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

Evaluation of 12-lead electrocardiogram at 0.55T for improved cardiac monitoring in magnetic resonance imaging

BACKGROUND

The 12-lead electrocardiogram (ECG) is a standard diagnostic tool for monitoring cardiac ischemia and heart rhythm during cardiac interventional procedures and stress testing. These procedures can benefit from magnetic resonance imaging (MRI) information; however, the MRI scanner magnetic field leads to ECG distortion that limits ECG interpretation. This study evaluated the potential for improved ECG interpretation in a "low field" 0.55T MRI scanner.

METHODS

The 12-lead ECGs were recorded inside 0.55T, 1.5T, and 3T MRI scanners, as well as at scanner table "home" position in the fringe field and outside the scanner room (seven pigs). To assess interpretation of ischemic ECG changes in a 0.55T MRI scanner, ECGs were recorded before and after coronary artery occlusion (seven pigs). ECGs was also recorded for five healthy human volunteers in the 0.55T scanner. ECG error and variation were assessed over 2-minute recordings for ECG features relevant to clinical interpretation: the PR interval, QRS interval, J point, and ST segment.

RESULTS

ECG error was lower at 0.55T compared to higher field scanners. Only at 0.55T table home position, did the error approach the guideline recommended 0.025 mV ceiling for ECG distortion (median 0.03 mV). At scanner isocenter, only in the 0.55T scanner did J point error fall within the 0.1 mV threshold for detecting myocardial ischemia (median 0.03 mV in pigs and 0.06 mV in healthy volunteers). Correlation of J point deviation inside versus outside the 0.55T scanner following coronary artery occlusion was excellent at scanner table home position (r2 = 0.97), and strong at scanner isocenter (r2 = 0.92).

CONCLUSION

ECG distortion is improved in 0.55T compared to 1.5T and 3T MRI scanners. At scanner home position, ECG distortion at 0.55T is low enough that clinical interpretation appears feasible without need for more cumbersome patient repositioning. At 0.55T scanner isocenter, ST segment changes during coronary artery occlusion appear detectable but distortion is enough to obscure subtle ST segment changes that could be clinically relevant. Reduced ECG distortion in 0.55T scanners may simplify the problem of suppressing residual distortion by ECG cable positioning, averaging, and filtering and could reduce current restrictions on ECG monitoring during interventional MRI procedures.

Broadly applicable methods for the detection of artefacts in electroencephalography acquired simultaneously with hemodynamic recordings

Electroencephalography (EEG) data, acquired simultaneously with magnetic resonance imaging (MRI), must be corrected for artefacts related to MR gradient switches (GS) and the cardioballistic (CB) effect. Canonical approaches require additional signal acquisition for artefact detection (e.g., MR volume onsets, ECG), without which the EEG data would be rendered uncleanable from these artefacts.•We present two broadly applicable methods for artefact detection based on peak detection combined with temporal constraints with respect to periodicity directly from the EEG data itself; no additional signals are required. We validated the performance of our methods versus the two canonical approaches for detection of GS/CB artefact, respectively, on 26 healthy human EEG-functional MRI resting-state datasets. Utilising various performance metrics, we found our methods to perform as well as - and sometimes better than - the canonical standard approaches. With as little as one EEG channel recording, our methods can be applied to detect GS/CB artefacts in EEG data acquired simultaneously with MRI in the absence of MR volume onsets and/or an ECG recording. The detected artefact onsets can then be fed into the standard artefact correction software.

Sophisticated Study of Time, Frequency and Statistical Analysis for Gradient-Switching-Induced Potentials during MRI

Magnetic resonance imaging (MRI) is a standard procedure in medical imaging, on a par with echography and tomodensitometry. In contrast to radiological procedures, no harmful radiation is produced. The constant development of magnetic resonance imaging (MRI) techniques has enabled the production of higher resolution images. The switching of magnetic field gradients for MRI imaging generates induced voltages that strongly interfere with the electrophysiological signals (EPs) collected simultaneously. When the bandwidth of the collection amplifiers is higher than 150 Hz, these induced voltages are difficult to eliminate. Understanding the behavior of these artefacts contributes to the development of new digital processing tools for better quality EPs. In this paper, we present a study of induced voltages collected in vitro using a device (350 Hz bandwidth). The experiments were conducted on a 1.5T MRI machine with two MRI sequences (fast spin echo (FSE) and cine gradient echo (CINE)) and three slice orientations. The recorded induced voltages were then segmented into extract patterns called "artefact puffs". Two analysis series, "global" and "local", were then performed. The study found that the temporal and frequency characteristics were specific to the sequences and orientations of the slice and that, despite the pseudo-periodic character of the artefacts, the variabilities within the same recording were significant. These evolutions were confirmed by two stationarity tests: the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) and the time-frequency approach. The induced potentials, all stationary at the global scale, are no longer stationary at the local scale, which is an important issue in the design of optimal filters adapted to reduce MRI artifacts contaminating a large bandwidth, which varies between 0 and 500 Hz.

A Brief Summary of EEG Artifact Handling

There are various obstacles in the way of use of EEG. Among these, the major obstacles are the artifacts. While some artifacts are avoidable, due to the nature of the EEG techniques there are inevitable artifacts as well. Artifacts can be categorized as internal/physiological or external/non-physiological. The most common internal artifacts are ocular or muscular origins. Internal artifacts are difficult to detect and remove, because they contain signal information as well. For both resting state EEG and ERP studies, artifact handling needs to be carefully carried out in order to retain the maximal signal. Therefore, an effective management of these inevitable artifacts is critical for the EEG based researches. Many researchers from various fields studied this challenging phenomenon and came up with some solutions. However, the developed methods are not well known by the real practitioners of EEG as a tool because of their limited knowledge about these engineering approaches. They still use the traditional visual inspection of the EEG. This work aims to inform the researchers working in the field of EEG about the artifacts and artifact management options available in order to increase the awareness of the available tools such as EEG preprocessing pipelines.

