@article {43054,
	title = {A cell-based framework for modeling cardiac mechanics},
	journal = {Biomechanics and Modeling in Mechanobiology},
	volume = {10101010},
	year = {2023},
	month = {01/2023},
	publisher = { Springer},
	keywords = {Cardiac Mechanics, cardiomyocyte contraction, cell geometries, intracellular and extracellular mechanics, microscale modeling},
	issn = {1617-7959},
	doi = {10.1007/s10237-022-01660-8},
	url = {https://link.springer.com/article/10.1007/s10237-022-01660-8},
	author = {Telle, {\r A}shild and James D. {Trotter} and Cai, Xing and Finsberg, Henrik and Kuchta, Miroslav and Sundnes, Joakim and Wall, Samuel}
}
@article {sundnes2023computational,
	title = {Editorial: Computational models of cardiovascular growth and remodeling},
	journal = {Frontiers in Physiology},
	volume = {14},
	year = {2023},
	pages = {56},
	publisher = {Frontiers},
	doi = { https://doi.org/10.3389/fphys.2023.1130420},
	url = {https://www.frontiersin.org/articles/10.3389/fphys.2023.1130420/full},
	author = {Sundnes, Joakim and Lik Chuan {Lee} and Wall, Samuel and Valdez-Jasso, Daniela}
}
@article {43078,
	title = {simcardems: A FEniCS-based cardiac electro-mechanicssolver},
	journal = {Journal of Open Source Software},
	volume = {88442954520810717},
	year = {2023},
	month = {Jan-01-2023},
	pages = {4753},
	publisher = {JOSS},
	doi = {10.21105/joss.04753},
	url = {https://joss.theoj.org/papers/10.21105/joss.04753},
	author = {Finsberg, Henrik and Ilsbeth Gerarda Ma {van Herck} and Daversin-Catty, C{\'e}cile and Arevalo, Hermenegild and Wall, Samuel}
}
@misc {42583,
	title = {A cell-based framework for modeling cardiac mechanics},
	howpublished = {International Symposium in honor of Professor Gerhard A. Holzapfel{\textquoteright}s 60th birthday, Graz, Austria},
	year = {2022},
	abstract = {The mechanical function of cardiac tissue results from the complex interplay ofcontracting cardiomyocytes and the passive extracellular matrix. Most computationalmodels of cardiac mechanics are based on a continuum approach, where the tissueis viewed as a continuous and homogeneous mix of cells and extracellular material.This approach has been successfully applied in numerous studies,and will undoubtedly remain a cornerstone of computational biomechanics.However, the extensive homogenization limits the models{\textquoteright} ability to give detailedinsight into the mechanical forces experienced by individual cardiac cells, andto delineate the mechanical contributions of myocytes and the extracellular matrix.More detailed models exist, in the form of continuum mechanics modelsof individual myocytes, but these are typically limited to a single myocyte anddo not consider the extracellular matrix.Computational models of cardiac electrophysiology are typically based on thesame continuous and homogenized concept as the mechanics model, with thebidomain model being the reference model for several decades. More recently,models have been developed that explicitly represent the cells, the membrane,and the domain between the cells. The approach is commonly referred to as the EMI(Extracellular-Membrane-Intracellular) model, and has been applied instudies of cardiac and neuronal electrophysiology. Natural extensions of theEMI framework include detailed models of intra- and extracellular ion concentrationsand electro-diffusion, as well as coupling to models for cell contraction and mechanics.We present a mechanical analogue of the EMI model, i.e., a continuum basedcardiac mechanics model that explicitly represents a three-dimensional networkof cells embedded in an extracellular matrix. Both the intra- and extracellular domainsare modeled as hyperelastic, with constitutive models based based onthe Holzapfel-Ogden model for passive myocardium. The two domainshave different passive mechanical properties, and the intracellular domain isactively contracting while the extracellular domain is completely passive.The active contraction is incorporated through a so-called active strain model,and in this first version of the model it is assumed to be synchronous and homogeneousacross the entire intracellular domain. The model was parameterized usingpublicly available experimental data for stretching and shear experiments,and was used in preliminary explorations of mechanical interactions betweenthe intra- and extracellular domains. In particular, we studied how myocytestress and strain are affected by the mechanical properties of the two domains,during passive stretching and active contraction. The results show considerablespatial variations in both stress and strain, and indicate that the detailedgeometrical representation of the cells may give improved insight into certainmechanisms of biomechanics and mechano-biology. Further development ofthe model should include a more detailed exploration of material parameters,cell geometry, and the mechanical coupling between the cells and the surroundingmatrix, as well as extending the framework to consider inhomogeneous contractionand potentially coupling of contraction to cell electrophysiology and calcium diffusion.},
