Factors affecting the accuracy of the boundary element method in the forward problem--I: Calculating surface potentials

Tracking the Position of the Heart From Body Surface Potential Maps and Electrograms

The accurate generation of forward models is an important element in general research in electrocardiography, and in particular for the techniques for ElectroCardioGraphic Imaging (ECGI). Recent research efforts have been devoted to the reliable and fast generation of forward models. However, these model can suffer from several sources of inaccuracy, which in turn can lead to considerable error in both the forward simulation of body surface potentials and even more so for ECGI solutions. In particular, the accurate localization of the heart within the torso is sensitive to movements due to respiration and changes in position of the subject, a problem that cannot be resolved with better imaging and segmentation alone. Here, we propose an algorithm to localize the position of the heart using electrocardiographic recordings on both the heart and torso surface over a sequence of cardiac cycles. We leverage the dependency of electrocardiographic forward models on the underlying geometry to parameterize the forward model with respect to the position (translation) and orientation of the heart, and then estimate these parameters from heart and body surface potentials in a numerical inverse problem. We show that this approach is capable of localizing the position of the heart in synthetic experiments and that it reduces the modeling error in the forward models and resulting inverse solutions in canine experiments. Our results show a consistent decrease in error of both simulated body surface potentials and inverse reconstructed heart surface potentials after re-localizing the heart based on our estimated geometric correction. These results suggest that this method is capable of improving electrocardiographic models used in research settings and suggest the basis for the extension of the model presented here to its application in a purely inverse setting, where the heart potentials are unknown.

Integral equations and boundary-element solution for static potential in a general piece-wise homogeneous volume conductor

Boundary element methods (BEM) are used for forward computation of bioelectromagnetic fields in multi-compartment volume conductor models. Most BEM approaches assume that each compartment is in contact with at most one external compartment. In this work, I present a general surface integral equation and BEM discretization that remove this limitation and allow BEM modeling of general piecewise-homogeneous medium. The new integral equation allows positioning of field points at junctioned boundary of more than two compartments, enabling the use of linear collocation BEM in such a complex geometry. A modular BEM implementation is presented for linear collocation and Galerkin approaches, starting from the standard formulation. The approach and resulting solver are verified in four ways, including comparisons of volume and surface potentials to those obtained using the finite element method (FEM), and the effect of a hole in skull on electroencephalographic scalp potentials is demonstrated.

Comparison of spherical and realistically shaped boundary element head models for transcranial magnetic stimulation navigation

OBJECTIVE

MRI-guided real-time transcranial magnetic stimulation (TMS) navigators that apply electromagnetic modeling have improved the utility of TMS. However, their accuracy and speed depends on the assumed volume conductor geometry. Spherical models found in present navigators are computationally fast but may be inaccurate in some areas. Realistically shaped boundary-element models (BEMs) could increase accuracy at a moderate computational cost, but it is unknown which model features have the largest influence on accuracy. Thus, we compared different types of spherical models and BEMs.

METHODS

Globally and locally fitted spherical models and different BEMs with either one or three compartments and with different skull-to-brain conductivity ratios (1/1-1/80) were compared against a reference BEM.

RESULTS

The one-compartment BEM at inner skull surface was almost as accurate as the reference BEM. Skull/brain conductivity ratio in the range 1/10-1/80 had only a minor influence. BEMs were superior to spherical models especially in frontal and temporal areas (up to 20mm localization and 40% intensity improvement); in motor cortex all models provided similar results.

CONCLUSIONS

One-compartment BEMs offer a good balance between accuracy and computational cost.

SIGNIFICANCE

Realistically shaped BEMs may increase TMS navigation accuracy in several brain areas, such as in prefrontal regions often targeted in clinical applications.

An electrical heart model incorporating real geometry and motion

This paper describes an electrical model of the ventricles incorporating real geometry and motion. Cardiac geometry and motion is obtained from segmentations of multiple-slice MRI time sequences. A static heart model developed previously is deformed to match the observed geometry using a novel shape registration algorithm. The resulting electrocardiograms and body surface potential maps are compared to a static simulation in the resting heart. These results demonstrate that introducing motion into the cardiac model modifies the ECG during the T wave at peak contraction of the ventricles.

