Key result
An algorithm for imaging isochrones of ventricular activation using sparse Bayesian learning correlated closely with known local activation times obtained by contact mapping in a patient with scarred myocardium.
Why the study?
Electrocardiographic imaging aids pre-procedure planning for catheter ablation, prompting the evaluation of a new algorithm for calculating global myocardial activation times in structurally normal and scarred ventricular myocardium.
Case Report (n=1)
No
A novel non-invasive electrocardiographic imaging algorithm accurately estimates global myocardial activation times and captures abnormal propagation patterns in scarred myocardium.
Offers non-invasive ventricular activation mapping in scar; extends sparse Bayesian learning to clinical electrocardiographic imaging.
Electrocardiographic imaging has been shown to provide useful information for pre-procedure planning of catheter-ablation procedures. The methodology involves reconstruction of unipolar electrograms (EGMs) and isochronal maps on the epicardial surface from noninvasively acquired body-surface potentials. We have developed an algorithm for evaluating global myocardial activation times. First, the cross-correlation method determines the delay in local activation times among pairs of neighboring nodes. Next, a sparse linear system is constructed from known activation delays of neighboring nodes. To solve this system, we use a sparse Bayesian learning method to calculate the global myocardial activation times. The aim of this study was to assess the proposed method in both structurally normal and scarred ventricular myocardium. Isochronal maps of calculated activation times were compared with local activation times (LATs) derived from directly-measured epicardial EGMs obtained by electroanatomic contact mapping, for pacing delivered by an implantable cardioverter defibrillator (ICD) at the endocardial right-ventricular (RV) apex, and for catheter pacing at RV epicardial site. We found that even in the presence of infarct scar, isochronal maps calculated by the proposed method correlated closely with known LATs exported from an electroanatomic mapping system.
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Zhou et al. (2018) conducted a case report in Recurrent scar-related ventricular tachycardia (n=1). Algorithm for imaging isochrones of ventricular activation (Sparse Bayesian learning) vs. Electroanatomic contact mapping (Carto system) was evaluated on Correlation of estimated isochronal maps with measured local activation times. An algorithm for imaging isochrones of ventricular activation using sparse Bayesian learning correlated closely with known local activation times obtained by contact mapping in a patient with scarred myocardium.