	author = {Sundnes, Joakim and Telle, {\r A}shild and Wall, Samuel}
}
@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}
}
@article {odeigah2022computational,
	title = {Computational models of ventricular mechanics and adaptation in response to right-ventricular pressure overload},
	journal = {Frontiers in Physiology},
	year = {2022},
	pages = {1774},
	publisher = {Frontiers},
	abstract = {Pulmonary arterial hypertension (PAH) is associated with substantial remodeling of the right ventricle (RV), which may at first be compensatory but at a later stage becomes detrimental to RV function and patient survival. Unlike the left ventricle (LV), the RV remains understudied, and with its thin-walled crescent shape, it is often modeled simply as an appendage of the LV. Furthermore, PAH diagnosis is challenging because it often leaves the LV and systemic circulation largely unaffected. Several treatment strategies such as atrial septostomy, right ventricular assist devices (RVADs) or RV resynchronization therapy have been shown to improve RV function and the quality of life in patients with PAH. However, evidence of their long-term efficacy is limited and lung transplantation is still the most effective and curative treatment option. As such, the clinical need for improved diagnosis and treatment of PAH drives a strong need for increased understanding of drivers and mechanisms of RV growth and remodeling (G\&amp;R), and more generally for targeted research into RV mechanics pathology. Computational models stand out as a valuable supplement to experimental research, offering detailed analysis of the drivers and consequences of G\&amp;R, as well as a virtual test bench for exploring and refining hypotheses of growth mechanisms. In this review we summarize the current efforts towards understanding RV G\&amp;R processes using computational approaches such as reduced-order models, three dimensional (3D) finite element (FE) models, and G\&amp;R models. In addition to an overview of the relevant literature of RV computational models, we discuss how the models have contributed to increased scientific understanding and to potential clinical treatment of PAH patients.},
	author = {Oscar O {Odeigah} and Valdez-Jasso, Daniela and Wall, Samuel and Sundnes, Joakim}
}
@misc {43010,
	title = {Estimating active tension in cardiac micromuscles},
	howpublished = {World Congress on Biomechanics (WCB), Taipei, Taiwan (Virtual)},
	year = {2022},
	type = {Contributed},
	abstract = {Introduction:Microphysiological systems (MPSs) provide a well-defined environment for the formation and monitoring of cardiac micromuscles, and provide a powerful platform for both disease and drug development studies. Such devices can replicate key features of the heart{\textquoteright}s electromechanical behavior, giving a detailed in vitro testbed for investigating cardiac function, both biomechanics and electrophysiology. In an MPS, quantities like displacement and velocity can be identified based on optical measurements of the tissues during contraction [1]. While useful for evaluating relative changes in muscle twitch, it remains difficult to quantify and characterize the underlying active tension that causesdisplacement during contraction.Methods:In this work, we applied an inverse modeling approach to estimate the active tension generated during contraction, as well as the fiber directions in a cardiac micromuscle. Cardiomyocytes differentiated from human induced pluripotent stem cells (hiPSC-CMs) were loaded into MPSs and self-assembled into a uniaxial beating microtissue. High-speed microscopic videos were recorded over several contractions and changes in displacement were calculated. Finally, we used a computational mechanical model in combination with an optimization algorithm, similar to the one used in [2], to find the active tension and fiber directions likely to cause the tissue displacement.Results:Using the displacement recorded for a single chip (Fig 1A), the active strain (Fig 1C), varying over time and space, and the fiber direction (Fig 1D), varying over space, can be estimated. The model, depending on these two variables, was able to closely reproduce (Fig 1B) the displacement given as input. The corresponding mean active tension for this specific experiment at peak contraction value is given by 0.059 {\textpm} 0.043 (active strain) and the corresponding fiber direction angle 3.3{\textdegree} {\textpm} 25.8{\textdegree}.Discussion:Through our framework we can identify regions of active contraction, and fiber direction alignment, both known to be important metrics from a physiological perspective. We can also quantify the active tension generated. This approach can be used to quantify differences and changes in a range of experiments where mechanical properties are critical metrics, including but not limited to screening of drugs that alter contractility, and tissue structural development in different maturation protocols.References:[1] Huebsch, N et al. Metabolically-Driven Maturation of hiPSC-Cell Derived Cardiac Chip. Biorxiv (preprint). 2020. https://doi.org/10.1101/485169.[2] Finsberg, H. et al: Estimating cardiac contraction through high resolution data assimilation of a personalized mechanical model. Journal of Computational Science. 2018;24:85{\textendash}90. https://doi.org/10.1016/j.jocs.2017.07.013},
