B. Tilg

Noninvasive myocardial activation time imaging: a novel inverse algorithm applied to clinical ECG mapping data

Linear approaches like the minimum-norm least-square algorithm show insufficient performance when it comes to estimating the activation time map on the surface of the heart from electrocardiographic (ECG) mapping data. Additional regularization has to be considered leading to a nonlinear problem formulation. The Gauss-Newton approach is one of the standard mathematical tools capable of solving this kind of problem. To our experience, this algorithm has specific drawbacks which are caused by the applied regularization procedure. In particular, under clinical conditions the amount of regularization cannot be determined clearly. For this reason, we have developed an iterative algorithm solving this nonlinear problem by a sequence of regularized linear problems. At each step of iteration, an individual L-curve is computed. Subsequent iteration steps are performed with the individual optimal regularization parameter. This novel approach is compared with the standard Gauss-Newton approach. Both methods are applied to simulated ECG mapping data as well as to single beat sinus rhythm data from two patients recorded in the catheter laboratory. The proposed approach shows excellent numerical and computational performance, even under clinical conditions at which the Gauss-Newton approach begins to break down.

Model-based imaging of cardiac electrical excitation in humans

Activation time (AT) imaging from electrocardiographic (ECG) mapping data has been developing for several years. By coupling ECG mapping and three-dimensional (3-D) + time anatomical data, the electrical excitation sequence can be imaged completely noninvasively in the human heart. In this paper, a bidomain theory-based surface heart model AT imaging approach was applied to single-beat data of atrial and ventricular depolarization in two patients with structurally normal hearts. In both patients, the AT map was reconstructed from sinus and paced rhythm data. Pacing sites were the apex of the right ventricle and the coronary sinus (CS) ostium. For CS pacing, the reconstructed AT pattern on the endocardium of the right atrium was compared with the CARTO map in both patients. The localization errors of the origins of the initial endocardial breakthroughs were determined to be 6 and 12 mm. The sites of early activation and the areas with late activation were estimated with sufficient accuracy. The reconstructed sinus rhythm sequence was in good qualitative agreement with the pattern previously published for the isolated Langendorff-perfused human heart.

A new spatiotemporal regularization approach for reconstruction of cardiac transmembrane potential patterns

The single-beat reconstruction of electrical cardiac sources from body-surface electrocardiogram data might become an important issue for clinical application. The feasibility and field of application of noninvasive imaging methods strongly depend on development of stable algorithms for solving the underlying ill-posed inverse problems. We propose a novel spatiotemporal regularization approach for the reconstruction of surface transmembrane potential (TMP) patterns. Regularization is achieved by imposing linearly formulated constraints on the solution in the spatial as well as in the temporal domain. In the spatial domain an operator similar to the surface Laplacian, weighted by a regularization parameter, is used. In the temporal domain monotonic nondecreasing behavior of the potential is presumed. This is formulated as side condition without the need of any regularization parameter. Compared to presuming template functions, the weaker temporal constraint widens the field of application because it enables the reconstruction of TMP patterns with ischemic and infarcted regions. Following the line of Tikhonov regularization, but considering all time points simultaneously, we obtain a linearly constrained sparse large-scale convex optimization problem solved by a fast interior point optimizer. We demonstrate the performance with simulations by comparing reconstructed TMP patterns with the underlying reference patterns.

Effects of Cardiac Resynchronization Therapy on Ventricular Repolarization in Patients with Congestive Heart Failure

Introduction: Biventricular pacing has been shown to improve the clinical status of patients with congestive heart failure, but little is known about its influence on ventricular repolarization. The aim of our study was to evaluate the effect of biventricular pacing on ECG markers of ventricular repolarization in patients with congestive heart failure.

Atrial Noninvasive Activation Mapping of Paced Rhythm Data

Introduction: Atrial arrhythmias have emerged as a topic of great interest for clinical electrophysiologists. Noninvasive imaging of electrical function in humans may be useful for computer‐aided diagnosis and treatment of cardiac arrhythmias, which can be accomplished by the fusion of data from ECG mapping and magnetic resonance imaging (MRI).

