Influence of Modeling Errors on the Initial Estimate for Nonlinear Myocardial Activation Times Imaging Calculated With Fastest Route Algorithm

Abstract

Noninvasive reconstruction of cardiac electrical activity has a great potential to support clinical decision making, planning, and treatment. Recently, significant progress has been made in the estimation of the cardiac activation from body surface potential maps (BSPMs) using boundary element method (BEM) with the equivalent double layer (EDL) as a source model. In this formulation, noninvasive assessment of activation times results in a nonlinear optimization problem with an initial estimate calculated with the fastest route algorithm (FRA). Each FRA-simulated activation sequence is converted into the ECG. The best initialization is determined by the sequence providing the highest correlation between predicted and measured potentials. We quantitatively assess the effects of the forward modeling errors on the FRA-based initialization. We present three simulation setups to investigate the effects of volume conductor model simplifications, neglecting the cardiac anisotropy and geometrical errors on the localization of ectopic beats starting on the ventricular surface. For the analysis, 12-lead ECG and 99 electrodes BSPM system were used. The areas in the heart exposing the largest localization errors were volume conductor model and electrode configuration specific with an average error <10 mm. The results show the robustness of the FRA-based initialization with respect to the considered modeling errors.

Impact of the Endocardium in a Parameter Optimization to Solve the Inverse Problem of Electrocardiography

“…Unlike our method they showed that the choice of the initial estimates had an impact on the quality of the inverse procedure. This importance had also been reported by Potyagaylo et al (2016) and Erem et al (2014).…”

ECG imaging of ventricular tachycardia: evaluation against simultaneous non-contact mapping and CMR-derived grey zone

“…Spatio-temporal regularization with the method by Huiskamp and Greensite is well suited for stable reconstruction across the time points of a VT cycle, compared to methods that identify focal activity or that operate on single time points [46,49,50]. Further, it is better suited for cases with large scars compared to spatio-temporal methods that make rigorous assumptions on action potential shapes and tissue excitability, such as rule-based approaches [47] or the critical times method [26]. On the other hand, methods which require that TMV courses are non-decreasing in time [11,39] impose spatio-temporal constraints that leave room for behaviour associated with scar tissue, but they must make the assumption that electric sources from repolarization are negligible during VT cycles.…”

Electrical Properties Tomography Based on $B_{{1}}$ Maps in MRI: Principles, Applications, and Challenges

“…They are useful for understanding the distribution of electromagnetic field inside tissue. For example, accurate EP models are needed to localize the internal electrical activities based on noninvasive electrophysiological recording over the body surface such as electroencephalography (EEG) [ 14 ]–[ 19 ] and electrocardiography (ECG) [ 20 ]–[ 24 ]. On the other hand, EPs are critical to estimate the distribution of electric current and electromagnetic power inside the body in applications utilizing electromagnetic stimulation for treatment, such as deep brain stimulation (DBS) to mitigate Parkinson’s disease symptom [ 25 ]–[ 27 ], transcranial direct current stimulation [ 28 ], transcranial magnetic stimulation (TMS) in neuropsychiatry [ 29 ], radiofrequency (RF) ablation to remove arrhythmic genesis foci [ 30 ] and RF hyperthermia in cancer treatment [ 31 ].…”