Evaluation of local electric fields generated by transcranial direct current stimulation with an extracephalic reference electrode based on realistic 3D body modeling

In this study, local electric field distributions generated by transcranial direct current stimulation (tDCS) with an extracephalic reference electrode were evaluated to address extracephalic tDCS safety issues. To this aim, we generated a numerical model of an adult male human upper body and applied the 3D finite element method to electric current conduction analysis. In our simulations, the active electrode was placed over the left primary motor cortex (M1) and the reference electrode was placed at six different locations: over the right temporal lobe, on the right supraorbital region, on the right deltoid, on the left deltoid, under the chin, and on the right buccinator muscle. The maximum current density and electric field intensity values in the brainstem generated by the extracephalic reference electrodes were comparable to, or even less than, those generated by the cephalic reference electrodes. These results suggest that extracephalic reference electrodes do not lead to unwanted modulation of the brainstem cardio-respiratory and autonomic centers, as indicated by recent experimental studies. The volume energy density was concentrated at the neck area by the use of deltoid reference electrodes, but was still smaller than that around the active electrode locations. In addition, the distributions of elicited cortical electric fields demonstrated that the use of extracephalic reference electrodes might allow for the robust prediction of cortical modulations with little dependence on the reference electrode locations.

Cardiac position sensitivity study in the electrocardiographic forward problem using stochastic collocation and boundary element methods

The electrocardiogram (ECG) is ubiquitously employed as a diagnostic and monitoring tool for patients experiencing cardiac distress and/or disease. It is widely known that changes in heart position resulting from, for example, posture of the patient (sitting, standing, lying) and respiration significantly affect the body-surface potentials; however, few studies have quantitatively and systematically evaluated the effects of heart displacement on the ECG. The goal of this study was to evaluate the impact of positional changes of the heart on the ECG in the specific clinical setting of myocardial ischemia. To carry out the necessary comprehensive sensitivity analysis, we applied a relatively novel and highly efficient statistical approach, the generalized polynomial chaos-stochastic collocation method, to a boundary element formulation of the electrocardiographic forward problem, and we drove these simulations with measured epicardial potentials from whole-heart experiments. Results of the analysis identified regions on the body-surface where the potentials were especially sensitive to realistic heart motion. The standard deviation (STD) of ST-segment voltage changes caused by the apex of a normal heart, swinging forward and backward or side-to-side was approximately 0.2 mV. Variations were even larger, 0.3 mV, for a heart exhibiting elevated ischemic potentials. These variations could be large enough to mask or to mimic signs of ischemia in the ECG. Our results suggest possible modifications to ECG protocols that could reduce the diagnostic error related to postural changes in patients possibly suffering from myocardial ischemia.

TMS modeling toolbox for realistic simulation

Transcranial magnetic stimulation (TMS) is a technique for brain stimulation using rapidly changing magnetic fields generated by coils. It has been established as an effective stimulation technique to treat patients suffering from damaged brain functions. Although TMS is known to be painless and noninvasive, it can also be harmful to the brain by incorrect focusing and excessive stimulation which might result in seizure. Therefore there is ongoing research effort to elucidate and better understand the effect and mechanism of TMS. Lately Boundary element method (BEM) and Finite element method (FEM) have been used to simulate the electromagnetic phenomenon of TMS. However, there is a lack of general tools to generate the models of TMS due to some difficulties in realistic modeling of the human head and TMS coils. In this study, we have developed a toolbox through which one can generate high-resolution FE TMS models. The toolbox allows creating FE models of the head with isotropic and anisotropic electrical conductivities in five different tissues of the head and the coils in 3D. The generated TMS model is importable to FE software packages such as ANSYS for further and efficient electromagnetic analysis. We present a set of demonstrative results of realistic simulation of TMS with our toolbox.

The inverse problem utilizing the boundary element method for a nonstandard female torso

This paper proposes a new method of rapidly deriving the transfer matrix for the boundary element method (BEM) forward problem from a tailored female torso geometry in the clinical setting. The method allows rapid calculation of epicardial potentials (EP) from body surface potentials (BSP). The use of EPs in previous studies has been shown to improve the successful detection of the life-threatening cardiac condition--acute myocardial infarction. The MRI scanning of a cardiac patient in the clinical setting is not practical and other methods are required to accurately deduce torso geometries for calculation of the transfer matrix. The new method allows the noninvasive calculation of tailored torso geometries from a standard female torso and five measurements taken from the body surface of a patient. This scaling of the torso has been successfully validated by carrying out EP calculations on 40 scaled torsos and ten female subjects. It utilizes the BEM in the calculation of the transfer matrix as the BEM depends only upon the topology of the surfaces of the torso and the heart, the former can now be accurately deduced, leaving only the latter geometry as an unknown.

