@misc {42849,
	title = {Computational 3D cardiac electromechanical models for functional and pharmacological analysis},
	howpublished = {9th International Workshop on Cardiac Mechano-Electric Coupling and Arrhythmias},
	year = {2022},
	author = {Ilsbeth Gerarda Ma {van Herck} and Llopis-Lorente, Jordi and Finsberg, Henrik and Daversin-Catty, C{\'e}cile and Mora, Maria and Saiz, Javier and Trenor, Beatriz and Arevalo, Hermenegild and Wall, Samuel}
}
@misc {42561,
	title = {Functional Analysis of Healthy and Heart Failure Tissue Populations using 3D Cardiac Electromechanical Models},
	howpublished = {15th World Congress on Computational Mechanics (virtual)},
	year = {2022},
	abstract = {Computer modelling and simulation of the beating heart must reflect on electrical activation of cells and tissue, mechanical properties of tissue, and their interaction. Electrophysiological properties of the heart have been simulated abundantly and applied to increase mechanistic understanding of disease and improve treatment development. Recent maturity in cardiac mechanical modelling increased quantitative predictive power. However, tight coupling of cardiac mechanics with the underlying electrophysiological properties of the tissue makes modelling clinical mechanical phenomena such as cardiac disease and drug effects difficult. A combination of uncertainty quantification through populations of models and fully coupled electromechanics models provide greater predictive power on cardiac mechanisms and aid treatment development for cardiac diseases.\&nbsp;A fully coupled electromechanics model of ventricular tissue is developed by coupling the O{\textquoteright}Hara-Rudy[1] electrophysiology model and the Land[2] mechanics model. A population of models was created by varying 16 electrophysiological and 11 mechanical parameters at the cell level. The population was calibrated from 1000 to 187 models based on biomarkers derived from the action potential shape, calcium transient and active tension. This calibrated population was altered in 11 parameters of the cell model to represent heart failure (based on [3]). A geometry of 20x7x3 mm is simulated with 1.0 or 0.5 mm spatial resolution for mechanics or electrophysiology respectively, with free movement in the fibre direction on one side. Results are extracted at the centre of the tissue, as well as tissue shortening on the free-contracting side.\&nbsp;Relative to the healthy population, heart failure manifests in both electrophysiological and mechanics biomarkers. The action potential takes ~20\% longer to recover from activation and peak calcium concentration in the cell is reduced by 50.9\%. In a similar trend, mechanical biomarkers show 42.2\% reduction in peak active force, slower contraction and more variation in recovery times across the heart failure tissue population. The peak tissue shortening in the fibre direction as a result of free contraction is reduced from 0.68{\textpm}0.07mm to 0.45{\textpm}0.07mm (-33.2\%) and its peak is delayed by 112ms (38.6\%) in heart failure.\&nbsp;These simulations indicate strong effects on electrophysiological and mechanical heart function by population variation and disease such as heart failure. Therefore, strongly coupled 3D models are necessary to assess the impact of biological variation, cardiac vulnerability as well as safe and effective treatment development.REFERENCES[1]\&nbsp;\&nbsp;\&nbsp;\&nbsp; O{\textquoteright}Hara, T. et al.; PLoS Comput. Biol. 2011 [doi:10.1371/journal.pcbi.1002061][2]\&nbsp;\&nbsp;\&nbsp;\&nbsp; Land, S. et al.; J. Mol. Cell. Cardiol. 2017 [doi:10.1016/J.YJMCC.2017.03.008][3]\&nbsp;\&nbsp;\&nbsp;\&nbsp; Gomez, J. et al; PLoS ONE 2014 [doi:10.1371/journal.pone.0106602]},
	keywords = {Cardiac biomechanics, Cardiac disease, Uncertainty quantification},
	author = {Ilsbeth Gerarda Ma {van Herck} and Finsberg, Henrik and Daversin-Catty, C{\'e}cile and Mora, Maria and Trenor, Beatriz and Arevalo, Hermenegild and Wall, Samuel}
}
@misc {42850,
	title = {Omecamtiv Mecarbil Improves Contraction Behaviour in a 3D Electromechanical Tissue Model of Heart Failure},
