Effects of simultaneous EEG recording on MRI data quality at 1.5, 3 and 7 tesla

Abstract

Although the focus of attention on data degradation during simultaneous MRI/EEG recording has to date largely been upon EEG artefacts, the presence of the conducting wires and electrodes of the EEG recording system also causes some degradation of MRI data quality. This may result from magnetic susceptibility effects which lead to signal drop-out and image distortion, as well as the perturbation of the radiofrequency fields, which can cause local signal changes and a global reduction in the signal to noise ratio (SNR) of magnetic resonance images. Here, we quantify the effect of commercially available 32 and 64 electrode caps on the quality of MR images obtained in scanners operating at magnetic fields of 1.5, 3 and 7 T, via the use of MR-based, field-mapping techniques and analysis of the SNR in echo planar image time series. The electrodes are shown to be the dominant source of magnetic field inhomogeneity, although the localised nature of the field perturbation that they produce means that the effect on the signal intensity from the brain is not significant. In the particular EEG caps investigated here, RF inhomogeneity linked to the longer ECG and EOG leads causes some reduction in the signal intensity in images obtained at 3 and 7 T. Measurements of the standard deviation of white matter signal in EPI time series indicates that the introduction of the EEG cap produces a small reduction in the image signal to noise ratio, which increases with the number of electrodes used.

Introduction

Combined electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is becoming an increasingly popular tool for the investigation of human brain function. The combination of these techniques has already been shown to have great potential for providing new understanding of the relationship between both spontaneous and evoked electrical activity and the haemodynamic response in the human brain (Goldman et al., 2002, Laufs et al., 2003, Scarff et al., 2004, Debener et al., 2005). The value of this approach in the study of diseases, such as epilepsy, has also become apparent (Lemieux et al., 2001, Lemieux, 2004). The largest challenge in the implementation of simultaneous EEG and fMRI lies in recording the weak electrical signals from the brain in the presence of the large voltages resulting from the time-varying magnetic field gradients that are needed for MRI, as well as those due to cardiac related movement in the strong static magnetic field of the magnetic resonance (MR) scanner. The focus of most technical work in this area has therefore been on characterisation and elimination of the artefacts in EEG recordings made simultaneously with MRI (Allen et al., 1998, Allen et al., 2000, Anami et al., 2003, Debener et al., 2007-this issue). This work has of course, been crucial in making it possible to record useful EEG data in combined EEG/fMRI experiments. The degradation of MR images due to the presence of the EEG equipment has been less well explored, since it has proved possible to acquire fMRI data with simultaneous EEG recording without making any significant modifications to the MRI techniques or hardware. However, as simultaneous EEG and fMRI is applied across more areas of research, it is important to understand the effect of the combined approach on the data acquired using both modalities.

It has previously been shown that the presence of the EEG recording apparatus can have an adverse effect on the quality of MR image data (Krakow et al., 2000, Lazeyras et al., 2001, Scarff et al., 2004, Vasios et al., 2006). Scarff et al. (2004) noted that the signal to noise ratio (SNR) of MR images decreased with increasing numbers of EEG electrodes. Their analysis was carried out on T₂^⁎-weighted images acquired using echo planar imaging (EPI), the imaging technique that is most commonly used in fMRI studies, and the SNR measurement was made by comparing the average signal within a brain region to the standard deviation across an area outside the head containing only noise. Some investigative work has also been carried out by Vasios et al. (2006) on the effects of their “InkCap” system on the SNR in echo planar images of the human brain, indicating that this system has very little effect on image quality. The same group has also measured the effect of EEG caps on the quality of retinotopic maps obtained using fMRI (Bonmassar et al., 2001) showing the cap has little effect. The work done by Krakow et al. (2000) was more extensive, involving study of the effects of the different components of the EEG system on images of phantoms and human subjects acquired using EPI. The in-plane spatial extent of the image artefact was used as a measure of the severity of the effect produced by a variety of electrodes, resistors and leads. The largest artefacts were found to be produced by injudiciously chosen resistors. In addition, the artefact due to any combination of materials was found to be “comparable to that of the worst single component” (Krakow et al., 2000). These authors also investigated the artefacts caused by conductive gel and paste/gel mixtures used for conventional EEG recordings. These artefacts were found to be significant, leading to the recommendation that the minimum possible amount of gel should be used.

The previous work in this area has concentrated on the characterisation of artefacts due to the EEG system in fMRI data, rather than exploration of the mechanisms underlying the degradation of image quality and has been somewhat qualitative in nature. There are a number of possible sources of degradation of MR images in the presence of the EEG recording apparatus, but the most important effects may be those of (i) the magnetic susceptibility of the cap materials on the homogeneity of the static magnetic field, and, (ii) the electrically conducting elements of the EEG system on the uniformity of the radio frequency (RF) fields involved in excitation and detection of the MR signal.