3D modeling of the total electric field induced by transcranial magnetic stimulation using the boundary element method

Transcranial magnetic stimulation (TMS) delivers highly localized brain stimulations via non-invasive externally applied magnetic fields. This non-invasive, painless technique provides researchers and clinicians with a unique tool capable of stimulating both the central and peripheral nervous systems. However, a complete analysis of the macroscopic electric fields produced by TMS has not yet been performed. In this paper, we addressed the importance of the secondary E-field created by surface charge accumulation during TMS using the boundary element method (BEM). 3D models were developed using simple head geometries in order to test the model and compare it with measured values. The effects of tissue geometry, size and conductivity were also investigated. Finally, a realistically shaped head model was used to assess the effect of multiple surfaces on the total E-field. Secondary E-fields have the greatest impact at areas in close proximity to each tissue layer. Throughout the head, the secondary E-field magnitudes typically range from 20% to 35% of the primary E-field's magnitude. The direction of the secondary E-field was generally in opposition to the primary E-field; however, for some locations, this was not the case (i.e. going from high to low conductivity tissues). These findings show that realistically shaped head geometries are important for accurate modeling of the total E-field.

A Matlab library for solving quasi-static volume conduction problems using the boundary element method

The boundary element method (BEM) is commonly used in the modeling of bioelectromagnetic phenomena. The Matlab language is increasingly popular among students and researchers, but there is no free, easy-to-use Matlab library for boundary element computations. We present a hands-on, freely available Matlab BEM source code for solving bioelectromagnetic volume conduction problems and any (quasi-)static potential problems that obey the Laplace equation. The basic principle of the BEM is presented and discretization of the surface integral equation for electric potential is worked through in detail. Contents and design of the library are described, and results of example computations in spherical volume conductors are validated against analytical solutions. Three application examples are also presented. Further information, source code for application examples, and information on obtaining the library are available in the WWW-page of the library: (http://biomed.tkk.fi/BEM).

Development of volume conductor and source models to localize epileptic foci

SUMMARY

There is increasing interest in mapping and source reconstruction from electrocorticoencephalographic (ECoG) grid data and comparison to surface EEG evaluations of epileptic patients. ECoG mapping onto three-dimensional renderings of the individual cortical anatomy derived from magnetic resonance images and computed tomography (CT) is performed after coregistration of anatomical and functional coordinate systems. Source reconstructions from ECoG and EEG are compared using different source models and realistically shaped volume conductor models. Realistically shaped volume conductor models for EEG source reconstruction are a prerequisite for improved localization accuracy. Individual boundary element method (BEM) models derived from MRI represent the "gold standard" and can approximate isotropic homogeneous head compartments and thus give an improved description of the head shape as compared with classical oversimplifying spherical shell models. Anisotropic volume conduction properties of the bone layer or the white matter fibers can be described by the finite element method (FEM); unfortunately, these models require a huge computational effort and are thus not used in daily applications. To avoid this computational effort, head models derived from an averaged MRI dataset can be used. Highly refined models with a large number of nodes and thus better numerical accuracy can be used by this approach, because the setup is performed only once and the decomposed models or precomputed leadfield matrices are saved for later application. Individual image data are not at all needed, if an overlay of the reconstruction results with the anatomy is not desired. With precomputed leadfield matrices and linear interpolation techniques, at least standardized BEM and FEM volume conductor models derived from averaged MRI datasets can achieve the same computational speed as analytical spherical models. The smoothed cortical envelope is used as a realistically shaped single-shell volume conductor model for ECoG source reconstruction, whereas three-compartment BEM-models are required for EEG. The authors describe how to localize ECoG-grid electrode positions and how to segment the cortical surface from coregistered magnetic resonance and CT images. Landmark-based coregistration is performed using common fiducials in both image modalities. Another more promising automatic approach is based on mutual three-dimensional volume gray-level information. The ECoG electrode positions can be retrieved from three-dimensional CT slices manually using cursors in thresholded images with depth information. Alternatively, the smoothed envelope of the cortical surface segmented from the MRI is used to semiautomatically determine the grid electrode positions by marking the four corners and measuring distances along the smoothed surface. With extended source patches for cortically constrained scans and current density reconstructions, results from ECoG and surface EEG data were compared. Single equivalent dipoles were used to explain the EEG far fields, and results were compared with the original current density distributions explaining the ECoG data. The authors studied the performance of spherical and realistically shaped BEM volume conductor models for EEG and ECoG source reconstruction in spherical and nonspherical parts of the head with simulations and measured epileptic spike data. Only small differences between spherical and realistically shaped models were found in the spherical parts of the head, whereas realistically shaped models are superior to spherical approximations in both single-shell ECoG and three-shell EEG cases in the nonspherical parts, such as the temporal lobe areas. The ECoG near field is more complicated to interpret than the surface EEG far field and cannot be explained in general by simple equivalent dipoles. However, from simulations with realistically shaped volume conductor models and cortically constrained source models, the authors studied how the bone and skin layer act as spatial low pass filters that smooth and simplify the surface EEG maps generated by much more complicated-looking source configurations derived from measured ECoG data.

