Information theoretic-based approaches, such as entropy measures, provide new insights into the complex system dynamics of atrial fibrillation and offer potential for improved AF mapping.
Can information theoretic-based approaches improve AF mapping and detection of ablation targets compared to traditional methods?
Information theory offers a promising, less empirically-reliant approach to AF mapping that may improve the identification of ablation targets.
Atrial Fibrillation (AF) is the most common cardiac rhythm disorder seen in hospitals and in general practice, accounting for up to a third of arrhythmia related hospitalizations. Unfortunately, AF treatment is in practice complicated by the lack of understanding of the fundamental mechanisms underlying the arrhythmia, which makes detection of effective ablation targets particularly difficult. Various approaches to AF mapping have been explored in the hopes of better pinpointing these effective targets, such as Dominant Frequency (DF) analysis, complex fractionated electrograms (CFAE) and unipolar reconstruction (FIRM), but many of these methods have produced conflicting results or require further investigation. Exploration of AF using information theoretic-based approaches may have the potential to provide new insights into the complex system dynamics of AF, whilst also providing the benefit of being less reliant on empirically derived definitions in comparison to alternate mapping approaches. This work provides an overview of information theory and reviews its applications in AF analysis, with particular focus on AF mapping. The works discussed in this review demonstrate how understanding AF from a signal property perspective can provide new insights into the arrhythmic phenomena, which may have valuable clinical implications for AF mapping and ablation in the future.
Dharmaprani et al. (Wed,) conducted a review in Atrial Fibrillation. Information theory-based approaches (Entropy) was evaluated. Information theoretic-based approaches, such as entropy measures, provide new insights into the complex system dynamics of atrial fibrillation and offer potential for improved AF mapping.