Cardiac Propagation Pattern Mapping With Vector Field for Helping Tachyarrhythmias Diagnosis With Clinical Tridimensional Electro-Anatomical Mapping Tools

Abstract

Ventricular (VT) and atrial (AT) tachycardias are some of the most common clinical cardiac arrhythmias. For ablation of tachycardia substrates, two clinical diagnosis methods are used: invasive electro-anatomical mapping for an accurate diagnosis using electrograms (EGMs) acquired with intra-cardiac catheters, and localized on the surface mesh of the studied cavities; and non-invasive electrocardiographic imaging (ECGi) for a global view of the arrhythmia, with EGMs mathematically reconstructed from body surface electrocardiograms using 3-D cardio-thoracic surface meshes obtained from CT-scans. In clinics, VT and AT are diagnosed by studying activation time maps that depict the propagation of the activation wavefront on the cardiac mesh. Nevertheless, slow conduction areas - a well-known pro-arrhythmic feature for tachycardias - and tachycardia specific propagation patterns are not easily identifiable with these maps. Therefore, local characterization of the activation wavefront propagation can be helpful for improving VT and AT diagnoses. The purpose of this study is to develop a method to locally characterize the activation wavefront propagation for clinical data. For this, a conduction velocity (CV) vector field is estimated and analyzed using divergence and curl mathematical operators. The workflow was first validated on a simulated database from computer models, and then applied to a clinical database obtained from ECGi to improve AT diagnosis. The results show the relevancy and the efficacy of the proposed method to guide ablation of tachyarrhythmias.

Electrocardiographic predictors of successful resynchronization of left bundle branch block by His bundle pacing

“…Propagation discontinuity is not observed on direct endocardial contact mapping, 18 indicating the specific pattern of slowed or blocked propagation may be an artifact produced by the ECGI system's inverse solution 22 (which is also supported by in silico modeling 23 ) or an artifact arising from epi‐endo anisotropy. Importantly our study shows that these block artifacts correspond to biological phenomena due to their ability to identify patients amenable to resynchronization.…”

A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation

“…Several methods have been proposed for CV estimation, such as triangulation techniques, finite difference techniques or polynomial surface fitting (for a complete review see Cantwell et al, 2015 ). In this work, we follow the last approach by adapting the pipeline for the numerical approximation of CV, which was developed in Frontera et al ( 2020 ) for the left ventricle and designed starting from the work of Dallet et al ( 2018 ) and Roney et al ( 2019b ).…”

Challenges Associated with Interpreting Mechanisms of AF

“…Activation time maps can be post-processed to calculate conduction velocity maps. [51][52][53] Electrogram Features…”

“…55 Ablation of complex fractionated atrial electrograms (CFAE) terminated AF in 95% of patients in their study. 53 However, other groups have failed to replicate this success. 68,69 One confounding factor is that there are different definitions of…”

“…[ 55 ] Ablation of complex fractionated atrial electrograms (CFAE) terminated AF in 95% of patients in their study. [ 53 ] However, other groups have failed to replicate this success. [ 68 , 69 ] One confounding factor is that there are different definitions of fractionated electrograms, with the clinically used electroanatomical mapping software using different algorithms to calculate CFAE scores, which have been shown to correlate poorly with each other and with conduction velocity and the number of waves per AF cycle.…”