	doi = {  10.5281/zenodo.6844384},
	url = {https://zenodo.org/record/6844384$\#$.Y6wym37MJFQ},
	author = {Telle, {\r A}shild and Charrez, B{\'e}r{\'e}nice and Charwat, Verena and Finsberg, Henrik and Kevin E. {Healy} 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}
}
@inbook {42517,
	title = {Identifying Ionic Channel Block in a Virtual Cardiomyocyte Population Using Machine Learning Classifiers},
	booktitle = {Computational Physiology - Simula Summer School 2021 - Student Reports},
	volume = {12},
	year = {2022},
	month = {05/2022},
	pages = {91 - 109},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	keywords = {action potential, AI, cardiomyocyte, classification},
	isbn = {978-3-031-05163-0},
	issn = {2512-1677},
	doi = {10.1007/978-3-031-05164-710.1007/978-3-031-05164-7_8},
	url = {https://link.springer.com/chapter/10.1007/978-3-031-05164-7_8},
	author = {Singstad, Bj{\o}rn-Jostein and Bendik Steinsv{\r a}g {Dalen} and Sihra, Sandhya and Forsch, Nickolas and Wall, Samuel},
	editor = {Kimberly J {McCabe}}
}
@article {42717,
	title = {Metabolically driven maturation of human-induced-pluripotent-stem-cell-derived cardiac microtissues on microfluidic chips},
	journal = {Nature Biomedical Engineering},
	volume = {6},
	year = {2022},
	month = {Jan-04-2022},
	pages = {372 - 388},
	publisher = {Nature Publishing Group},
	address = {London, UK},
	doi = {10.1038/s41551-022-00884-4},
	url = {https://www.nature.com/articles/s41551-022-00884-4https://www.nature.com/articles/s41551-022-00884-4.pdfhttps://www.nature.com/articles/s41551-022-00884-4.pdfhttps://www.nature.com/articles/s41551-022-00884-4},
	author = {Huebsch, Nathaniel and Charrez, Berenice and Neiman, Gabriel and Siemons, Brian and Steven C. {Boggess} and Wall, Samuel and Charwat, Verena and Karoline Horgmo {J{\ae}ger} and Cleres, David and Telle, {\r A}shild and Felipe T. {Lee-Montiel} and Nicholas C. {Jeffreys} and Deveshwar, Nikhil and Andrew G {Edwards} and Serrano, Jonathan and Snuderl, Matija and Stahl, Andreas and Tveito, Aslak and Evan W. {Miller} and Kevin E. {Healy}}
}
@misc {42718,
	title = {Modeling cardiac mechanics using a cell-based framework},
	howpublished = {15th World Congress on Computational Mechanics (WCCM-XV), Yokohama, Japan},
	year = {2022},
	publisher = {15th World Congress on Computational Mechanics (WCCM-XV)},
	type = {Contributed},
	abstract = {Cardiac tissue primarily consists of interconnected cardiac cells which contract in a synchronized manner as the heart beats. Most computational models of cardiac tissue, however, homogenize out the individual cells and their surroundings. This approach has been immensely useful for describing cardiac mechanics on an overall level, but gives very limited understanding of the interaction between individual cells and their intermediate surroundings. Several models have been developed for single cells, see e.g. [1, 2]. In this work, we extend the mechanical part of these frameworks to a domain representing multiple cells, allowing us to investigate cell-matrix and cell-cell interactions. We present a mechanical model in which each cell and the extracellular matrix have an explicit geometrical representation, similar to the electrophysiological model presented in [3]. The strain energy functions are defined separately for each of the intracellular and extracellular subdomains, while we assume continuity of displacement and stresses along the membrane. Active tension is only assigned to the intracellular subdomain. For each state, we find an equilibrium solution using the finite element method. We explore passive and active mechanics for a single cell surrounded by an extracellular matrix and for small collections of cells combined into tissue blocks. The explicit geometric representation gives rise to highly varying strain and stress patterns. We show that the extracellular matrix stiffness highly influences the cardiomyocyte stresses during contraction. Through large-scale simulations enabled by high-performance computing, we also demonstrate that our model can be scaled to small collections of cells, resembling small cardiac tissue samples.

[1] Tracqui, T. and Ohayon, J. An integrated formulation of anisotropic force{\textendash}calcium relations driving spatio-temporal contractions of cardiac myocytes. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences (2009).
[2] Ruiz-Baier, R. Gizzi, A., Rossi, S. Cherubini, C. Laadhari, A. Filippi, S. and Quarteroni, A. Mathematical modelling of active contraction in isolated cardiomyocytes. Mathematical Medicine and Biology (2014).
[3] Tveito, A., J{\ae}ger, KH. Kuchta, M. Mardal, K-A. and Rognes, ME. A cell-based framework for numerical modeling of electrical conduction in cardiac tissue. Frontiers in Physics (2017).
