EXPERIMENTAL ANALYSIS AND COMPUTATIONAL MODELING OF MULTI FIELD CARDIAC SIGNALS

The study of cardiac electrophysiology, a field at the intersection of biology, physics, and engineering, has long captivated researchers due to its inherent complexity and profound clinical implications. The heart’s rhythmic contractions, governed by intricate electro mechanical processes, are essential for life, yet they remain vulnerable to disruptions that can lead to devastating outcomes. Among these, cardiac arrhythmias pose a significant challenge, ranking as one of the leading causes of sudden cardiac death worldwide. Under standing the mechanisms underlying arrhythmias is not only a matter of scientific curiosity but also a critical step toward developing effective diagnostic and therapeutic solutions. This thesis recognizes that arrhythmias cannot be fully understood or addressed through a single perspective. Instead, their study requires a multi-field approach that integrates experimental observations, computational simulations, and clinical data. By analyzing cardiac signals across spatial and temporal scales, this work seeks to uncover the processes that drive the onset and progress of electrical instabilities. From the cellular dynamics to the macroscopic behavior of the heart as a whole, this investigation strives to connect fundamental mechanisms with real-world applications. The motivation for this research arises from the complexity of cardiac arrhythmias and the need to explore their mechanisms through multiple methodologies. Advances in experimental techniques, such as high-resolution optical and electro-anatomical mapping, provide opportunities to expand existing methodologies and offer additional insights into arrhythmogenic behavior, refining strategies for patient-specific interventions. This interdisciplinary research begins with an exploration of cardiac electrophysiology and arrhythmogenesis, emphasizing the roles of voltage-calcium coupling and alternans. Experimental studies using high-resolution optical mapping capture thermo-electrical in teractions and characterize alternans, a well known pro-arrhythmic phenomenon. Compu tational models simulate the interplay between electrical activity, thermal effects, and mag netic fields, introducing perspectives on cardiac magnetic fields as a potential biomarker for arrhythmias. Clinical analyses of electro-anatomical mapping data enable the development of patient-specific models that connect foundational research to practical applications. By integrating experimental investigations, theoretical modeling, and clinical data in terpretation, this thesis exemplifies a multi-field approach to understanding arrhythmoge nesis. The findings advance fundamental knowledge of cardiac dynamics and establish afoundation for translational applications, contributing to precision medicine and improving predictive models for diagnosing and treating cardiac disorders. This thesis seeks to advance the understanding of cardiac arrhythmogenesis by employing spatio-temporal analysis of different cardiac signals. Specifically, this work seeks to: 1. Investigate the thermo-electric spatiotemporal dynamics of voltage and calcium sig nals (Chapter 6): using high-resolution simultaneous optical mapping techniques, this study aims to characterize the onset and progression of alternans for both types of signals. 2. Explore the relationship between electrical activity and cardiac magnetic fields under hyperthermia (40◦C) as well as hypothermia (33÷29◦C) (Chapter 7): develop and validate computational models to study the cardiac magnetic field, focusing on its correlation with electrical signals and its potential as a complementary indicator of arrhythmogenic events. 3. Analyze clinical electro-anatomical signals from CARTO 3 System, developing patient-specific models (Chapter 8): examine a cohort of 5 post-ischemic patient electrograms to assess the manifestation of ventricular tachycardia events, extracting the geometry and properties of the cardiac substrate to identify clinically relevant patterns and potential biomarkers. By integrating these analyses, the study aims to enhance the understanding of arrhythmogenic mechanisms of the isthmus and improve precision for target ablation.