Evaluating the spatial relationship of event-related potential and functional MRI sources in the primary visual cortex

The integration of electroencephalogram (EEG) recordings and functional magnetic resonance imaging (fMRI) can provide considerable insight into brain functionality. However, the direct relationship between neural and hemodynamic activity is still poorly understood. Of particular interest is the spatial correspondence between event-related potential (ERP) and fMRI sources. In the current study we localized sources generated by a checkerboard stimulus presented to eight subjects using both EEG and fMRI. The location of the sources of the visual evoked potential (VEP) were estimated at each timepoint and compared to the location of peak fMRI activity. In the majority of participants we found that the N75 dipole location coincides with a region of positive blood oxygenation level-dependent (BOLD) activation and the P100 dipole location coincides with a region of negative BOLD activation. These findings demonstrate the importance of including the negative BOLD response in combined EEG/fMRI studies.

Effect of cardiac motion on body surface electrocardiographic potentials: an MRI-based simulation study

This paper describes an electrical model of cardiac ventricles incorporating real geometry and motion. The heart anatomy and its motion through the cardiac cycle are obtained from segmentations of multiple-slice MRI time sequences; the special conduction system is constructed using an automated mapping procedure from an existing static heart model. The heart model is mounted in an anatomically realistic voxel model of the human body. The cardiac electrical source and surface potentials are determined numerically using both a finite-difference scheme and a boundary-element method with the incorporation of the motion of the heart. The electrocardiograms (ECG) and body surface potential maps are calculated and compared to the static simulation in the resting heart. The simulations demonstrate that introducing motion into the cardiac model modifies the ECG signals, with the most obvious change occurring during the T-wave at peak contraction of the ventricles. Body surface potential maps differ in some local positions during the T-wave, which may be of importance to a number of cardiac models, including those incorporating inverse methods.

Diffuse photon propagation in multilayered geometries

Diffuse optical tomography (DOT) is an emerging functional medical imaging modality which aims to recover the optical properties of biological tissue. The forward problem of the light propagation of DOT can be modelled in the frequency domain as a diffusion equation with Robin boundary conditions. In the case of multilayered geometries with piecewise constant parameters, the forward problem is equivalent to a set of coupled Helmholtz equations. In this paper, we present solutions for the multilayered diffuse light propagation for a three-layer concentric sphere model using a series expansion method and for a general layered geometry using the boundary element method (BEM). Results are presented comparing these solutions to an independent Monte Carlo model, and for an example three layered head model.

Accuracy of quadratic versus linear interpolation in noninvasive Electrocardiographic Imaging (ECGI)

Electrocardiographic Imaging (ECGI) is a cardiac functional imaging modality, noninvasively reconstructing epicardial potentials, electrograms and isochrones (activation maps) from multi-channel body surface potential recordings. The procedure involves solving Laplace's equation in the source-free volume conductor between torso and epicardial surfaces, using Boundary Element Method (BEM). Previously, linear interpolation (LI) on three-noded triangular surface elements was used in the BEM formulation. Here, we use quadratic interpolation (QI) for potentials over six-noded linear triangles. The performance of LI and QI in ECGI is evaluated through direct comparison with measured data from an isolated canine heart suspended in a human-torso-shaped electrolyte tank. QI enhances the accuracy and resolution of ECGI reconstructions for two different inverse methods, Tikhonov regularization and Generalized Minimal Residual (GMRes) method, with the QI-GMRes combination providing the highest accuracy and resolution. QI reduces the average relative error (RE) between reconstructed and measured epicardial potentials by 25%. It preserves the amplitude (average RE reduced by 48%) and morphology of electrograms better (average correlation coefficient for QI approximately 0.97, LI approximately 0.92). We also applied QI to ECGI reconstructions in human subjects during cardiac pacing, where QI locates ventricular pacing sites with higher accuracy (< or = 10 mm) than LI (< or = 18 mm).