MRI relies on the use of a strong and extremely homogenous magnetic field, B₀, which usually varies in strength by less than 1 part per million over the imaging region. Unfortunately, whenever an object is placed inside the magnet its presence disturbs the homogeneity of the field. The magnitude of the field disturbance is of order χB₀, where χ is the magnetic susceptibility of the object, although the exact spatial form of the field perturbation depends on the shape of the object and its orientation with respect to the main field. The magnetic susceptibility of water is about − 9 × 10^− 6 whilst that of air is approximately zero, with most tissues of the human body having χ-values close to that of water. The materials used in EEG caps are also only weakly magnetic (e.g. for copper, χ = − 9.2 × 10^− 6), but unfortunately the high sensitivity of MRI to field perturbations means that field changes of only a few micro-Tesla can cause image artefacts. This is because the frequency of the NMR signal is 42.6 MHz per Tesla of applied field, so that even small changes in field cause significant frequency variation (e.g. 1 μT causes a 42.6 Hz frequency offset). Consequently the presence of the EEG electrodes and leads can introduce artefacts in MR image data due to magnetic field inhomogeneity. These artefacts take two main forms. First, field inhomogeneity leads to image distortion, an effect which becomes important when frequency offsets are similar in size to the frequency separation of pixels in the image. This is a particular problem in EPI since for this sequence the separation of pixels is large (typically 10–50 Hz). Second, if the variation in frequency across the imaging slice is large the signal in gradient echo images will be reduced, leading to regions of signal loss or “drop-out”. This effect is a consequence of the variation of the phase of the NMR signal coming from different positions across the slice and it becomes significant when the range of frequencies across the slice, Δf, is large enough that Δf × TE ∼ 1, where TE is the echo time. It is often the case that signal drop-out is a more significant problem than image distortion in fMRI data. Clearly the extent of signal drop-out and image distortion will depend on the magnetic susceptibilities of the materials used in the electrodes and leads and their spatial arrangement with respect to the subject's head and applied field. Maps showing the spatial variation of field offsets would provide useful information about the dominant sources of artefact.

MRI also relies on the use of an RF coil that produces a uniform magnetic field varying at the NMR frequency (e.g. 128 MHz at 3 T) when energised. The strength of the rotating component of this magnetic field which interacts with the nuclear magnetization is usually written as B₁. To generate an MR image it is necessary to excite an NMR signal from the sample which is done by applying an RF pulse via the RF coil. The effect of this pulse is to rotate the nuclear magnetization from its equilibrium state of alignment with the applied B₀ field, by an angle, θ, that depends on the product of B₁ and the duration of the RF pulse. The NMR signal that is used to form an MR image depends on the amount of transverse magnetization generated by the RF pulse, which is proportional to sinθ. Any variation in the strength of B₁ over the object being imaged will therefore give rise to unwanted intensity variation in the resulting image. The strength of the signal received from a particular region of the object also depends on the value of B₁ in that region (via the principle of reciprocity) giving rise to further intensity variation in the presence of any spatial inhomogeneity of B₁. When materials of high electrical conductivity are exposed to RF, large surface current densities which act to screen the RF field from the interior of the material are generated. These currents also disturb the B₁-field within regions in close proximity to the conductor. Consequently it can be expected that electrically conducting material in EEG caps will cause some perturbation of the B₁-field, leading to artefactual intensity variation in MR images. In addition, the interaction between the RF field and conducting material increases the effective resistance of the RF coil. Since a resistance acts as a source of noise, this effect can lead to a reduction in the SNR of images obtained in combined EEG/fMRI studies.

The aim of the work described in this paper was to characterise the artefacts generated in MR images by the presence of commercially available EEG recording hardware as a function of field strength and number of cap electrodes. Experiments were therefore conducted using 32 and 64 electrode caps on MR systems operating at 1.5, 3 and 7 T to evaluate the level of artefact and the SNR reduction manifested in echo planar images, as are typically used in fMRI experiments, due to the presence of the EEG recording system. Simple analysis of such data does not allow assignment of the source of artefacts specifically to B₁ or B₀ inhomogeneity. Such an assignment would however be valuable in deciding how to modify EEG cap arrangements so as to reduce the level of artefact. We also therefore carried out B₀ and B₁ mapping at the three field strengths so as to quantify the field perturbations produced by the 32 and 64 electrode caps.