An Integrated Electrophysiological and Structural Investigation of Cardiac Arrythmias Mechanisms in an Ex-Vivo Rabbit Model
Current methods for diagnosing cardiac arrhythmias have significant limitations; invasive procedures carry risks, while non-invasive techniques like the 12-lead ECG lack sufficient spatial resolution for detailed mechanistic insight. This research aims to provide a mechanistic characterization of induced arrhythmias by integrating advanced electrophysiological mapping with structural tissue analysis in an ex-vivo rabbit heart model. A multimodal platform combining panoramic optical mapping and contact electrical mapping was used to simultaneously record cardiac activity during various induced rhythms. Data was systematically compared to identify areas of concordance and discordance. Additionally, histological analysis using H&E staining was performed to correlate functional findings with the underlying structural substrate. Advanced signal processing, including Independent Component Analysis (ICA), was applied to mitigate artifacts such as ventricular far-field contamination. The results demonstrated a high degree of concordance between optical and electrical mapping during organized rhythms. However, this agreement breaks down significantly in complex, disorganized states such as Atrial Fibrillation (AF). During AF, electrical mapping recorded dominant frequencies more than double those from optical mapping. Optical signals were found to be susceptible to far-field artifacts. The ICA was successful in removing this ventricular far-field, which improved concordance with electrical maps. Histological analysis revealed significant structural remodeling, including increased nucleus density and myofiber disarray, in hearts subjected to arrhythmias compared to controls, with the most severe changes observed following Ventricular Fibrillation (VF). The study concludes that neither optical nor electrical mapping alone provides a complete picture of cardiac electrophysiology, especially during complex arrhythmias. The successful use of ICA highlights the importance of advanced signal processing for artifact removal in optical signals. Finally, the correlation between the severity of arrhythmia and the degree of structural remodeling provides a clear morphological basis for the arrhythmogenic substrate, bridging the gap between the heart’s electrical function and its physical structure.