\end{thebibliography}
},
	keywords = {cardiomyocyte contraction, cell-based geometries, intracellular and extracellular mechanics, microscale cardiac mechanics},
	url = {https://prezi.com/view/uGIK0kQvrZ6G1CNOkc73/},
	author = {Telle, {\r A}shild and James D. {Trotter} and Cai, Xing and Kuchta, Miroslav and Finsberg, Henrik and Sundnes, Joakim 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}
}
@article {43086,
	title = {Validating the Arrhythmogenic Potential of High-, Intermediate-, and Low-Risk Drugs in a Human-Induced Pluripotent Stem Cell-Derived Cardiac Microphysiological System},
	journal = {ACS Pharmacology \& Translational Science},
	volume = {5},
	year = {2022},
	pages = {652{\textendash}667},
	publisher = {American Chemical Society},
	abstract = {Evaluation of arrhythmogenic drugs is required by regulatory agencies before any new compound can obtain market approval. Despite rigorous review, cardiac disorders remain the second most common cause for safety-related market withdrawal. On the other hand, false-positive preclinical findings prohibit potentially beneficial candidates from moving forward in the development pipeline. Complex\&nbsp;in vitro\&nbsp;models using cardiomyocytes derived from human-induced pluripotent stem cells (hiPSC-CM) have been identified as a useful tool that allows for rapid and cost-efficient screening of proarrhythmic drug risk. Currently available hiPSC-CM models employ simple two-dimensional (2D) culture formats with limited structural and functional relevance to the human heart muscle. Here, we present the use of our 3D cardiac microphysiological system (MPS), composed of a hiPSC-derived heart micromuscle, as a platform for arrhythmia risk assessment. We employed two different hiPSC lines and tested seven drugs with known ion channel effects and known clinical risk: dofetilide and bepridil (high risk); amiodarone and terfenadine (intermediate risk); and nifedipine, mexiletine, and lidocaine (low risk). The cardiac MPS successfully predicted drug cardiotoxicity risks based on changes in action potential duration, beat waveform (i.e., shape), and occurrence of proarrhythmic events of healthy patient hiPSC lines in the absence of risk cofactors. We showcase examples where the cardiac MPS outperformed existing hiPSC-CM 2D models.},
	doi = {https://doi.org/10.1021/acsptsci.2c00088},
	url = {https://pubs.acs.org/doi/abs/10.1021/acsptsci.2c00088},
	author = {Charwat, Verena and Charrez, B{\'e}r{\'e}nice and Brian A. {Siemons} and Finsberg, Henrik and Karoline Horgmo {J{\ae}ger} and Andrew G {Edwards} and Huebsch, Nathaniel and Wall, Samuel and Miller, Evan and Tveito, Aslak and Kevin E. {Healy}}
}
@article {shavik2021computational,
	title = {Computational Modeling Studies of the Roles of Left Ventricular Geometry, Afterload, and Muscle Contractility on Myocardial Strains in Heart Failure with Preserved Ejection Fraction},
	journal = {Journal of Cardiovascular Translational Research},
	volume = {14},
	year = {2021},
	pages = {1131{\textendash}1145},
	publisher = {Springer},
	author = {Sheikh Mohammad {Shavik} and Wall, Samuel and Sundnes, Joakim and Julius M {Guccione} and Sengupta, Partho and Scott D {Solomon} and Burkhoff, Daniel and Lik Chuan {Lee}}
}
@article {27660,
	title = {Computational prediction of drug response in short QT syndrome type 1 based on measurements of compound effect in stem cell-derived cardiomyocytes},
	journal = {PLoS Computational Biology},
	volume = {17},
	year = {2021},
	pages = {e1008089},
	publisher = {Public Library of Science},
	abstract = {Short QT (SQT) syndrome is a genetic cardiac disorder characterized by an abbreviated QT interval of the patient{\textquoteright}s electrocardiogram. The syndrome is associated with increased risk of arrhythmia and sudden cardiac death and can arise from a number of ion channel mutations. Cardiomyocytes derived from induced pluripotent stem cells generated from SQT patients (SQT hiPSC-CMs) provide promising platforms for testing pharmacological treatments directly in human cardiac cells exhibiting mutations specific for the syndrome. How- ever, a difficulty is posed by the relative immaturity of hiPSC-CMs, with the possibility that drug effects observed in SQT hiPSC-CMs could be very different from the corresponding drug effect\&nbsp;in vivo. In this paper, we apply a multistep computational procedure for translating measured drug effects from these cells to human QT response. This process first detects drug effects on individual ion channels based on measurements of SQT hiPSC-CMs and then uses these results to estimate the drug effects on ventricular action potentials and QT intervals of adult SQT patients. We find that the procedure is able to identify IC50\&nbsp;values in line with measured values for the four drugs quinidine, ivabradine, ajmaline and mexiletine. In addition, the predicted effect of quinidine on the adult QT interval is in good agreement with measured effects of quinidine for adult patients. Consequently,\&nbsp;the computational procedure appears to be a useful tool for helping predicting adult drug responses from pure\&nbsp;in vitro\&nbsp;measurements of patient derived cell lines.},
	doi = {https://doi.org/10.1371/journal.pcbi.1008089},
	url = {https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008089\&type=printable},
	author = {Karoline Horgmo {J{\ae}ger} and Wall, Samuel and Tveito, Aslak}
}
@article {27659,