Estimating Resting HRV during fMRI: A Comparison between Laboratory and Scanner Environment

Heart rate variability (HRV) is regularly assessed in neuroimaging studies as an indicator of autonomic, emotional or cognitive processes. In this study, we investigated the influence of a loud and cramped environment during magnetic resonance imaging (MRI) on resting HRV measures. We compared recordings during functional MRI sessions with recordings in our autonomic laboratory (LAB) in 101 healthy subjects. In the LAB, we recorded an electrocardiogram (ECG) and a photoplethysmogram (PPG) over 15 min. During resting state functional MRI, we acquired a PPG for 15 min. We assessed anxiety levels before the scanning in each subject. In 27 participants, we performed follow-up sessions to investigate a possible effect of habituation. We found a high intra-class correlation ranging between 0.775 and 0.996, indicating high consistency across conditions. We observed no systematic influence of the MRI environment on any HRV index when PPG signals were analyzed. However, SDNN and RMSSD were significantly higher when extracted from the PPG compared to the ECG. Although we found a significant correlation of anxiety and the decrease in HRV from LAB to MRI, a familiarization session did not change the HRV outcome. Our results suggest that psychological factors are less influential on the HRV outcome during MRI than the methodological choice of the cardiac signal to analyze.

Schrödinger filtering: a precise EEG despiking technique for EEG-fMRI gradient artifact

In EEG data acquired in the presence of fMRI, gradient-related spike artifacts contaminate the signal following the common preprocessing step of average artifact subtraction. Spike artifacts compromise EEG data quality since they overlap with the EEG signal in frequency, thereby confounding frequency-based inferences on activity. As well, spike artifacts can inflate or deflate correlations among time series, thereby confounding inferences on functional connectivity. We present Schrödinger filtering, which uses the Schrödinger equation to decompose the spike-containing input. The basis functions of the decomposition are localized and pulse-shaped, and selectively capture the various input peaks, with the spike components clustered at the beginning of the spectrum. Schrödinger filtering automatically subtracts the spike components from the data. On real and simulated data, we show that Schrödinger filtering (1) simultaneously accomplishes high spike removal and high signal preservation without affecting evoked activity, and (2) reduces spurious pairwise correlations in spontaneous activity. In these regards, Schrödinger filtering was significantly better than three other despiking techniques: median filtering, amplitude thresholding, and wavelet denoising. These results encourage the use of Schrödinger filtering in future EEG-fMRI pipelines, as well as in other spike-related applications (e.g., fMRI motion artifact removal or action potential extraction).

Artifacts in Simultaneous hdEEG/fMRI Imaging: A Nonlinear Dimensionality Reduction Approach

Simultaneous recordings of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) are at the forefront of technologies of interest to physicians and scientists because they combine the benefits of both modalities—better time resolution (hdEEG) and space resolution (fMRI). However, EEG measurements in the scanner contain an electromagnetic field that is induced in leads as a result of gradient switching slight head movements and vibrations, and it is corrupted by changes in the measured potential because of the Hall phenomenon. The aim of this study is to design and test a methodology for inspecting hidden EEG structures with respect to artifacts. We propose a top-down strategy to obtain additional information that is not visible in a single recording. The time-domain independent component analysis algorithm was employed to obtain independent components and spatial weights. A nonlinear dimension reduction technique t-distributed stochastic neighbor embedding was used to create low-dimensional space, which was then partitioned using the density-based spatial clustering of applications with noise (DBSCAN). The relationships between the found data structure and the used criteria were investigated. As a result, we were able to extract information from the data structure regarding electrooculographic, electrocardiographic, electromyographic and gradient artifacts. This new methodology could facilitate the identification of artifacts and their residues from simultaneous EEG in fMRI.

Reconstruction of the 12-lead ECG using a novel MR-compatible ECG sensor network

PURPOSE

Current electrocardiography (ECG) devices in MRI use non-conventional electrode placement, have a narrow bandwidth, and suffer from signal distortions including magnetohydrodynamic (MHD) effects and gradient-induced artifacts. In this work a system is proposed to obtain a high-quality 12-lead ECG.

METHODS

A network of N electrically independent MR-compatible ECG sensors was developed (N = 4 in this study). Each sensor uses a safe technology - short cables, preamplification/digitization close to the patient, and optical transmission - and provides three bipolar voltage leads. A matrix combination is applied to reconstruct a 12-lead ECG from the raw network signals. A subject-specific calibration is performed to identify the matrix coefficients, maximizing the similarity with a true 12-lead ECG, acquired with a conventional 12-lead device outside the scan room. The sensor network was subjected to radiofrequency heating phantom tests at 3T. It was then tested in four subjects, both at 1.5T and 3T.

RESULTS

Radiofrequency heating at 3T was within the MR-compatibility standards. The reconstructed 12-lead ECG showed minimal MHD artifacts and its morphology compared well with that of the true 12-lead ECG, as measured by correlation coefficients above 93% (respectively, 84%) for the QRS complex shape during steady-state free precession (SSFP) imaging at 1.5T (respectively, 3T).

CONCLUSION

High-quality 12-lead ECG can be reconstructed by the proposed sensor network at 1.5T and 3T with reduced MHD artifacts compared to previous systems. The system might help improve patient monitoring and triggering and might also be of interest for interventional MRI and advanced cardiac MR applications.

Advances in Real-Time MRI-Guided Electrophysiology

Purpose of Review

Theoretical benefits of real-time MRI guidance over conventional electrophysiology include contemporaneous 3D substrate assessment and accurate intra-procedural guidance and evaluation of ablation lesions. We review the unique challenges inherent to MRI-guided electrophysiology and how to translate the potential benefits in the treatment of cardiac arrhythmias.

Recent Findings

Over the last 5 years, there has been substantial progress, initially in animal models and more recently in clinical studies, to establish methods and develop workflows within the MR environment that resemble those of conventional electrophysiology laboratories. Real-time MRI-guided systems have been used to perform electroanatomic mapping and ablation in patients with atrial flutter, and there is interest in developing the technology to tackle more complex arrhythmias including atrial fibrillation and ventricular tachycardia.

Summary

Mainstream adoption of real-time MRI-guided electrophysiology will require demonstration of clinical benefit and will be aided by increased availability of devices suitable for use in the MRI environment.

Electrocardiogram Acquisition During Remote Magnetic Catheter Navigation

Electrocardiogram (ECG) acquisition is required during catheter treatment of cardiac arrhythmias. The remote magnetic navigation technology allows the catheter to be moved automatically inside the heart chambers using large external magnets. Each change of position of the catheter requires fast motion of the magnets, therefore magnetic fluxes are created through the ECG cables, causing large distortions of the ECG signals. In this study a novel ECG sensor is proposed for reducing such distortions. The sensor uses short cables to connect the electrodes to the amplification and optical conversion circuit, using a technology similar to that used for magnetic resonance imaging. The proposed sensor was compared to the conventional 12-lead ECG device during various operation modes of the magnets. Quantitative morphological analysis of the different waves of the ECG was performed in two healthy subjects and on a conductivity phantom reproducing various cardiac pathologies. In healthy subjects the beat-to-beat correlation coefficients were improved with the proposed sensor for the PR interval (80-93% vs. 49-89%), QRS complex (93-96% vs. 74-94%), ST segment + T wave (95-98% vs. 67-99%), and whole PQRST wave (82-97% vs. 55-96%). Similar observations were made with the conductive gel in the whole PQRST wave in the pathological morphologies of the ECG for the VT (99% vs. 56-98%), AT (95% vs. 26-89%), ST_E (96-97% vs. 20-91%) and ST_D (96% vs. 28-90%). The new sensor might be used for better (uninterrupted) monitoring of the patient during catheter interventions using remote magnetic navigation. It has the potential to improve the robustness and/or duration of certain clinical procedures such as ventricular tachycardia ablation.

