P. Tejero Cervera. Source Estimation in Cardiac Fibrotic Substrate from Intracardiac Signals. Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT). Masterarbeit. 2021
Atrial fibrillation (AF) is the most prevalent arrhythmia in the world, affecting 1-1.5% of the general population. It is commonly associated with fibrosis of cardiac tissue that involves the formation and deposition of extracellular matrix (ECM), playing an important role in the onset and maintenance of AF. Many treatments currently exist to try to stop this disease. Among them, electroanatomical mapping consists in the measurement using an array of electrodes in an intravenous catheter near or on the surface of the heart, obtaining the amplitude of the electrogram (EGM). Depending on its value, it is considered the cardiac area evaluated as fibrotic or healthy tissue and, it is ablated or not respectively using the catheter ablation procedure. However, this technique is not very reliable and its success rate is very suboptimal. Thus, the main objective of this work is to explore an inverse problem reconstruction by obtaining the signals from the EGMs of simulated reentrant activity in fibrotic patches. By doing so, it will be possible to obtain a map of the extracellular potentials (EPs) of the cardiac tissue to localize strategic ablation points that promote AF. To achieve this, it is performed the inverse problem through the implementation in MATLAB software of the second-order Tikhonov regularization, L-curve method, Generalized Singular Value Decomposition (GSVD), depth normalization and Boundary Element Method (BEM). Additionally, it has been calculated the activation times (ATs) and repolarization times (RTs), and localised the singularity points using phase singularity (PS) analysis. The simulation setup is a patch with dimensions 50x50x1 mm and a spatial resolution of 0.2 mm, where the mesh of electrodes has been: 8x8, 12x12 and 16x16 at a distance from the tissue of 0.5 mm or 1 mm. Four cases have been performed: healthy tissue by applying a planar wave front and with reentry, and fibrotic tissue by applying a planar wave front and with reentry. In addition, two more cases have been done when the electrode-source distance (ESD) was considerably greater (2 mm and 10 mm). The results obtained for each case have been the reconstruction of the EPs, the AT and RT maps of the electrodes and the reconstructed tissue, the RMSE graphs of the AT and RT computed between electrodes and the closest point to each one, and the phase and singularity points map. Although the reconstructions of EPs were visually similar to the ground truth, the AT and RT maps still need to be improved as it is difficult to identify the propagation of the characteristic voltage pattern. Regarding the calculated RMSE, values around 59 ms and 64 ms for the detection of AT and RT respectively have been obtained for the case of fibrotic tissue with reentry, which are quite acceptable. Also, there is less error with the 16x16 electrode grid that covers completely the simulated tissue. As the ESD is increased (2 mm or 10 mm), greater errors and dispersion of values are obtained due to the lower precision of the electrodes. However, through PS analysis, the phase maps show various singularity points, making an approximate detection on singularity maps. For this reason, although the implemented algorithm needs to be improved in order to get better results, it is possible to localise approximately with this method the reentrant points in simulated fibrotic tissue.