	howpublished = {49th Computing in Cardiology Conference},
	year = {2022},
	author = {Ilsbeth Gerarda Ma {van Herck} and Mora, Maria and Finsberg, Henrik and Daversin-Catty, C{\'e}cile and Trenor, Beatriz and Arevalo, Hermenegild and Wall, Samuel}
}
@inproceedings {42559,
	title = {Population of Computational Cell and Tissue Cardiac Electromechanical Models for functional analysis},
	journal = {World Congress of Biomechanics},
	year = {2022},
	edition = {9th},
	abstract = {IntroductionCardiac computational models can fill important gaps in understanding the cardiomyocyte or cardiac tissue properties. Recent maturity in cardiac mechanical modelling enables quantitative predictive power across a range of applications. One challenge however is the tight coupling of cardiac mechanics with the underlying electrophysiological properties of the tissue, which makes modelling clinical mechanical phenomena such as drug effects difficult. More robust predictions can be achieved by modelling populations of models, which incorporate stochastic parameter variability to represent biological variation. For cardiac computational models to live up to their potential in developing safe and efficient treatments for increasingly prevalent cardiac disease, such populations of fully coupled electromechanics models will provide greater predictive power on mechanics and physiology of the heart.\&nbsp;MethodsA fully coupled electromechanics model of ventricular tissue is developed by coupling the O{\textquoteright}Hara-Rudy[1] electrophysiology model and the Land[2] mechanics model. A population of models was created by varying 16 electrophysiological and 11 mechanical parameters at the cell level. The population was calibrated from 1000 to 187 models based on biomarkers derived from the action potential shape, calcium transient and active tension. The electromechanics solver is implemented by combining existing solvers for electrophysiology[3] and mechanics[4], which are both based on the open-source framework FEniCS[5]. A geometry of 20x7x3 mm is simulated with 1.0 or 0.5 mm spatial resolution for mechanics or electrophysiology respectively, with free movement in the fibre direction on one side.\&nbsp;ResultsTraces from all population models were extracted at the center of the tissue in all directions (green star in top left panel) for further analysis (see figure). Electrophysiological biomarkers, such as action potential duration and systolic calcium concentration remain within calibrated and cell population model range. The maximum active tension in tissue is reduced by 65\% compared to cell simulations. This reduction can be attributed to the free contraction in tissue versus fixed stretch in calibration and cell simulations. The magnitude and especially the recovery duration of active stretch varies widely across the population (see table for average{\textpm}SD). This range of timing and force of contraction reinforce the need to assess cardiac function and drug effects in populations of electromechanical models.\&nbsp;DiscussionWe present a pipeline for creating populations of strongly coupled 3D excitation-contraction models for ventricular tissue. The tissue model includes bidirectional coupling and biological variation, facilitating further investigation into the multifactorial effect of variation and drugs on the in silico human heart. This enables simulation of both mechanical and physiological function of the heart to aid development of safe and efficient treatment based on population statistics.\&nbsp;ReferencesO{\textquoteright}Hara, T. et al.; PLoS Comput Biol 2011 [doi:10.1371/journal.pcbi.1002061]Land, S. et al.; J. Mol. Cell. Cardiol. 2017 [doi:10.1016/J.YJMCC.2017.03.008]Logg, A. et al.; Springer 2012 [doi:10.1007/978-3-642-23099-8]Rognes, M. E. et al.; Journal of Open Source Software, 2017 [doi:10.21105/joss.00224]Finsberg, H. N. T.; Journal of Open Source Software, 2019 [doi:10.21105/joss.01539]},
	author = {van Herck, Ilse and Finsberg, Henrik and Daversin-Catty, C{\'e}cile and Mora, Maite and Trenor, Beatriz and Arevalo, Hermenegild and Wall, Samuel}
}