Prospective gating control for highly efficient cardio-respiratory synchronised short and constant TR MRI in the mouse

PURPOSE

Cardiac and respiratory motion derived image artefacts are reduced when data are acquired with cardiac and respiratory synchronisation. Where steady state imaging techniques are required in small animals, synchronisation is most commonly performed using retrospective gating techniques but these invoke an inherent time penalty. This paper reports the development of prospective gating techniques for cardiac and respiratory motion desensitised MRI with significantly reduced minimum scan time compared to retrospective gating.

METHODS

Prospective gating incorporating the automatic reacquisition of data corrupted by motion at the entry to each breath was implemented in short TR 3D spoiled gradient echo imaging. Motion sensitivity was examined over the whole mouse body for scans performed without gating, with respiratory gating, and with cardio-respiratory gating. The gating methods were performed with and without automatic reacquisition of motion corrupted data immediately after completion of the same breath. Prospective cardio-respiratory gating, with acquisition of 64 k-space lines per cardiac R-wave, was used to enable whole body DCE-MRI in the mouse.

RESULTS

Prospective cardio-respiratory gating enabled high fidelity steady state imaging of physiologically mobile organs such as the heart and lung. The automatic reacquisition of data corrupted by motion at the entry to each breath minimised respiratory motion artefact and enabled a highly efficient data capture that was adaptive to changes in the inter-breath interval. Prospective cardio-respiratory gating control enabled DCE-MRI to be performed over the whole mouse body with the acquisition of successive image volumes every 12-15 s at 422 μm isotropic resolution.

CONCLUSIONS

Highly efficient cardio-respiratory motion desensitised steady state MRI can be performed in small animals with prospective synchronisation, centre-out phase-encode ordering, and the automatic reacquisition of data corrupted by motion at the entry to each breath. The method presented is robust against spontaneous changes in the breathing rate. Steady state imaging with prospective cardio-respiratory gating is much more efficient than with retrospective gating, and enables the examination of rapidly changing systems such as those found when using DCE-MRI.

Filtering of ECG signals distorted by magnetic field gradients during MRI using non-linear filters and higher-order statistics

The electrocardiogram (ECG) is the state-of-the-art signal for patient monitoring and gating in cardiovascular magnetic resonance (CMR) imaging applications. However, ECG signals are severely distorted during MRI scans due to the effects of static magnetic fields, radio frequency pulses and fast-switching gradient magnetic fields. Gradient-induced artifacts that cause high frequency peaks in the ECG signal especially hamper a correct and reliable QRS detection. To cope with this problem, a new median-based real-time gradient filter (M1) approach was developed. To improve the filter results, a preprocessing step based on higher-order statistics (M2) was added to this. For the evaluation of the filtering techniques, ECG signals were acquired in a 3T MRI scanner during different MR sequences. A qualitative comparison was made using the mean square error as well as the signal power before and after filtering and the results of the QRS detection. Here, reliable results were achieved (detection error rate [DER] M1: 0.23%, DER M2: 0.74%). It was shown that the two developed techniques allowed a reliable suppression of the gradient artifacts in real time.

ECG Electrode Placements for Magnetohydrodynamic Voltage Suppression

This study aims to investigate a set of electrocardiogram (ECG) electrode lead locations to improve the quality of four-lead ECG signals acquired during magnetic resonance imaging (MRI). This was achieved by identifying electrode placements that minimized the amount of induced magnetohydrodynamic voltages (VMHD) in the ECG signals. Reducing VMHD can improve the accuracy of QRS complex detection in ECG as well as heartbeat synchronization between MRI and ECG during the acquisition of cardiac cine. A vector model based on thoracic geometry was developed to predict induced VMHD and to optimize four-lead ECG electrode placement for the purposes of improved MRI gating. Four human subjects were recruited for vector model establishment (Group 1), and five human subjects were recruited for validation of VMHD reduction in the proposed four-lead ECG (Group 2). The vector model was established using 12-lead ECG data recorded from Group 1 of four healthy subjects at 3 Tesla, and a gradient descent optimization routine was utilized to predict optimal four-lead ECG placement based on VMHD vector alignment. The optimized four-lead ECG was then validated in Group 2 of five healthy subjects by comparing the standard and proposed lead placements. A 43.41% reduction in VMHD was observed in ECGs using the proposed electrode placement, and the QRS complex was preserved. A VMHD-minimized electrode placement for four-lead ECG gating was presented and shown to reduce induced magnetohydrodynamic (MHD) signals, potentially allowing for improved cardiac MRI physiological monitoring.

Adaptive step size LMS improves ECG detection during MRI at 1.5 and 3 T

OBJECTIVE

We describe a new real-time filter to reduce artefacts on electrocardiogram (ECG) due to magnetic field gradients during MRI. The proposed filter is a least mean square (LMS) filter able to continuously adapt its step size according to the gradient signal of the ongoing MRI acquisition.

MATERIALS AND METHODS

We implemented this filter and compared it, within two databases (at 1.5 and 3 T) with over 6000 QRS complexes, to five real-time filtering strategies (no filter, low pass filter, standard LMS, and two other filters optimized within the databases: optimized LMS, and optimized Kalman filter).

RESULTS

The energy of the remaining noise was significantly reduced (26 vs. 68%, p < 0.001) with the new filter vs. standard LMS. The detection error of our ventricular complex (QRS) detector was: 11% with our method vs. 25% with raw ECG, 35% with low pass filter, 17% with standard LMS, 12% with optimized Kalman filter, and 11% with optimized LMS filter.

CONCLUSION

The adaptive step size LMS improves ECG denoising during MRI. QRS detection has the same F1 score with this filter than with filters optimized within the database.