	title = {Identifying drug response by combining measurements of the membrane potential, the cytosolic calcium concentration, and the extracellular potential in microphysiological systems},
	journal = {Frontiers in Pharmacology},
	volume = {11},
	year = {2021},
	pages = {569489},
	publisher = {Frontiers},
	abstract = {Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs) offer a new means to study and understand the human cardiac action potential, and can give key insight into how compounds may interact with important molecular pathways to destabilize the electrical function of the heart. Important features of the action potential can be readily measured using standard experimental techniques, such as the use of voltage sensitive dyes and fluorescent genetic reporters to estimate transmembrane potentials and cytosolic calcium concentrations. Using previously introduced computational procedures, such measurements can be used to estimate the current density of major ion channels present in hiPSC-CMs, and how compounds may alter their behavior. However, due to the limitations of optical recordings, resolving the sodium current remains difficult from these data. Here we show that if these optical measurements are complemented with observations of the extracellular potential using multi electrode arrays (MEAs), we can accurately estimate the current density of the sodium channels. This inversion of the sodium current relies on observation of the conduction velocity which turns out to be straightforwardly computed using measurements of extracellular waves across the electrodes. The combined data including the membrane potential, the cytosolic calcium concentration and the extracellular potential further opens up for the possibility of accurately estimating the effect of novel drugs applied to hiPSC-CMs.},
	doi = {doi: 10.3389/fphar.2020.569489},
	url = {https://www.frontiersin.org/articles/10.3389/fphar.2020.569489/full},
	author = {Karoline Horgmo {J{\ae}ger} and Charwat, Verena and Wall, Samuel and Kevin E. {Healy} and Tveito, Aslak}
}
@inbook {27570,
	title = {Modeling Cardiac Mechanics on a Sub-Cellular Scale},
	booktitle = {Modeling Excitable Tissue: The EMI Framework},
	volume = {7},
	year = {2021},
	month = {11/2020},
	pages = {28-43},
	publisher = { Springer International Publishing},
	organization = { Springer International Publishing},
	edition = {1},
	chapter = {3},
	address = {Cham},
	abstract = {We aim to extend existing models of single-cell mechanics to the EMI framework, to define spatially resolved mechanical models of cardiac myocytes embedded in a passive extracellular space. The models introduced here will be pure mechanics models employing fairly simple constitutive laws for active and passive mechanics. Future extensions of the models may include a coupling to the electrophysiology and electro-diffusion models described in the other chapters, to study the impact of spatially heterogeneous ion concentrations on the cell and tissue mechanics.},
	author = {Telle, {\r A}shild and Wall, Samuel and Sundnes, Joakim},
	editor = {Tveito, Aslak and Marie E. {Rognes} and Mardal, Kent-Andre}
}
@article {27048,
	title = {A computational study on integrated mechanisms of mechano-electric feedback in ischemic arrhythmogenesis},
	journal = {SAGE},
	year = {2020},
	publisher = {Clinical Medicine Insights: Cardiology},
	author = {Timmermann, Viviane and Alexander T. {Quinn} and Sundnes, Joakim and Wall, Samuel and Andrew D. {McCulloch} and Andrew G {Edwards}}
}
@article {27367,
	title = {Computational translation of drug effects from animal experiments to human ventricular myocytes},
	journal = {Nature Scientific Reports },
	number = {10},
	year = {2020},
	pages = {10537},
	publisher = {Nature Publishing Group},
	abstract = {Using animal cells and tissues as precise measuring devices for developing new drugs presents a long- standing challenge for the pharmaceutical industry. Despite the very significant resources that continue to be dedicated to animal testing of new compounds, only qualitative results can be obtained. This often results in both false positives and false negatives. Here, we show how the effect of drugs applied to animal ventricular myocytes can be translated, quantitatively, to estimate a number of different effects of the same drug on human cardiomyocytes. We illustrate and validate our methodology by translating, from animal to human, the effect of dofetilide applied to dog cardiomyocytes, the effect\&nbsp;of E-4031 applied to zebrafish cardiomyocytes, and, finally, the effect of sotalol applied to rabbit cardiomyocytes. In all cases, the accuracy of our quantitative estimates are demonstrated. Our computations reveal that, in principle, electrophysiological data from testing using animal ventricular myocytes, can give precise, quantitative estimates of the effect of new compounds on human cardiomyocytes.},
	doi = {10.1038/s41598-018-35858-7},
	url = { https://rdcu.be/b5iBl},
	author = {Tveito, Aslak and Karoline Horgmo {J{\ae}ger} and Maleckar, Molly and Wayne R. {Giles} and Wall, Samuel}
}
@article {27079,
	title = {Improved computational identification of drug response using optical measurements of human stem cell derived cardiomyocytes in microphysiological systems},
	journal = {Frontiers in Pharmacology},
	volume = {10},
	number = {1648},
	year = {2020},
	month = {02/2020},
	publisher = {Frontiers},
