Personalization of digital twin models using characteristic electrogram signatures to identify atrial fibrillation initiation sites as potential ablation target

• Applicants: Privatdozent Dr.-Ing. Axel Loewe; Privatdozent Dr. Armin Luik; Professor Dr. Reza Wakili
• Subject Area: Cardiology, Angiology ; Medical Physics, Biomedical Technology
• Term: since 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 394433254

Atrial fibrillation (AF) is the most prevalent heart rhythm disorder and poses challenges for patients and healthcare systems worldwide. Despite advancements in understanding of basic mechanisms underlying AF and empirical trials evaluating different treatment strategies, a significant number of patients experience AF recurrence following treatment according to current guidelines. The lack of success in achieving long-term freedom from arrhythmia can be attributed to the insufficient characterization of the individual patient's functional and structural AF substrate, necessitating more personalized diagnostic and treatment approaches. This project aims to develop, combine, and validate advanced signal processing algorithms and digital twin modeling techniques to optimize AF treatment beyond pulmonary vein isolation (PVI). Vulnerable sites that contribute to AF initiation can be identified by comprehensively characterizing the substrate properties of the atrial tissue and conducting virtual stress tests with personalized digital twin models. Targeting these vulnerable sites aims to prevent future episodes and thus to increase abation success rates. We will utilize a comprehensive clinical signal database and realistic high-resolution simulations to identify characteristic electrogram signatures associated with these vulnerable substrate sites in a well-controlled environment. Successful identification of these sites would eliminate the need for personalized computer simulations in the future, thus further facilitating clinical translation. Focusing on PVI non-responders allows for the assessment of the novel approach in a feasible and focused cohort with pro-arrhythmic substrate beyond the pulmonary veins. Therefore, this project aims to develop an objective, operator- independent, and digitally enhanced approach for AF ablation. The expected outcomes of this research include a validated digital twin- powered algorithm to identify vulnerable substrate sites in individual patients, characteristic electrogram signatures of these sites, and correlation to clinical outcome. This research has the potential to significantly impact the field of AF treatment by providing a more personalized and effective approach to improve patient outcomes.

• DFG Programme: Research Grants