Reducing of gradient induced artifacts on the ECG signal during MRI examinations using Wilcoxon filter

The electrocardiogramm (ECG) is the state-of-the-art signal for gating in cardiovascular magnetic resonance imaging and patient monitoring. Using the ECG for gating and monitoring during the magnetic resonance imaging examination is a high challenging task due to the superimposition of the magnetohydrodynamic effect, radio-frequency (RF) pulses and fast switching gradient magnetic fields. The gradient induced artifacts hamper the correct QRS detection which is needed for correct gating and heart rate calculation and ECG displaying for patient monitoring. To suppress the gradient artifacts from the ECG signal acquired during MRI, a technique based on the Wilcoxon filter was developed. It was evaluated using ECG signals of 14 different subjects acquired in a 3 T MRI scanner. It could be shown reliable results for reducing gradient induced artifacts in the ECG signal in real-time.

Marker-based ballistocardiographic artifact correction improves spike identification in EEG-fMRI of focal epilepsy patients

OBJECTIVES

Ballistocardiographic (BCG) artifacts resemble interictal epileptic discharges (IEDs) and can lead to incorrect IED identification in EEG-fMRI. This study investigates IEDs marked in EEGs corrected using information from a moiré phase tracking (MPT) marker.

METHODS

EEG-fMRI from 18 patients was processed with conventional methods for BCG removal, while 9 patients used a MPT marker. IEDs were marked first without ECG information. In a second review, suspicious IEDs synchronous with the BCG were discarded. After each review, an event-related fMRI analysis was performed on the marked IEDs.

RESULTS

No difference was found in the proportion of suspicious IEDs in the 2 patient groups. However, the distribution of IED timings was significantly related to the cardiac cycle in 11 of 18 patients recorded without MPT marker, but only 2 of 9 patients with marker. In patients recorded without marker, failing to discard suspicious IEDs led to more inaccurate fMRI maps and more distant activations.

CONCLUSIONS

BCG artifact correction based on MPT recordings allowed a more straightforward identification of IEDs that did not require ECG information in the large majority of patients.

SIGNIFICANCE

Marker-based ballistocardiographic artifact correction greatly facilitates the study of the generators of interictal discharges with EEG-fMRI.

Presurgical brain mapping in epilepsy using simultaneous EEG and functional MRI at ultra-high field: feasibility and first results

OBJECTIVES

The aim of this study was to demonstrate that eloquent cortex and epileptic-related hemodynamic changes can be safely and reliably detected using simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) recordings at ultra-high field (UHF) for clinical evaluation of patients with epilepsy.

MATERIALS AND METHODS

Simultaneous EEG-fMRI was acquired at 7 T using an optimized setup in nine patients with lesional epilepsy. According to the localization of the lesion, mapping of eloquent cortex (language and motor) was also performed in two patients.

RESULTS

Despite strong artifacts, efficient correction of intra-MRI EEG could be achieved with optimized artifact removal algorithms, allowing robust identification of interictal epileptiform discharges. Noise-sensitive topography-related analyses and electrical source localization were also performed successfully. Localization of epilepsy-related hemodynamic changes compatible with the lesion were detected in three patients and concordant with findings obtained at 3 T. Local loss of signal in specific regions, essentially due to B 1 inhomogeneities were found to depend on the geometric arrangement of EEG leads over the cap.

CONCLUSION

These results demonstrate that presurgical mapping of epileptic networks and eloquent cortex is both safe and feasible at UHF, with the benefits of greater spatial resolution and higher blood-oxygenation-level-dependent sensitivity compared with the more traditional field strength of 3 T.

On utilizing uncertainty information in template-based EEG-fMRI ballistocardiogram artifact removal

The correction of ballistocardiogram artifacts in simultaneous EEG-fMRI often yields unsatisfactory results. To improve the signal-to-noise ratio (SNR) of results, we inferred EEG signal uncertainty from postcorrection artifact residuals and computed the uncertainty-weighted mean of ERPs. Using an uncertainty-weighted mean significantly and consistently reduced both inter- and intrasubject SEM in the analysis of auditory evoked responses (AER, indicated by the N1-P2 complex) and in the effects of an auditory oddball paradigm (N1-P3 complex, standard-deviant difference). SNR increased by 3% on average for the AER amplitude (intrasubject) and 17% on average for the auditory oddball ERP (intersubject). This demonstrates that weighting by uncertainty complements existing artifact correction algorithms to increase SNR in ERPs. More specifically, it is an efficient method to utilize seemingly corrupt (difficult-to-correct) EEG data that might otherwise be discarded.

Pulse artifact detection in simultaneous EEG-fMRI recording based on EEG map topography

One of the major artifact corrupting electroencephalogram (EEG) acquired during functional magnetic resonance imaging (fMRI) is the pulse artifact (PA). It is mainly due to the motion of the head and attached electrodes and wires in the magnetic field occurring after each heartbeat. In this study we propose a novel method to improve PA detection by considering the strong gradient and inversed polarity between left and right EEG electrodes. We acquired high-density EEG-fMRI (256 electrodes) with simultaneous electrocardiogram (ECG) at 3 T. PA was estimated as the voltage difference between right and left signals from the electrodes showing the strongest artifact (facial and temporal). Peaks were detected on this estimated signal and compared to the peaks in the ECG recording. We analyzed data from eleven healthy subjects, two epileptic patients and four healthy subjects with an insulating layer between electrodes and scalp. The accuracy of the two methods was assessed with three criteria: (i) standard deviation, (ii) kurtosis and (iii) confinement into the physiological range of the inter-peak intervals. We also checked whether the new method has an influence on the identification of epileptic spikes. Results show that estimated PA improved artifact detection in 15/17 cases, when compared to the ECG method. Moreover, epileptic spike identification was not altered by the correction. The proposed method improves the detection of pulse-related artifacts, particularly crucial when the ECG is of poor quality or cannot be recorded. It will contribute to enhance the quality of the EEG increasing the reliability of EEG-informed fMRI analysis.