On Computing Dominant Frequency From Bipolar Intracardiac Electrograms

Dominant frequency (DF) computed from action potentials is a key parameter for investigating atrial fibrillation in animal studies and computer models. A recent clinical trial reported consistent results computing DF from 30 Hz to 400 Hz bandpass filtered bipolar electrograms in humans. The DF (<15 Hz and, thus, filtered out) was recovered by rectifying the signal, while the theoretical background of this approach was left uncommented. It is the focus of this paper to provide this background by a Fourier analysis. We demonstrate that it is mainly the timing of the narrow deflections (local activation at the catheter tip) which contribute to the DF peak in the frequency spectrum. Due to the typical signal morphology pronounced harmonic peaks occur in the spectrum. This is a disadvantage when computing the regularity index (RI) as a parameter for local organization and signal quality. It is demonstrated for synthetical and patient data that at low DF the RI is far below the optimal value one even for high underlying organization and good signal quality. The insight obtained promotes the development of better measures for organization. The finding that mainly timing of activation contributes to DF might promote the development of powerful realtime signal processing tools for computing DF

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.

Lead field computation for the electrocardiographic inverse problem-finite elements versus boundary elements

In order to be able to solve the inverse problem of electrocardiography, the lead field matrix (transfer matrix) has to be calculated. The two methods applied for computing this matrix, which are compared in this study, are the boundary element method (BEM) and the finite element method (FEM). The performance of both methods using a spherical model was investigated. For a comparable discretization level, the BEM yields smaller relative errors compared to analytical solutions. The BEM needs less computation time, but a larger amount of memory. Inversely calculated myocardial activation times using either the FEM or BEM computed lead field matrices give similar activation time patterns. The FEM, however, is also capable of considering anisotropic conductivities. This property might have an impact for future development, when also individual myocardial fiber architecture can be considered in the inverse formulation.

A comparison of noninvasive reconstruction of epicardial versus transmembrane potentials in consideration of the null space

We compare two source formulations for the electrocardiographic forward problem in consideration of their implications for regularizing the ill-posed inverse problem. The established epicardial potential source model is compared with a bidomain-theory-based transmembrane potential source formulation. The epicardial source approach is extended to the whole heart surface including the endocardial surfaces. We introduce the concept of the numerical null and signal space to draw attention to the problems associated with the nonuniqueness of the inverse solution and show that reconstruction of null-space components is an important issue for physiologically meaningful inverse solutions. Both formulations were tested with simulated data generated with an anisotropic heart model and with clinically measured data of two patients. A linear and a recently proposed quasi-linear inverse algorithm were applied for reconstructions of the epicardial and transmembrane potential, respectively. A direct comparison of both formulations was performed in terms of computed activation times. We found the transmembrane potential-based formulation is a more promising source formulation as stronger regularization by incorporation of biophysical a priori information is permitted.

Cardiac anisotropy: is it negligible regarding noninvasive activation time imaging?

The aim of this study was to quantify the effect of cardiac anisotropy in the activation-based inverse problem of electrocardiography. Differences of the patterns of simulated body surface potential maps for isotropic and anisotropic conditions were investigated with regard to activation time (AT) imaging of ventricular depolarization. AT maps were estimated by solving the nonlinear inverse ill-posed problem employing spatio-temporal regularization. Four different reference AT maps (sinus rhythm, right-ventricular and septal pacing, accessory pathway) were calculated with a bidomain theory based anisotropic finite-element heart model in combination with a cellular automaton. In this heart model a realistic fiber architecture and conduction system was implemented. Although the anisotropy has some effects on forward solutions, effects on inverse solutions are small indicating that cardiac anisotropy might be negligible for some clinical applications (e.g., imaging of focal events) of our AT imaging approach. The main characteristic events of the AT maps were estimated despite neglected electrical anisotropy in the inverse formulation. The worst correlation coefficient of the estimated AT maps was 0.810 in case of sinus rhythm. However, all characteristic events of the activation pattern were found. The results of this study confirm our clinical validation studies of noninvasive AT imaging in which cardiac anisotropy was neglected.