Journal
APPLIED SCIENCES-BASEL
Volume 12, Issue 13, Pages -Publisher
MDPI
DOI: 10.3390/app12136438
Keywords
electrophysiology; parameter optimisation; smoothed particle hydrodynamics; meshless model; cardiac resynchronization therapy; CRT-EPiggy19 challenge
Categories
Funding
- Spanish Ministry of Science and Innovation [TIN2011-28067, REDINSCOR RD06/003/008, PID2019-105674RB-I00]
- Spanish Industrial and Technological Development Center [cvREMOD-CEN-20091044]
- Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme [MDM-2015-0502]
- Government of Aragon (Spain) [LMP94_21]
- Directorate General of Science Policy of the Generalitat Valenciana (Spain) [PROMETEU 2016/088]
- RSF [19-14-00134]
- European Regional Development Fund (ERDF) [DPI2016-75799R]
- Seventh Framework Programme (FP7/2007-2013) for research, technological and demonstration under grant agreement VP2HF [611823]
Ask authors/readers for more resources
Computational models of cardiac electrophysiology can reduce non-response to CRT by optimizing electrode placement, meshless models are valid alternatives, and data assimilation strategy is crucial.
Computational models of cardiac electrophysiology are promising tools for reducing the rates of non-response patients suitable for cardiac resynchronization therapy (CRT) by optimizing electrode placement. The majority of computational models in the literature are mesh-based, primarily using the finite element method (FEM). The generation of patient-specific cardiac meshes has traditionally been a tedious task requiring manual intervention and hindering the modeling of a large number of cases. Meshless models can be a valid alternative due to their mesh quality independence. The organization of challenges such as the CRT-EPiggy19, providing unique experimental data as open access, enables benchmarking analysis of different cardiac computational modeling solutions with quantitative metrics. We present a benchmark analysis of a meshless-based method with finite-element methods for the prediction of cardiac electrical patterns in CRT, based on a subset of the CRT-EPiggy19 dataset. A data assimilation strategy was designed to personalize the most relevant parameters of the electrophysiological simulations and identify the optimal CRT lead configuration. The simulation results obtained with the meshless model were equivalent to FEM, with the most relevant aspect for accurate CRT predictions being the parameter personalization strategy (e.g., regional conduction velocity distribution, including the Purkinje system and CRT lead distribution).
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available