Recursive approach of EEG-segment-based principal component analysis substantially reduces cryogenic pump artifacts in simultaneous EEG-fMRI data

Electroencephalography (EEG) data simultaneously acquired with functional magnetic resonance imaging (fMRI) data are preprocessed to remove gradient artifacts (GAs) and ballistocardiographic artifacts (BCAs). Nonetheless, these data, especially in the gamma frequency range, can be contaminated by residual artifacts produced by mechanical vibrations in the MRI system, in particular the cryogenic pump that compresses and transports the helium that chills the magnet (the helium-pump). However, few options are available for the removal of helium-pump artifacts. In this study, we propose a recursive approach of EEG-segment-based principal component analysis (rsPCA) that enables the removal of these helium-pump artifacts. Using the rsPCA method, feature vectors representing helium-pump artifacts were successfully extracted as eigenvectors, and the reconstructed signals of the feature vectors were subsequently removed. A test using simultaneous EEG-fMRI data acquired from left-hand (LH) and right-hand (RH) clenching tasks performed by volunteers found that the proposed rsPCA method substantially reduced helium-pump artifacts in the EEG data and significantly enhanced task-related gamma band activity levels (p=0.0038 and 0.0363 for LH and RH tasks, respectively) in EEG data that have had GAs and BCAs removed. The spatial patterns of the fMRI data were estimated using a hemodynamic response function (HRF) modeled from the estimated gamma band activity in a general linear model (GLM) framework. Active voxel clusters were identified in the post-/pre-central gyri of motor area, only from the rsPCA method (uncorrected p<0.001 for both LH/RH tasks). In addition, the superior temporal pole areas were consistently observed (uncorrected p<0.001 for the LH task and uncorrected p<0.05 for the RH task) in the spatial patterns of the HRF model for gamma band activity when the task paradigm and movement were also included in the GLM.

ECG-based gating in ultra high field cardiovascular magnetic resonance using an independent component analysis approach

BACKGROUND

In Cardiovascular Magnetic Resonance (CMR), the synchronization of image acquisition with heart motion is performed in clinical practice by processing the electrocardiogram (ECG). The ECG-based synchronization is well established for MR scanners with magnetic fields up to 3 T. However, this technique is prone to errors in ultra high field environments, e.g. in 7 T MR scanners as used in research applications. The high magnetic fields cause severe magnetohydrodynamic (MHD) effects which disturb the ECG signal. Image synchronization is thus less reliable and yields artefacts in CMR images.

METHODS

A strategy based on Independent Component Analysis (ICA) was pursued in this work to enhance the ECG contribution and attenuate the MHD effect. ICA was applied to 12-lead ECG signals recorded inside a 7 T MR scanner. An automatic source identification procedure was proposed to identify an independent component (IC) dominated by the ECG signal. The identified IC was then used for detecting the R-peaks. The presented ICA-based method was compared to other R-peak detection methods using 1) the raw ECG signal, 2) the raw vectorcardiogram (VCG), 3) the state-of-the-art gating technique based on the VCG, 4) an updated version of the VCG-based approach and 5) the ICA of the VCG.

RESULTS

ECG signals from eight volunteers were recorded inside the MR scanner. Recordings with an overall length of 87 min accounting for 5457 QRS complexes were available for the analysis. The records were divided into a training and a test dataset. In terms of R-peak detection within the test dataset, the proposed ICA-based algorithm achieved a detection performance with an average sensitivity (Se) of 99.2%, a positive predictive value (+P) of 99.1%, with an average trigger delay and jitter of 5.8 ms and 5.0 ms, respectively. Long term stability of the demixing matrix was shown based on two measurements of the same subject, each being separated by one year, whereas an averaged detection performance of Se = 99.4% and +P = 99.7% was achieved.Compared to the state-of-the-art VCG-based gating technique at 7 T, the proposed method increased the sensitivity and positive predictive value within the test dataset by 27.1% and 42.7%, respectively.

CONCLUSIONS

The presented ICA-based method allows the estimation and identification of an IC dominated by the ECG signal. R-peak detection based on this IC outperforms the state-of-the-art VCG-based technique in a 7 T MR scanner environment.

An experimental setup to characterize MR switched gradient-induced potentials

We have developed an experimental setup as an in vitro research tool for studying the contamination of electrophysiological signals (EPS) by MRI environment; particularly, when due to the switched gradient-induced potentials. The system is composed of: 1) a MRI compatible module for the transmission of the EPS into the MRI tunnel, 2) a gelatin-based tissue-mimicking phantom, placed inside the tunnel, in which EPS is injected, 3) a detection module composed of a five input channel MRI compatible transmitter placed inside the tunnel, allowing an on-site pre-amplification of the bio-potentials and their transmission, via an optical fiber cable, to a four filtered output per channel receiver (350 Hz, 160 Hz, 80 Hz, and 40 Hz, for a total of 20 channels) placed in the control room, and 4) a signal processing algorithm used to analyze the generated induced potentials. A set of tests were performed to validate the electronic performances of the setup. We also present in this work an interesting application of the setup, i.e., the acquisition and analysis of the induced potentials with respect of the slice orientation for a given MRI sequence. Significant modifications of the time and frequency characteristics were observed with respect to axial, coronal or sagittal orientations.

Prospective self-gated nonenhanced magnetic resonance angiography of the peripheral arteries

Most nonenhanced MRA techniques for evaluating peripheral artery disease (PAD) require cardiac synchronization through physiological gating. Electrocardiographic gating is the most popular method for cardiac synchronization; however, it is subject to interference from switching magnetic field gradients and radiofrequency pulses. A method is described for self-gated nonenhanced MRA that does not require the use of electrocardiographic gating. Imaging was prospectively triggered by detecting the acceleration of blood flow during systole with a reference-less phase contrast navigator. The technique was implemented for nonsubtractive nonenhanced MRA using quiescent-interval single-shot MRA. The lower extremity peripheral arteries of eight healthy subjects were imaged using electrocardiographic-, pulse-, and self-gated quiescent-interval single-shot. Self-gated quiescent-interval single-shot triggered with 99% accuracy. There were no significant differences in relative contrast, contrast-to-noise ratio, or image quality between self-gated and electrocardiographic-gated quiescent-interval single-shot MRA (P > 0.05). Image quality with pulse gating was inferior.

Assessment of global cardiac function

High-resolution magnetic resonance cine imaging (cine-MRI) allows for a non-invasive assessment of ventricular function and mass in normal mice and in genetically and surgically modified mouse models of cardiac disease. The assessment of myocardial mass and function by cine-MRI does not rely on geometric assumptions, as the hearts are covered from the base to the apex, typically by a stack of two-dimensional images. The MR data acquisition is then followed by image segmentation of specific cine frames in each slice to obtain geometric and functional parameters, such as end-diastolic volume (EDV), end-systolic volume (ESV) or ejection fraction (EF). This technique has been well established in clinical routine application and it is now also becoming the reference method in experimental cardiovascular MRI. The cine images are typically acquired in short- and long-axis orientations of the heart to facilitate an accurate assessment of cardiac functional parameters. These views can be difficult to identify, particularly in animals with diseased hearts. Furthermore, data analysis can be the source of a systematic error, mainly for myocardial mass measurement. We have established protocols that allow for a quick and reproducible way of obtaining the relevant cardiac views for cine-MRI, and for accurate image analysis.

