Electro-anatomical maps (EAM’s) are used to guide ablation towards meaningful regions (e.g. the pulmonary veins). However, anatomical reconstruction in EAM systems is known to be poorly accurate and, as such, the clinician might be provided with a misleading feedback. To solve this issue, we have developed a framework to correct the errors in the EAM reconstruction by using pre-procedurally acquired anatomical scans. With the proposed system, the clinician will have at the same time precise measurements of electrical activity and of the underlying anatomy.
Besides the errors in the navigation system, a second important factor affecting the success rates of atrial ablation is the lack of standardization. Indeed, indeed, it is still relatively unknown which are the electrical sources sustaining the fibrillation or how ablation can interrupt them. Hereto, ablation schemes including the elimination of rotors were very recently introduced and claimed superior to standard ablation schemes based on the electrical isolation of the pulmonary veins (PV’s) alone. In rotor-based ablation, multielectrode sensing catheters are used to reconstruct rotor position. Yet, the initial findings could not be replicated in multicenter studies. In AFIBROTIC, we used computational modelling to test some of the underlying assumptions of rotor-driven ablation and benchmark basket-guided ablation: if the rotor core can be reliably localized by a grid of electrodes; how the number/resolution of electrodes and the distance from the atrial wall can affect such localization; if simulated ablation is able per se to terminate AF. Concerning the suitability of the multielectrode catheter, we evaluated the effect of two factors: i) the relative distance between electrodes in the sensing catheter and ii) the distance between the catheter and the atrial wall. As such, we were able to set an upper bound on both settings above which rotor detection becomes unreliable. Additionally, the developed computational model was used as an in-silico testing environment for ablation. Hereto, ablation was implemented by setting zero conductivity to the ablated tissue in the numerical model. Our very preliminary findings seem to question the effectiveness of rotor-driven ablation but need further verification.
A further objective consisted in the study of intra-atrial blood flow in atrial fibrillation. AF, due to atrial enlargement and reduced mechanical function, might induce blood stasis and, therefore, favor the formation of blood clots. Yet, no hemodynamic parameter is taken into account by modern stroke risk stratification indices. This can explain in part the low predictive power of such indices. The objective of this activity was therefore use computational fluid dynamics (CFD) to understand and quantify anatomical and functional modulators of intra-atrial blood flow in atrial fibrillation on a subject specific basis. Hereto, an image processing personalization pipeline was developed to extract patient-specific atrial anatomy and motion over time from dynamic CT data. The study showed that atrial fibrillation is responsible for an overall reduction in the blood flow velocity inside the atrium and especially in the left atrial appendage. Moreover, blood particles were shown to remain longer in the atrial appendage during atrial fibrillation episodes. These result point towards a key role of mechanical remodeling in AF in explaining blood stasis and, potentially, stroke risk. In the longer run, we aim to provide a pipeline for the optimal patient-specific assessment of stroke risk in AF.