	abstract = {Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs) hold great potential for drug screening applications. However, their usefulness is limited by the relative immaturity of the cells{\textquoteright} electrophysiological properties as compared to native cardiomyocytes in the adult human heart. In this work, we extend and improve on methodology to address this limitation, building on previously introduced computational procedures which predict drug effects for adult cells based on changes in optical measurements of action potentials and calcium\&nbsp;transients made in stem cell derived cardiac microtissues. This methodology quantifies ion channel changes through the inversion of data into a mathematical model, and maps this response to an adult phenotype through the assumption of functional invariance of fundamental intracellular and membrane channels during maturation.\&nbsp;Here we utilize an updated action potential model to represent both hiPSC-CMs and adult cardiomyocytes, apply an IC50-based\&nbsp;model of dose-dependent drug effects, and introduce a continuation-based optimization algorithm for analysis of dose escalation measurements using five drugs with known effects. The improved methodology can identify drug induced changes more efficiently, and quantitate important metrics such as IC50 in line with published values. Consequently, the updated methodology is a step towards employing computational procedures to elucidate drug effects in adult cardiomyocytes for new drugs using stem cell-derived experimental tissues.\&nbsp;},
	doi = {10.3389/fphar.2019.01648},
	author = {Karoline Horgmo {J{\ae}ger} and Charwat, Verena and Charrez, B{\'e}r{\'e}nice and Finsberg, Henrik and Maleckar, Molly and Wall, Samuel and Kevin E. {Healy} and Tveito, Aslak}
}
@article {27176,
	title = {Multisite pacing and myocardial scars: a computational study},
	journal = {Computer Methods in Biomechanics and Biomedical Engineering},
	volume = {23},
	year = {2020},
	month = {01/2020},
	publisher = {Taylor and Francis},
	issn = {1025-5842},
	doi = {10.1080/10255842.2020.1711885},
	url = {https://www.tandfonline.com/doi/full/10.1080/10255842.2020.1711885},
	author = {Albatat, Mohammad and Bergsland, Jacob and Arevalo, Hermenegild and Hans Henrik {Odland} and Wall, Samuel and Sundnes, Joakim and Balasingham, Ilangko}
}
@article {timmermann2019arrhythmogenic,
	title = {Arrhythmogenic current generation by myofilament-triggered Ca2+ release and sarcomere heterogeneity},
	journal = {Biophysical Journal},
	volume = {117},
	year = {2019},
	pages = {2471-2485},
	publisher = {Cell Press},
	author = {Timmermann, Viviane and Andrew G {Edwards} and Wall, Samuel and Sundnes, Joakim and Andrew D. {McCulloch}}
}
@article {27087,
	title = {Computational quantification of patient-specific changes in ventricular dynamics associated with pulmonary hypertension},
	journal = {American Journal of Physiology-Heart and Circulatory Physiology},
	volume = {31711911},
	year = {2019},
	pages = {H1363 - H1375},
	publisher = {American Journal of Physiology},
	author = {Finsberg, Henrik and Xi, Ce and Zhao, Xiaodan and Le Tan, Ju and Genet, Martin and Sundnes, Joakim and Lik Chuan {Lee} and Zhong, Liang and Wall, Samuel}
}
@article {26641,
	title = {Detecting undetectables: Can conductances of action potential models be changed without appreciable change in the transmembrane potential?},
	journal = {Chaos},
	volume = {29},
	number = {073102},
	year = {2019},
	month = {07/2019},
	publisher = {AIP},
	abstract = {Mathematical models describing the dynamics of the cardiac action potential are of great value for understanding how changes to the system can disrupt the normal electrical activity of cells and tissue in the heart. However, to represent specific data, these models must be parameterized, and adjustment of the maximum conductances of the individual contributing ionic currents is a commonly used method. Here, we present a method for investigating the uniqueness of such resulting parameterizations. Our key question is: Can the maximum conductances of a model be changed without giving any appreciable changes in the action potential? If so, the model parameters are not unique and this poses a major problem in using the models to identify changes in parameters from data, for instance, to evaluate potential drug effects. We propose a method for evaluating this uniqueness, founded on the singular value decomposition of a matrix consisting of the individual ionic currents. Small singular values of this matrix signify lack of parameter uniqueness and we show that the conclusion from linear analysis of the matrix carries over to provide insight into the uniqueness of the parameters in the nonlinear case. Using numerical experiments, we quantify the identifiability of the maximum conductances of well-known models of the cardiac action potential. Furthermore, we show how the identifiability depends on the time step used in the observation of the currents, how the application of drugs may change identifiability, and, finally, how the stimulation protocol can be used to improve the identifiability of a model.},
	doi = {10.1063/1.5087629},
	url = {https://aip.scitation.org/doi/10.1063/1.5087629},
	author = {Karoline Horgmo {J{\ae}ger} and Wall, Samuel and Tveito, Aslak}
}
@misc {27104,
	title = {Finite element modeling of cardiac tissue in heart-on-a-chip systems},
	howpublished = {Washington DC, USA},