Adaptive noise cancellation to suppress electrocardiography artifacts during real-time interventional MRI

PURPOSE

To develop a system for artifact suppression in electrocardiogram (ECG) recordings obtained during interventional real-time magnetic resonance imaging (MRI).

MATERIALS AND METHODS

We characterized ECG artifacts due to radiofrequency pulses and gradient switching during MRI in terms of frequency content. A combination of analog filters and digital least mean squares adaptive filters were used to filter the ECG during in vivo experiments and the results were compared with those obtained with simple low-pass filtering. The system performance was evaluated in terms of artifact suppression and ability to identify arrhythmias during real-time MRI.

RESULTS

Analog filters were able to suppress artifacts from high-frequency radiofrequency pulses and gradient switching. The remaining pulse artifacts caused by intermittent preparation sequences or spoiler gradients required adaptive filtering because their bandwidth overlapped with that of the ECG. Using analog and adaptive filtering, a mean improvement of 38 dB (n = 11, peak QRS signal to pulse artifact noise) was achieved. This filtering system was successful in removing pulse artifacts that obscured arrhythmias such as premature ventricular complexes and complete atrioventricular block.

CONCLUSION

We have developed an online ECG monitoring system employing digital adaptive filters that enables the identification of cardiac arrhythmias during real-time MRI-guided interventions.

Modeling MR induced artifacts contaminating electrophysiological signals recorded during MRI

The purpose of this paper is to present a novel parametric model for Magnetic Resonance (MR) induced artifacts contaminating electrophysiological signals (ECG, EEG, EMG, etc.) recorded simultaneously during MRI. The aim to construct an analytical representation of these artifacts is of great importance as it helps to understand and make appropriate hypotheses about the artifacts' generation process. The model presented in this paper assumes a periodic and stationary nature of these artifacts. Statistical KPSS tests were applied to confirm that observed artifacts are weak-sense stationary. The model based on a sum of sinusoids of different amplitudes, frequencies and phase delays {A, f, Φ} was most suited to represent these artifacts. The sinusoidal model parameters {A, f, Φ} were estimated by BFGS optimization. The lowest mean square error (MSE) is used to determine the model with the optimum parameters. Pearson's correlation coefficients were used as indices to evaluate the accuracy of the calculated model.

Model-based reconstruction for cardiac cine MRI without ECG or breath holding

This paper describes an acquisition and reconstruction strategy for cardiac cine MRI that does not require the use of electrocardiogram or breath holding. The method has similarities with self-gated techniques as information about cardiac and respiratory motion is derived from the imaging sequence itself; here, by acquiring the center k-space line at the beginning of each segment of a balanced steady-state free precession sequence. However, the reconstruction step is fundamentally different: a generalized reconstruction by inversion of coupled systems is used instead of conventional gating. By correcting for nonrigid cardiac and respiratory motion, generalized reconstruction by inversion of coupled systems (GRICS) uses all acquired data, whereas gating rejects data acquired in certain motion states. The method relies on the processing and analysis of the k-space central line data: local information from a 32-channel cardiac coil is used in order to automatically extract eigenmodes of both cardiac and respiratory motion. In the GRICS framework, these eigenmodes are used as driving signals of a motion model. The motion model is defined piecewise, so that each cardiac phase is reconstructed independently. Results from six healthy volunteers, with various slice orientations, show improved image quality compared to combined respiratory and cardiac gating.

Adaptive removal of gradients-induced artefacts on ECG in MRI: a performance analysis of RLS filtering

One of the main vital signs used in patient monitoring during Magnetic Resonance Imaging (MRI) is Electro-Cardio-Gram (ECG). Unfortunately, magnetic fields gradients induce artefacts which severely affect ECG quality. Adaptive Noise Cancelling (ANC) is one of the preferred techniques for artefact removal. ANC involves the adaptive estimation of the impulse response of the system constituted by the MRI equipment, the patient and the ECG recording device. Least Mean Square (LMS) adaptive filtering has been traditionally employed because of its simplicity: anyway, it requires the choice of a step-size parameter, whose proper value for the specific application must be estimated case by case: an improper choice could yield slow convergence and unsatisfactory behaviour. Recursive Least Square (RLS) algorithm has, potentially, faster convergence while not requiring any parameter. As far as the authors' knowledge, there is no systematic analysis of performances of RLS in this scenario. In this study we evaluated the performance of RLS for adaptive removal of artefacts induced by magnetic field gradients on ECG in MRI, in terms of efficacy of suppression. Tests have been made on real signals, acquired via an expressly developed system. A comparison with LMS was made on the basis of opportune performance indices. Results indicate that RLS is superior to LMS in several respects.

Independent component analysis-based artefact reduction: application to the electrocardiogram for improved magnetic resonance imaging triggering

Electrocardiogram (ECG) is required during magnetic resonance (MR) examination for monitoring patients under anaesthesia or with heart diseases and for synchronizing image acquisition with heart activity (triggering). Accurate and fast QRS detection is therefore desirable, but this task is complicated by artefacts related to the complex MR environment (high magnetic field, radio-frequency pulses and fast switching magnetic gradients). Specific signal processing has been proposed, whether using specific MR QRS detectors or ECG denoising methods. Most state-of-the-art techniques use a connection to the MR system for achieving their task, which is a major drawback since access to the MR system is often restricted. This paper introduces a new method for on-line ECG signal enhancement, called ICARE, which takes advantage of using multi-lead ECG and does not require any connection to the MR system. It is based on independent component analysis (ICA) and applied in real time. This algorithm yields accurate QRS detection for efficient triggering.

Good practices in EEG-MRI: the utility of retrospective synchronization and PCA for the removal of MRI gradient artefacts

The electroencephalogram (EEG) recorded during magnetic resonance imaging (MRI) inside the scanner is obstructed by the MRI gradient artefact (MGA) originating from the electromagnetic interference of the MRI with the sensitive measurement of electrical scalp potentials. Post-processing algorithms based on average artefact subtraction (AAS) have proven to be efficient in removing the MGA. However, the residual MGA after AAS still limits the quality and usable bandwidth of the EEG data despite further reduction through re-sampling, principal component analysis (PCA), and regressive filtering. We recently demonstrated that the residual MGA can largely be avoided by means of hardware synchronization. Here we present a new software synchronization method, which substitutes hardware synchronization and facilitates the removal of motion artefacts by PCA. The effectiveness of the retrospective synchronization algorithm (Resync) is demonstrated by comparison to the aforementioned techniques. For this purpose, we also developed a method for simulating the MGA and we propose new concepts for quantifying and comparing the performance of post-processing algorithms for EEG-MRI data. Results indicate that the benefits of (retrospective) synchronization and PCA depend largely on the relative contribution of timing errors and motion artefacts to the residual MGA as well as the frequency range of interest.

