Meshless Simulation of Multi-site Radio Frequency Catheter Ablation through the Fragile Points Method.

Autor: Mountris KA, Schilling R, Casals A, Wurdemann HA
Jazyk: angličtina
Zdroj: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2023 Jul; Vol. 2023, pp. 1-4.
DOI: 10.1109/EMBC40787.2023.10340348
Abstrakt: Computational models for radio frequency catheter ablation (RFCA) of cardiac arrhythmia have been developed and tested in conditions where a single ablation site is considered. However, in reality arrhythmic events are generated at multiple sites which are ablated during treatment. Under such conditions, heat accumulation from several ablations is expected and models should take this effect into account. Moreover, such models are solved using the Finite Element Method which requires a good quality mesh to ensure numerical accuracy. Therefore, clinical application is limited since heat accumulation effects are neglected and numerical accuracy depends on mesh quality. In this work, we propose a novel meshless computational model where tissue heat accumulation from previously ablated sites is taken into account. In this way, we aim to overcome the mesh quality restriction of the Finite Element Method and enable realistic multi-site ablation simulation. We consider a two ablation sites protocol where tissue temperature at the end of the first ablation is used as initial condition for the second ablation. The effect of the time interval between the ablation of the two sites is evaluated. The proposed method demonstrates that previous models that do not account for heat accumulation between ablations may underestimate the tissue heat distribution.Clinical relevance- The proposed computational model may be used to build and update a heat map for ablation guidance taking into account the contribution from previously ablated sites. Being a meshless model, it does not require significant input from the user during preprocessing. Therefore, it is suitable for application in a clinical setting.
Databáze: MEDLINE