	year = {2019},
	abstract = {Heart-on-a-chip devices can be used to control and monitor the cellular microenvironment of human cardiac microtissue, showing great potential as powerful cardiotoxicity screening platforms. Human induced pluripotent stem cell derived cardiomyocytes are combined with microfluidic technology to derive a tissue mimicking adult human ventricular dimensions, physiology and uniaxial beating properties, which can be used for pharmalogical studies and disease modeling [3]. Within such microphysiological systems, indicators of cardiac function, such as electrophysiology (action potential, calcium transient) and beating physiology (beat rate, contraction velocity) can be readily measured using image analysis techniques [2]. However, important mechanical properties such as myocyte contractility, tissue stress and tissue stiffness, cannot easily be revealed using current techniques. We thuspropose a numerical model simulating the dynamic mechanics of the microtissue.For our model we combined previously published models for cardiac electrochemical and mechanical properties, embedded with a geometrical representation of the tissue chamber, to quantify the passive and active properties of the system. We used a zero-dimensional point model of cardiac myofilaments developed by Rice et. al. [4] to calculate the force generated by single myocytes. This was coupled with a three-dimensional continuum model for myocardial mechanics given by Guccione et. al [1]. Together this gave a set of non-linear partial differential equations describing the stress and deformation, which we set up to find an equilibrium solution and calculate the resulting Cauchy stress. We imposed appropriate boundary conditions and solve the system using FEniCS {\textendash} both the framework for spatially dependent nonlinear boundary value problems, and for time-dependent initial value problems {\textendash} and evaluated the system using data provided from experimental pharmacology studies.Our results provide a quantification of the Cauchy stress developed through active myocardial contraction through the domain, and relative changes under differing simulated conditions. We compared these results with experimental measurements of contraction forces, using the same points for measurements. In this dual analysis we observed a comparable relative increase in Cauchy stress and microscopic measurements of contraction force, respectively, correlated with increasing drug doses. This combined in silico / in vitro system give us a platform for the quantification of internal mechanical properties, providing a framework for understanding the physiology complexity of microorgan tissues. Such a system can give new insight in cardiac mechanics in itself, and might also be important for further development of appropriate mathematical models.},
	author = {Telle, {\r A}shild and Charrez, B{\'e}r{\'e}nice and Kevin E. {Healy} and Tveito, Aslak and Wall, Samuel}
}
@inproceedings {27157,
	title = {Investigating the Pro- and Anti-Arrhythmic Properties of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes in Post-Infarction Patient Hearts: A Modeling Study},
	journal = {6th International Conference on Computational and Mathematical Biomedical Engineering},
	volume = {1},
	year = {2019},
	pages = {357-360},
	publisher = {Zeta Computational Resources Ltd.},
	issn = {2227-9385},
	author = {Arevalo, Hermenegild and Karoline Horgmo {J{\ae}ger} and Wall, Samuel}
}
@misc {27103,
	title = {A Numerical Model of Heart -on -a-Chip Systems  {\textendash} A Tool for Cardiotoxicity Screening},
	howpublished = {Melbourne, Australia},
	year = {2019},
	abstract = {Organ-on-a-chip devices can be used to control and monitor the cellular microenvironment of human microtissues, providing a promising platform for disease and drug development studies. Here we describe a heart-on-a-chip system combining human induced pluripotent stem cell derived cardiomyocytes with microfluidic technology as a cardiotoxicity screening platform (Mathur et al. Sci. Rep. 2015). Within this microphysiological system, image tracking techniques can be used to monitor important indicators of cardiac function, such as contraction velocity, beat rate, and prevalence (Huebsch et al. Tissue Eng. C. 2015). However, mechanical contraction properties such as force and stress are harder to capture. This motivates the need for a numerical model simulating the mechanical behavior of the microtissue, to predict and help monitor the effect of drugs and mutations on the contractility of the tissue. In this study we propose a model for cardiac tissue applied to a geometric representation of the chip system to predict contraction forces and strain. We are using a zero-dimensional point model of cardiac myofilaments developed by Rice et. al. (Biophysical Journal 2008) to calculate the force generated by single myocytes, embedded within a continuum model for the mechanics of ventricular myocardium given by Guccione et. al (ASME 1991). Combined, this give us a system of partial differential equations, which we solve using the finite element method over a given three-dimensional mesh. The parameters in the model are optimized using data from real heart-on-a-chip devices. We evaluated the system for pharmacology studies (as of now, negative and positive inotropes respectively flecainide and isoproterenol) using experimentally measured calcium amplitude transients to predict resulting Cauchy stresses at increasing drug doses. Combining our numerical model for mechanical simulation with experimental heart-on-a-chip data produced comparable dose response results. We observed similar trends for measurements of internal forces of the tissue under isometric conditions. This combined in silico / in vitro analysis system provides the possibility of a robust technique for understanding the physiological complexity of micro-organ function in vitro, facilitating contraction force assessment for drug screening and disease modeling in heart-on-a-chip systems.\&nbsp;},