Fast multipole acceleration of the MEG/EEG boundary element method

The accurate solution of the forward electrostatic problem is an essential first step before solving the inverse problem of magneto- and electroencephalography (MEG/EEG). The symmetric Galerkin boundary element method is accurate but cannot be used for very large problems because of its computational complexity and memory requirements. We describe a fast multipole-based acceleration for the symmetric boundary element method (BEM). It creates a hierarchical structure of the elements and approximates far interactions using spherical harmonics expansions. The accelerated method is shown to be as accurate as the direct method, yet for large problems it is both faster and more economical in terms of memory consumption.

Use of the isolated problem approach for multi-compartment BEM models of electro-magnetic source imaging

The isolated problem approach (IPA) is a method used in the boundary element method (BEM) to overcome numerical inaccuracies caused by the high-conductivity difference in the skull and the brain tissues in the head. Hämäläinen and Sarvas (1989 IEEE Trans. Biomed. Eng. 36 165-71) described how the source terms can be updated to overcome these inaccuracies for a three-layer head model. Meijs et al (1989 IEEE Trans. Biomed. Eng. 36 1038-49) derived the integral equations for the general case where there are an arbitrary number of layers inside the skull. However, the IPA is used in the literature only for three-layer head models. Studies that use complex boundary element head models that investigate the inhomogeneities in the brain or model the cerebrospinal fluid (CSF) do not make use of the IPA. In this study, the generalized formulation of the IPA for multi-layer models is presented in terms of integral equations. The discretized version of these equations are presented in two different forms. In a previous study (Akalin-Acar and Gençer 2004 Phys. Med. Biol. 49 5011-28), we derived formulations to calculate the electroencephalography and magnetoencephalography transfer matrices assuming a single layer in the skull. In this study, the transfer matrix formulations are updated to incorporate the generalized IPA. The effects of the IPA are investigated on the accuracy of spherical and realistic models when the CSF layer and a tumour tissue are included in the model. It is observed that, in the spherical model, for a radial dipole 1 mm close to the brain surface, the relative difference measure (RDM*) drops from 1.88 to 0.03 when IPA is used. For the realistic model, the inclusion of the CSF layer does not change the field pattern significantly. However, the inclusion of an inhomogeneity changes the field pattern by 25% for a dipole oriented towards the inhomogeneity. The effect of the IPA is also investigated when there is an inhomogeneity in the brain. In addition to a considerable change in the scale of the potentials, the field pattern also changes by 15%. The computation times are presented for the multi-layer realistic head model.

Symmetric BEM formulation for the M/EEG forward problem

The forward M/EEG problem consists in simulating the electric potential and the magnetic field produced outside the head by currents in the brain related to neural activity. All previously proposed solutions using the Boundary Element Method (BEM) were based on a double-layer integral formulation. We have developed an alternative symmetric BEM formulation, achieving a significantly higher accuracy for sources close to tissue interfaces, namely in the cortex. Numerical experiments using a spherical semi-realistic multilayer head model with a known analytical solution are presented, showing that the new BEM performs better than the formulations used in our earlier comparisons, and in most cases outperforms the Finite Element Method (FEM) as far as accuracy is concerned, thus making the BEM a viable choice.

Error analysis of a Galerkin method to solve the forward problem in MEG using the boundary element method

Sources of brain activity, e.g. epileptic foci, can be localized with Magnetoencephalography (MEG) measurements by recording the magnetic field outside the head. For a successful surgery a very high localization accuracy is needed. The most often used conductor model in the source localization is an analytic sphere, which is not always adequate, and thus a realistically shaped conductor model is needed. In this paper we examine a Galerkin method with linear basis functions to solve the forward problem in MEG using the boundary element method. Its accuracy is compared to the collocation method with constant and linear basis functions. The accuracies are determined for a unit sphere for which analytic solutions are available. The Galerkin method gives a clear improvement in the accuracy of the forward problem especially for the tangential component of the magnetic field. At realistic MEG measurement distances from the brain the Galerkin method reaches a given accuracy with lower computational costs than the collocation methods starting from a few hundreds of unknowns. With larger meshes the difference for the Galerkin method increases significantly.

Effects of dipole position, orientation and noise on the accuracy of EEG source localization

BACKGROUND

The electroencephalogram (EEG) reflects the electrical activity in the brain on the surface of scalp. A major challenge in this field is the localization of sources in the brain responsible for eliciting the EEG signal measured at the scalp. In order to estimate the location of these sources, one must correctly model the sources, i.e., dipoles, as well as the volume conductor in which the resulting currents flow. In this study, we investigate the effects of dipole depth and orientation on source localization with varying sets of simulated random noise in 4 realistic head models.

