Spatially Coherent Activation Maps for Electrocardiographic Imaging

Abstract

Abstract-Objective: Cardiac mapping is an important diagnostic step in cardiac electrophysiology. One of its purposes is to generate a map of the depolarization sequence. This map is constructed in clinical routine either by directly analyzing cardiac electrograms (EGM) recorded invasively or an estimate of these EGMs obtained by a non-invasive technique. Activation maps based on noninvasively estimated EGMs often show artefactual jumps in activation times. To overcome this problem we present a new method to construct the activation maps from reconstructed unipolar EGMs. Methods: On top of the standard estimation of local activation time from unipolar intrinsic deflections, we propose to mutually compare the EGMs in order to estimate the delays in activation for neighboring recording locations. We then describe a workflow to construct a spatially coherent activation map from local activation times and delay estimates in order to create more accurate maps. The method is optimized using simulated data and evaluated on clinical data from 12 different activation sequences. Results: We found that the standard methodology created lines of artificially strong activation time gradient. The proposed workflow enhanced these maps significantly. Conclusion: Estimating delays between neighbors is an interesting option for activation map computation in ECGi.

Improving the Spatial Solution of Electrocardiographic Imaging: A New Regularization Parameter Choice Technique for the Tikhonov Method

“…To test the effect of the new regularization parameter choice method and to compare with previous ones, eight different activation patterns (1 single site pacing in the right ventricular (RV) free wall, 1 single site pacing in the left ventricular (LV) lateral endocardial wall, 1 single site pacing in the LV mid wall, 1 single pacing site in the LV lateral epi and 4 single spiral waves) were simulated [19]. Propagating activation was simulated with a monodomain reaction-diffusion model in a realistic 3D model of the human ventricles, with transmembrane ionic currents computed with the Ten Tusscher et al model for the human ventricular myocyte [20].…”

Uniaxial strain of cultured mouse and rat cardiomyocyte strands slows conduction more when its axis is parallel to impulse propagation than when it is perpendicular

“…This approach, however, suffers from inaccuracies in the determination of ATs and from their round‐off to the next integer multiple of the sampling period (if the signals are not interpolated). As a more reliable method, we computed, as previously described, the conduction delays between all possible pairs of electrodes by finding the interpolated time of the negative‐to‐positive zero crossing of the Hilbert transform of the cross‐correlation function of the corresponding signals. A linear function of time a( x ) = x /θ + k was then fit to minimize the sum of the squared differences between the measured and fitted conduction delays.…”

Electrocardiographic Imaging Using a Spatio-Temporal Basis of Body Surface Potentials—Application to Atrial Ectopic Activity

“…We use the “global activation time” approach described in Dubois et al ( 2012 ), which is based on cross-correlating signals of nearby nodes to find their time delay. The method has further been advanced in Duchateau et al ( 2017 ) to combine delay-based and deflection-based activation times. In this work, however, we stick with the delay-only formulation.…”