Key result
DGM-TOP algorithm identifies critical ablation targets in 100% of in silico and clinical atrial tachycardias.
Why the study?
Reentry-based atrial tachycardias are maintained by counter-rotating waves around critical boundaries, but specific algorithms to calculate topological charge and automatically identify these boundaries from electroanatomical maps were needed.
Does the DGM-TOP algorithm accurately identify critical boundaries for ablation in atrial tachycardia?
Does the DGM-TOP algorithm accurately identify critical boundaries for ablation in atrial tachycardia?
The DGM-TOP algorithm successfully identifies critical boundaries in atrial tachycardia, demonstrating that interconnecting these boundaries is essential for successful ablation.
Answers are grounded in this paper and cite their sources.
May guide ablation target selection in atrial tachycardia; leaves open clinical utility pending prospective validation.
Introduction In the latest research on topology in cardiac arrhythmia, it was demonstrated through a fundamental mathematical principle called the index theorem that reentry based atrial tachycardias (AT) are maintained by pairs of counter-rotating waves that are either complete or near-complete rotations. Each wave is centered around a different anatomical object that exhibits a non-zero index/topological charge, called a critical boundary. Interconnecting both critical boundaries with an ablation line terminates the tachycardia. Methods This research focuses on the specific algorithms for calculating the index/topological charge of each anatomical boundary, called DGM-TOP. The algorithm used analyzes the electroanatomical map of the patient, extracting the nodes at each boundary. The index is then calculated for each boundary by sequentially summing the differences in local activation time and normalizing by the cycle length. Boundaries with a non-zero index are identified as critical boundaries. Results and discussion Using this method, pairs of critical boundaries were consistently detected in 100% of the 578 in silico and 100% of the 24 clinical ATs. Adhering to the previously described index theorem. Additionally, ablation results in both datasets show that termination of AT is only possible by interconnecting both critical boundaries. This outcome highlights the importance of detecting the critical boundaries before deciding on the correct ablation line, as any ablation line that does not connect both critical boundaries is unable to terminate the AT. Moreover, in the case of incorrect ablation, the BCL-algorithm was proposed to estimate the increase in tachycardia cycle length. However, only moderate correlation (r2=0.62) is observed for simulations, indicating a refinement of this BCL-algorithm is necessary in addition to a larger clinical dataset.
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Abeele et al. (2025) studied Atrial tachycardia (n=602). DGM-TOP algorithm was evaluated on Detection of pairs of critical boundaries. The DGM-TOP algorithm successfully detected pairs of critical boundaries in 100% of 578 in silico and 24 clinical atrial tachycardias, identifying the necessary ablation targets to terminate the arrhythmia.
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