Efficient algorithms for solving static hamilton-jacobi equations
Efficient algorithms for solving static hamilton-jacobi equations
FIMH '09 Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
A fast-marching approach to cardiac electrophysiology simulation for XMR interventional imaging
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Localization of sparse transmural excitation stimuli from surface mapping
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
STACOM'12 Proceedings of the third international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
Hi-index | 0.00 |
We present a pipeline for the personalization of model-based Purkinje fast conduction system using fast electrophysiological models and optical mapping data acquired from ex-vivo porcine hearts. The regional density of the Purkinje terminals as well as the latest endocardial activation time were the parameters personalized in an iterative procedure maximizing the similarity between the outcome of the electrophysiological simulations and measurements obtained from optical mapping data. We used a fast wave-front Eikonal-based electrophysiological model that generated the depolarization time maps that were subsequently compared with measurements at each iteration of the optimization stage. The pacing site given by the experimental data and the optimized Purkinje system were introduced into the electrophysiological model. We obtained a regional distribution of Purkinje end-terminals in agreement with findings in the literature. Nevertheless, remaining differences between simulations and measurements after personalization suggest that epicardial data obtained from optical mapping data might not be sufficient to optimize the Purkinje system, which is basically located at the endocardium. On the other hand, the developed pipeline could also be used with endocardial data on electrical activation provided by non-contact or contact mapping system.