaging artifact from continuous EEG recorded during functional MRI

Combined EEG/fMRI recording has been used to localize the generators of EEG events and to identify subject state in cognitive studies and is of increasing interest. However, the large EEG artifacts induced during fMRI have precluded simultaneous EEG and fMRI recording, restricting study design. Removing this artifact is difficult, as it normally exceeds EEG significantly and contains components in the EEG frequency range. We have developed a recording system and an artifact reduction method that reduce this artifact effectively. The recording system has large dynamic range to capture both low-amplitude EEG and large imaging artifact without distortion (resolution 2 microV, range 33.3 mV), 5-kHz sampling, and low-pass filtering prior to the main gain stage. Imaging artifact is reduced by subtracting an averaged artifact waveform, followed by adaptive noise cancellation to reduce any residual artifact. This method was validated in recordings from five subjects using periodic and continuous fMRI sequences. Spectral analysis revealed differences of only 10 to 18% between EEG recorded in the scanner without fMRI and the corrected EEG. Ninety-nine percent of spike waves (median 74 microV) added to the recordings were identified in the corrected EEG compared to 12% in the uncorrected EEG. The median noise after artifact reduction was 8 microV. All these measures indicate that most of the artifact was removed, with minimal EEG distortion. Using this recording system and artifact reduction method, we have demonstrated that simultaneous EEG/fMRI studies are for the first time possible, extending the scope of EEG/fMRI studies considerably.

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.