New cardiac MRI gating method using event-synchronous adaptive digital filter

When imaging the heart using MRI, an artefact-free electrocardiograph (ECG) signal is not only important for monitoring the patient's heart activity but also essential for cardiac gating to reduce noise in MR images induced by moving organs. The fundamental problem in conventional ECG is the distortion induced by electromagnetic interference. Here, we propose an adaptive algorithm for the suppression of MR gradient artefacts (MRGAs) in ECG leads of a cardiac MRI gating system. We have modeled MRGAs by assuming a source of strong pulses used for dephasing the MR signal. The modeled MRGAs are rectangular pulse-like signals. We used an event-synchronous adaptive digital filter whose reference signal is synchronous to the gradient peaks of MRI. The event detection processor for the event-synchronous adaptive digital filter was implemented using the phase space method-a sort of topology mapping method-and least-squares acceleration filter. For evaluating the efficiency of the proposed method, the filter was tested using simulation and actual data. The proposed method requires a simple experimental setup that does not require extra hardware connections to obtain the reference signals of adaptive digital filter. The proposed algorithm was more effective than the multichannel approach.

Alterations in human ECG due to the MagnetoHydroDynamic effect: a method for accurate R peak detection in the presence of high MHD artifacts

Blood flow in high static magnetic fields induces elevated voltages that contaminate the ECG signal which is recorded simultaneously during MRI scans for synchronization purposes. This is known as the magnetohydrodynamic (MHD) effect, it increases the amplitude of the T wave, thus hindering correct R peak detection. In this paper, we inspect the MHD induced alterations of human ECG signals recorded in a 1.5 Tesla steady magnetic field and establish a primary characterization of the induced changes using time and frequency domain analysis. We also reexamine our previously developed real time algorithm for MRI cardiac gating and determine that, with a minor modification, this algorithm is capable of achieving perfect detection even in the presence of strong MHD artifacts.

Synchronisation strategies in T2-weighted MR imaging for detection of liver lesions: Application on a nude mouse model

AIM

The objective of this work was to propose original synchronisation strategies based on T2-weighted sequence performed on a small animal MRI spectrometer in order to improve the image contrast and detect mouse liver lesions at high magnetic field.

MATERIALS AND METHODS

The experiments were performed in vivo at 7T using a 32 mm inner diameter cylindrical volumetric coil for both RF emission and reception. A sensitive pressure sensor was used to detect external movements due to both respiration and heart beats. The pressure sensor was interfaced with a commercial ECG Trigger Unit to use dedicated functionalities (trigger levels, delays and window). To enable T2-weighted imaging with minimised T1 effects, an acquisition strategy with controlled TR spanning over several respiratory cycles was developed. With this strategy, the slices were acquired over several respiratory periods.

RESULTS

The acquisition, performed over several respiratory periods, enables a longer TR than the typical mouse respiratory period. The image contrast is controllable and independent of the respiratory period. The heavily T2-weighted images obtained with the developed strategy allow better visualisation of lesions at high magnetic field. Moreover, double respiratory and cardiac synchronisation, based on a unique sensitive pressure sensor, improves image quality with less motion artifacts, especially in the ventral liver region. The total slice number is independent of respiratory period and thin slices can be acquired to cover the whole liver.

CONCLUSION

The developed strategy enables high quality pure T2-weighted imaging with minimal motion artifacts. This strategy improves T2-weighted image contrast and quality, especially at high magnetic field, on animals with short respiratory periods. The strategy was demonstrated using a mouse model of liver lesions at 7T. This protocol could be used to carry out a longitudinal follow-up.

A comparative study of different artefact removal algorithms for EEG signals acquired during functional MRI

In electroencephalographic (EEG) measurements performed during functional Magnetic Resonance Imaging (fMRI), imaging and cardiac artefacts strongly contaminate the EEG signal. Several algorithms have been proposed to suppress these artefacts and most of them have shown important improvements with respect to uncorrected signals. However, the relative performances of these algorithms have not been properly assessed. In particular, it is not known to what extent such algorithms deteriorate the EEG signal of interest. In this study, we propose to cross-validate different methods proposed for artefact correction, using a forward model to generate EEG and MR-related artefacts. The methods are assessed under various experimental conditions (described in terms of EEG sampling rate, artefacts amplitude, frequency band of interest, etc.). Using experimental data, we also tested the performance of the correction methods for alpha rhythm imaging and for epileptic spike reconstruction. Results show that most of the methods allow the observation of the modulation of alpha rhythms and the identification of spikes, despite subtle differences between algorithms. They also show that over-filtering the data may degrade the EEG. Our results indicate that the optimal artefact removal technique should be chosen according to whether one is interested in fast (>10 Hz) vs. slow (<10 Hz) oscillations or in evoked vs. ongoing activity.

Noise cancellation signal processing method and computer system for improved real-time electrocardiogram artifact correction during MRI data acquisition

A system was developed for real-time electrocardiogram (ECG) analysis and artifact correction during magnetic resonance (MR) scanning, to improve patient monitoring and triggering of MR data acquisitions. Based on the assumption that artifact production by magnetic field gradient switching represents a linear time invariant process, a noise cancellation (NC) method is applied to ECG artifact linear prediction. This linear prediction is performed using a digital finite impulse response (FIR) matrix, that is computed employing ECG and gradient waveforms recorded during a training scan. The FIR filters are used during further scanning to predict artifacts by convolution of the gradient waveforms. Subtracting the artifacts from the raw ECG signal produces the correction with minimal delay. Validation of the system was performed both off-line, using prerecorded signals, and under actual examination conditions. The method is implemented using a specially designed Signal Analyzer and Event Controller (SAEC) computer and electronics. Real-time operation was demonstrated at 1 kHz with a delay of only 1 ms introduced by the processing. The system opens the possibility of automatic monitoring algorithms for electrophysiological signals in the MR environment.

