Towards mechanisms-driven strategy for persistent atrial fibrillation ablation: Leveraging digital twins

Area of Science:

• Cardiology
• Biomedical Engineering
• Computational Medicine

Background:

• Atrial fibrillation (AF) is a common arrhythmia, increasing with age and leading to stroke and heart failure.
• Persistent AF (PsAF) is challenging to treat with catheter ablation due to atrial fibrotic remodeling.
• Current mapping techniques for PsAF substrate modification lack consistent clinical effectiveness.

Purpose of the Study:

• To review PsAF mechanisms and current ablation limitations.
• To highlight the potential of personalized digital twins (DTs) for improving PsAF treatment.
• To discuss DTs for mechanism-driven, personalized ablation planning.

Main Methods:

• Review of literature on PsAF mechanisms, ablation strategies, and digital twin technology.
• Analysis of limitations in current electrogram-based mapping and ablation approaches.
• Exploration of personalized digital twin capabilities for cardiac electrical activity reconstruction.

Main Results:

• PsAF maintenance involves complex atrial remodeling, challenging standard ablation.
• Existing mapping approaches for identifying arrhythmogenic substrates show controversial clinical effectiveness.
• Personalized digital twins enable non-invasive, patient-specific cardiac modeling.

Conclusions:

• Digital twins can predict arrhythmia inducibility and identify substrates pre-procedurally.
• DTs facilitate personalized, mechanism-driven ablation planning for PsAF.
• This technology holds potential to enhance patient care and outcomes in PsAF management.