METHODS

Dipole simulations were performed using realistic head models and using the boundary element method (BEM). In all, 92 dipole locations placed in temporal and parietal regions of the head with varying depth and orientation were investigated along with 6 different levels of simulated random noise. Localization errors due to dipole depth, orientation and noise were investigated.

RESULTS

The results indicate that there are no significant differences in localization error due tangential and radial dipoles. With high levels of simulated Gaussian noise, localization errors are depth-dependent. For low levels of added noise, errors are similar for both deep and superficial sources.

CONCLUSION

It was found that if the signal-to-noise ratio is above a certain threshold, localization errors in realistic head models are, on average the same for deep and superficial sources. As the noise increases, localization errors increase, particularly for deep sources.

Anatomically informed basis functions for EEG source localization: combining functional and anatomical constraints

Distributed linear solutions have frequently been used to solve the source localization problem in EEG. Here we introduce an approach based on the weighted minimum norm (WMN) method that imposes constraints using anatomical and physiological information derived from other imaging modalities. The anatomical constraints are used to reduce the solution space a priori by modeling the spatial source distribution with a set of basis functions. These spatial basis functions are chosen in a principled way using information theory. The reduced problem is then solved with a classical WMN method. Further (functional) constraints can be introduced in the weighting of the solution using fMRI brain responses to augment spatial priors. We used simulated data to explore the behavior of the approach over a range of the model's hyperparameters. To assess the construct validity of our method we compared it with two established approaches to the source localization problem, a simple weighted minimum norm and a maximum smoothness (Loreta-like) solution. This involved simulations, using single and multiple sources that were analyzed under different levels of confidence in the priors.

A standardized boundary element method volume conductor model

OBJECTIVES

We used a 3-compartment boundary element method (BEM) model from an averaged magnetic resonance image (MRI) data set (Montreal Neurological Institute) in order to provide simple access to realistically shaped volume conductor models for source reconstruction, as compared to individually derived models. The electrode positions were transformed into the model's coordinate system, and the best fit dipole results were transformed back to the original coordinate system. The localization accuracy of the new approach was tested in a comparison with simulated data and with individual BEM models of epileptic spike data from several patients.

METHODS

The standard BEM model consisted of a total of 4770 nodes, which describe the smoothed cortical envelope, the outside of the skull, and the outside of the skin. The electrode positions were transformed to the model coordinate system by using 3-5 fiducials (nasion, left and right preauricular points, vertex, and inion). The transformation consisted of an averaged scaling factor and a rigid transformation (translation and rotation). The potential values at the transformed electrode positions were calculated by linear interpolation from the stored transfer matrix of the outer BEM compartment triangle net. After source reconstruction the best fit dipole results were transformed back into the original coordinate system by applying the inverse of the first transformation matrix.

RESULTS

Test-dipoles at random locations and with random orientations inside of a highly refined reference BEM model were used to simulate noise-free data. Source reconstruction results using a spherical and the standardized BEM volume conductor model were compared to the known dipole positions. Spherical head models resulted in mislocation errors at the base of the brain. The standardized BEM model was applied to averaged and unaveraged epileptic spike data from 7 patients. Source reconstruction results were compared to those achieved by 3 spherical shell models and individual BEM models derived from the individual MRI data sets. Similar errors to that evident with simulations were noted with spherical head models. Standardized and individualized BEM models were comparable.

CONCLUSIONS

This new approach to head modeling performed significantly better than a simple spherical shell approximation, especially in basal brain areas, including the temporal lobe. By using a standardized head for the BEM setup, it offered an easier and faster access to realistically shaped volume conductor models as compared to deriving specific models from individual 3-dimensional MRI data.

On modeling the Wilson terminal in the boundary and finite element method

In clinical electrocardiography, the zero-potential is commonly defined by the Wilson central terminal. In the electrocardiographic forward and inverse problem, the zero-potential is often defined in a different way, e.g., by the sum of all node potentials yielding zero. This study presents relatively simple to implement techniques, which enable the incorporation of the Wilson Terminal in the boundary element method (BEM) and finite element method (FEM). For the BEM, good results are obtained when properly adopting matrix deflation for modeling the Wilson terminal. Applying other zero-potential-definitions, the obtained solutions contained a remarkable offset with respect to the reference defined by the Wilson terminal. In the inverse problem (nonlinear dipole fit), errors introduced by an erroneous zero-potential-definition can lead to displacements of more than 5 mm in the computed dipole location. For the FEM, a method similar to matrix deflation is proposed in order to properly consider the Wilson central terminal. The matrix obtained from this manipulation is symmetric, sparse and positive definite enabling the application of standard FEM-solvers.