Cardiac and Respiratory MRI Gating Using Combined Wavelet Sub-Band Decomposition and Adaptive Filtering

Cardiac Magnetic Resonance Imaging (MRI) requires synchronization to overcome motion related artifacts caused by the heart's contractions and the chest wall movements during respiration. Achieving good image quality necessitates combining cardiac and respiratory gating to produce, in real time, a trigger signal that sets off the consecutive image acquisitions. This guarantees that the data collection always starts at the same point of the cardiac cycle during the exhalation phase. In this paper, we present a real time algorithm for extracting a cardiac-respiratory trigger signal using only one, adequately placed, ECG sensor. First, an off-line calculation phase, based on wavelet decomposition, is run to compute an optimal QRS filter. This filter is used, afterwards, to accomplish R peak detection, while a low pass filtering process allows the retrieval of the respiration cycle. The algorithm's synchronization capabilities were assessed during mice cardiac MRI sessions employing three different imaging sequences, and three specific wavelet functions. The prominent image enhancement gave a good proof of correct triggering. QRS detection was almost flawless for all signals. As for the respiration cycle retrieval it was evaluated on contaminated simulated signals, which were artificially modulated to imitate respiration. The results were quite satisfactory.

Investigations of back muscle fatigue by simultaneous 31P MRS and surface EMG measurements

Investigations of back muscle fatigue are important for understanding the role of muscle strain in the development of low back pain. The aim of this contribution is to review the two main techniques used for in vivo investigations of metabolic and electrophysiological changes, namely magnetic resonance phosphorous spectroscopy ((31)P MRS) and surface electromyography (SEMG), and to report some of our recent results on simultaneous measurements using these techniques during isometric back-muscle contraction in volunteers. Since it appears that electrophysiological and metabolic factors are simultaneously involved in the processes of fatigue and muscle recovery during load application, simultaneous acquisition of complete information is quite promising for obtaining new insights into the metabolic origin of electrophysiological changes or vice versa. Performing these measurements simultaneously, however, is more intricate owing to the occurrence of signal artifacts caused by mutual signal interferences of both techniques. Besides these mutual disturbances, further experimental difficulties are related to spatial limitations within the bore of clinical whole-body high-field magnetic resonance (MR) systems (1.5 T) and the sensitivity of MR measurements to motion-induced artifacts. Our own experimental results are presented, and problems that occur using both techniques simultaneously, as well as possibilities to resolve them, are discussed. The results shed light on the interrelation of electrophysiological and metabolic changes during fatigue of the back muscle while performing an exercise.

Optimisation of a post-processing method to remove the pulse artifact from EEG data recorded during fMRI: An application to P300 recordings during e-fMRI

In functional cerebral studies, it has been established that co-registered electroencephalography (EEG) measurements and functional magnetic resonance imaging (fMRI) were complementary. However, EEG data recorded inside an MRI scanner are heavily distorted, mainly by the most prominent artifact, the cardiac pulse artifact (PA). We describe an original algorithm which yields a high-quality PA filter and demonstrates how this tool can be used to improve the quality of P300 ERP measurements during event-related fMRI (e-fMRI) experiments. EEG data were acquired in interleaved mode during e-fMRI while six healthy volunteers performed a visual odd-ball task, involving Distractors, Target and Novel stimuli, to elicit P300 components. The PA was corrected with the original algorithm. The temporal variations in the PA were evidenced using a principal component analysis (PCA), on each EEG channel. The procedure yielded several PA templates, which were regressed from the EEG data. The PA removal procedure was optimised, and then implemented to improve the measured P300 components. Regressing the most adequate PA template resulted in a high-quality reduction in spectral power at frequencies associated with the cardiac PA. More reliable P300 component measurements were obtained, evidencing higher amplitudes for Novels (9.76-11.20 microV) than for to Targets (6.3-9.09 microV) in centro-parietal and prefrontal areas. The improvement of the processing of EEG data acquired simultaneously with fMRI data provides a new tool and casts perspectives to study the functional organisation of the brain.

the effect of pathologic cardiac events on the spectral content of ECG

We designed a method of power spectral density (PSD) estimation of Electrocardiogram (ECG) signal in the normal and pathologic cases. MIT signal database was used as a source of signals. PQRST and QRS extraction methods are developed, the resulting complexes are then classified as normal or pathologic and are spectrally studied. For the spectral study, we used the maximal, mean, minimal frequencies as well as signal-energy in order to describe the spectra of normal and pathologic ECG events. Finally, we defined the quantitative and qualitative spectral modifications as a spectral biasing or signal's energy reduction.

Complete artifact removal for EEG recorded during continuous fMRI using independent component analysis

The simultaneous recording of EEG and fMRI is a promising method for combining the electrophysiological and hemodynamic information on cerebral dynamics. However, EEG recordings performed in the MRI scanner are contaminated by imaging, ballistocardiographic (BCG) and ocular artifacts. A number of processing techniques for the cancellation of fMRI environment disturbances exist: the most popular is averaged artifact subtraction (AAS), which performs well for the imaging artifact, but has some limitations in removing the BCG artifact, due to the variability in cardiac wave duration and shape; furthermore, no processing method to attenuate ocular artifact is currently used in EEG/fMRI, and contaminated epochs are simply rejected before signal analysis. In this work, we present a comprehensive method based on independent component analysis (ICA) for simultaneously removing BCG and ocular artifacts from the EEG recordings, as well as residual MRI contamination left by AAS. The ICA method has been tested on event-related potentials (ERPs) obtained from a visual oddball paradigm: it is very effective in attenuating artifacts in order to reconstruct clear brain signals from EEG acquired in the MRI scanner. It performs significantly better than the AAS method in removing the BCG artifact. Furthermore, since ocular artifacts can be completely suppressed, a larger number of trials is available for analysis. A comparison of ERPs inside the magnetic environment with those obtained out of the MRI scanner confirms that no systematic bias in the ERP waveform is produced by the ICA method.

Improving automatic analysis of the electrocardiogram acquired during magnetic resonance imaging using magnetic field gradient artefact suppression

The electrocardiogram (ECG) used for patient monitoring during magnetic resonance imaging (MRI) unfortunately suffers from severe artefacts. These artefacts are due to the special environment of the MRI. Modeling helped in finding solutions for the suppression of these artefacts superimposed on the ECG signal. After we validated the linear and time invariant model for the magnetic field gradient artefact generation, we applied offline and online filters for their suppression. Wiener filtering (offline) helped in generating reference annotations of the ECG beats. In online filtering, the least-mean-square filter suppressed the magnetic field gradient artefacts before the acquired ECG signal was input to the arrhythmia algorithm. Comparing the results of two runs (one run using online filtering and one run without) to our reference annotations, we found an eminent improvement in the arrhythmia module's performance, enabling reliable patient monitoring and MRI synchronization based on the ECG signal.

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.

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.