Boundary element method volume conductor models for EEG source reconstruction

OBJECTIVES

The boundary element method (BEM) approximates the different compartments of volume conductor models by closed triangle meshes with a limited number of nodes. The shielding effect of the weakly conducting skull layer of the human head leads to decreasing potential gradients from the inside to the outside. Thus, there may be an optimum distribution of nodes to the compartments for a given number of nodes corresponding to a fixed computational effort, resulting in improved accuracy as compared to standard uniform distributions.

METHODS

Spherical and realistically shaped surfaces are approximated by 500, 1000, 2000, and 3000 nodes, each leading to BEM models with 1500-9000 nodes in total. Electrodes are placed on extended 10/20-system positions. Potential distributions of test-dipoles at 4000 random positions within the innermost compartment are calculated. Dipoles are then fitted using 192 different models to find the optimum node distribution.

RESULTS

Fitted dipole positions for all BEM models are evaluated to show the dependency of the averaged and maximum localization errors on their node distributions. Dipoles close to the innermost boundary exhibit the largest localization errors, which mainly depend on the refinement of this compartment's triangle mesh.

CONCLUSIONS

More than 500 nodes per compartment are needed for reliable BEM models. For a state-of-the-art model consisting of 6000 nodes overall, the best model consists of 3000, 2000, and 1000 nodes from the inside to the outside.

Evaluation of inverse methods and head models for EEG source localization using a human skull phantom

We used a real-skull phantom head to investigate the performances of representative methods for EEG source localization when considering various head models. We describe several experiments using a montage with current sources located at multiple positions and orientations inside a human skull filled with a conductive medium. The robustness of selected methods based on distributed source models is evaluated as various solutions to the forward problem (from the sphere to the finite element method) are considered. Experimental results indicate that inverse methods using appropriate cortex-based source models are almost always able to locate the active source with excellent precision, with little or no spurious activity in close or distant regions, even when two sources are simultaneously active. Superior regularization schemes for solving the inverse problem can dramatically help the estimation of sparse and focal active zones, despite significant approximation of the head geometry and the conductivity properties of the head tissues. Realistic head models are necessary, though, to fit the data with a reasonable level of residual variance.

Field patterns in a 3D tapered spiral model of the electrically stimulated cochlea

Despite the fact that cochlear implants are widely and successfully used in clinical practice, relatively little is known to date about the electric field patterns they set up in the cochlea. Based upon the available measurements and modelling results, the scala tympani is usually considered to be a preferential current pathway that acts like a leaky transmission line. Therefore, most authors assume the current thresholds to decay exponentially along the length of the scala tympani. Here we present potential distributions calculated with a fully three-dimensional, spiralling volume conduction model of the guinea pig cochlea, and try to identify its preferential current pathways. The relatively well conducting scala tympani turns out to be the main one indeed, but the exponential decay (J approximately e(-z)) of current is only a good description of the far-field behaviour. In the vicinity of the electrodes, i.e. near the fibres that are most easily excited, higher current densities are found, that are best described by a spherical spread of the current (J approximately 1/R(2)). The results are compared with those obtained with a variant of our previous, rotationally symmetric, model and with measurements in the literature. The implications of the findings are discussed in the light of simulated neural responses.

Improving the accuracy of the boundary element method by the use of second-order interpolation functions

The boundary element method (BEM) is a widely used method to solve biomedical electromagnetic volume conduction problems. The commonly used formulation of this method uses constant interpolation functions for the potential and flat triangular surface elements. Linear interpolation for the potential on a flat triangular mesh turned out to yield a better accuracy. In this paper, we introduce quadratic interpolation functions for the potential and quadratically curved surface elements, resulting from second-order spatial interpolation. Theoretically, this results in an accuracy that is inversely proportional to the third power of element size. The method is tested on a four concentric sphere geometry, representative for electroencephalogram modeling, and compared to previous solutions of this problem in literature. In addition, a cylindrical test configuration is used. We conclude that the use of quadratic interpolation functions for the potential and of quadratically curved surface elements in BEM results in a significant increase in accuracy and in some cases even a reduction of the computation time with the same number of nodes involved in the calculations.

The effect of geometric and topologic differences in boundary element models on magnetocardiographic localization accuracy

This study was performed to evaluate the changes in magnetocardiographic (MCG) source localization results when the geometry and the topology of the volume conductor model were altered. Boundary element volume conductor models of three patients were first constructed. These so-called reference torso models were then manipulated to mimic various sources of error in the measurement and analysis procedures. Next, equivalent current dipole localizations were calculated from simulated and measured multichannel MCG data. The localizations obtained with the reference models were regarded as the "gold standard." The effect of each modification was investigated by calculating three-dimensional distances from the gold standard localizations to the locations obtained with the modified model. The results show that the effect of the lungs and the intra-ventricular blood masses is significant for deep source locations and, therefore, the torso model should preferably contain internal inhomogeneities. However, superficial sources could be localized within a few millimeters even with nonindividual, so called standard torso models. In addition, the torso model should extend long enough in the pelvic region, and the positions of the lungs and the ventricles inside the model should be known in order to obtain accurate localizations.

Electric potential produced by a dipole in a homogeneous conducting sphere

The potential produced by a dipole in a homogeneous conducting sphere is useful in simulation study, and the current available solutions still suffer from some shortcomings. In this communication, a closed solution is developed for the precise calculation of the potential anywhere in the spherical model.

Forward problem solution of electromagnetic source imaging using a new BEM formulation with high-order elements

Representations of the active cell populations on the cortical surface via electric and magnetic measurements are known as electromagnetic source images (EMSIs) of the human brain. Numerical solution of the potential and magnetic fields for a given electrical source distribution in the human brain is an essential part of electromagnetic source imaging. In this study, the performance of the boundary element method (BEM) is explored with different surface element types. A new BEM formulation is derived that makes use of isoparametric linear, quadratic or cubic elements. The surface integration is performed with Gauss quadrature. The potential fields are solved assuming a concentric three-shell model of the human head for a tangential dipole at different locations. In order to achieve 2% accuracy in potential solutions, the number of quadratic elements is of the order of hundreds. However, with linear elements, this number is of the order of ten thousand. The relative difference measures (RDMs) are obtained for the numerical models that use different element types. The numerical models that employ quadratic and cubic element types provide superior performance over linear elements in terms of accuracy in solutions. Assuming a homogeneous sphere model of the head, the RDMs are also obtained for the three components (radial and tangential) of the magnetic fields. The RDMs obtained for the tangential fields are, in general, much higher than those obtained for the radial fields. Both quadratic and cubic elements provide superior performance compared with linear elements for a wide range of dipole locations.

EEG and MEG: forward solutions for inverse methods

A solution of the forward problem is an important component of any method for computing the spatio-temporal activity of the neural sources of magnetoencephalography (MEG) and electroencephalography (EEG) data. The forward problem involves computing the scalp potentials or external magnetic field at a finite set of sensor locations for a putative source configuration. We present a unified treatment of analytical and numerical solutions of the forward problem in a form suitable for use in inverse methods. This formulation is achieved through factorization of the lead field into the product of the moment of the elemental current dipole source with a "kernel matrix" that depends on the head geometry and source and sensor locations, and a "sensor matrix" that models sensor orientation and gradiometer effects in MEG and differential measurements in EEG. Using this formulation and a recently developed approximation formula for EEG, based on the "Berg parameters," we present novel reformulations of the basic EEG and MEG kernels that dispel the myth that EEG is inherently more complicated to calculate than MEG. We also present novel investigations of different boundary element methods (BEM's) and present evidence that improvements over currently published BEM methods can be realized using alternative error-weighting methods. Explicit expressions for the matrix kernels for MEG and EEG for spherical and realistic head geometries are included.

Application of high-order boundary elements to the electrocardiographic inverse problem

Eight-noded quadrilateral boundary elements are applied to the electrocardiographic inverse problem as an example for high-order boundary elements. It is shown that the choice of the shape functions used for approximation of the potentials has a remarkable influence on the solution obtained if the number of electrodes is smaller than the number of primary source points (under-determined equation system). Three different formulations are investigated considering a concentric spheres problem where an analytic solution is available: (a) the isoparametric formulation; (b) the quasi-first-order formulation; and (c) the pseudo-subparametric formulation as a new method. In a second step the pseudo-subparametric formulation (which provided the best results in the test problem) is applied to real word data. The transmembrane potential pattern of a 40 years old female suffering from severe heart failure and ventricular tachycardia after large anterior wall myocardial infarction is reconstructed for one time instant. Furthermore, an algorithm for the calculation of the transfer matrix is presented which avoids restrictions to the boundary element mesh caused by the placement of the electrodes.