	author = {Telle, {\r A}shild and Charrez, Berenice and Kevin E. {Healy} and Tveito, Aslak and Wall, Samuel}
}
@misc {27105,
	title = {A numerical model of mechanical properties of cardiac tissue in heart-on-a-chip devices},
	year = {2019},
	address = {Norwegian meeting on PDEs, Trondheim, Norway},
	author = {Telle, {\r A}shild and Charrez, B{\'e}r{\'e}nice and Kevin E. {Healy} and Tveito, Aslak and Wall, Samuel}
}
@misc {27046,
	title = {A one-dimensional computational study of mechano-electric feedback and arrhythmogenic current generation},
	howpublished = {Gordon Research Conference "Cardiac Arrhythmia Mechanisms", Barga, Italy},
	year = {2019},
	author = {Timmermann, Viviane and Sundnes, Joakim and Wall, Samuel and Andrew D. {McCulloch} and Andrew G {Edwards}}
}
@article {doi:10.1080/10255842.2019.1579312,
	title = {Sensitivity of stress and strain calculations to passive material parameters in cardiac mechanical models using unloaded geometries},
	journal = {Computer Methods in Biomechanics and Biomedical Engineering},
	volume = {22},
	number = {6},
	year = {2019},
	note = {PMID: 30822148},
	pages = {664-675},
	publisher = {Taylor \& Francis},
	doi = {10.1080/10255842.2019.1579312},
	url = {https://doi.org/10.1080/10255842.2019.1579312},
	author = {Kallhovd, Siri and Sundnes, Joakim and Wall, Samuel}
}
@misc {26382,
	title = {Adjoint Based Data Assimilation for Quantification of Dynamic Mechanical Behavior of the Heart},
	howpublished = {World Congress of Biomechanics, New York, USA},
	year = {2018},
	author = {Wall, Samuel and Finsberg, Henrik and Balaban, Gabriel and Sundnes, Joakim and Lik Chuan {Lee}}
}
@misc {26381,
	title = {Adjoint based data assimilation for quantifying mechanical properties in clinical cardiac mechanics},
	howpublished = {Computer Methods in Biomechanics and Bioengineering, Lisbon, Portugal},
	year = {2018},
	author = {Wall, Samuel and Finsberg, Henrik and Balaban, Gabriel and Lik Chuan {Lee}}
}
@misc {26384,
	title = {Adjoint Based Personalization of Mechanical Models for Quantification of Right Ventricular Failure in Pulmonary Hypertension},
	year = {2018},
	address = {Heart by Numbers Conference, Berlin, Germany},
	author = {Finsberg, Henrik and Xi, Ce and Xiaodan, Zhao and Le Tan, Ju and Genet, Martin and Sundnes, Joakim and Lik Chuan {Lee} and Zhong, Liang and Wall, Samuel}
}
@misc {27045,
	title = {A computational study of the contribution of mechano-electric feedback to arrhythmogenic current generation},
	howpublished = {Berlin, Germany},
	year = {2018},
	publisher = {Heart by Numbers, Biophysical Society},
	author = {Timmermann, Viviane and Sundnes, Joakim and Wall, Samuel and Andrew D. {McCulloch} and Andrew G {Edwards}}
}
@article {25636,
	title = {Efficient estimation of personalized biventricular mechanical function employing gradient-based optimization},
	journal = { International Journal for Numerical Methods in Biomedical Engineering},
	volume = {34},
	year = {2018},
	publisher = {John Wiley \& Sons},
	doi = {10.1002/cnm.2982},
	author = {Finsberg, Henrik and Xi, Ce and Le Tan, Ju and Zhong, L and Genet, Martin and Sundnes, Joakim and Lik Chuan {Lee} and Wall, Samuel}
}
@inproceedings {26370,
	title = {Electromechanical Model to Predict Cardiac Resynchronization Therapy},
	journal = {2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
	year = {2018},
	pages = {5446-5459},
	publisher = {IEEE},
	doi = {10.1109/EMBC.2018.8513539},
	author = {Albatat, Mohammad and King, Ryan and Unger, Laura and Arevalo, Hermenegild and Wall, Samuel and Sundnes, Joakim and Bergsland, Jacob and Balasingham, Ilangko}
}
@misc {26385,
	title = {In Silico - Augmented Cardiac Microphysiological Systems for Evaluating Cardiac Drug Effects},
	year = {2018},
	address = {BMES Conference, Atlanta, USA},
	author = {Wall, Samuel and Karoline Horgmo {J{\ae}ger} and Huebsch, Nathaniel and Charrez, B{\'e}r{\'e}nice and Healy, Kevin and Tveito, Aslak}
}
@misc {26386,
	title = {In Silico - Augmented Cardiac Microphysiological Systems for Evaluating Cardiac Drug Effects},
	year = {2018},
	address = {Keystone Organ on Chip Symposium, Montana, USA},
	author = {Wall, Samuel and Karoline Horgmo {J{\ae}ger} and Huebsch, Nathaniel and Charrez, B{\'e}r{\'e}nice and Healy, Kevin and Tveito, Aslak}
}
@misc {26383,
	title = {In Silico Modeling of Cardiac Microphysiological  Systems for Evaluating Drug Side Effects},
	howpublished = {Heart By Numbers Conference, Berlin, Germany},
	year = {2018},
	author = {Wall, Samuel and Tveito, Aslak and Karoline Horgmo {J{\ae}ger} and Andrew G {Edwards} and Healy, Kevin and Huebsch, Nathaniel and Charrez, B{\'e}r{\'e}nice}
}
@article {25968,
	title = {In vivo estimation of elastic heterogeneity in an infarcted human heart},
	journal = {Biomechanics and Modeling in Mechanobiology},
	volume = {17},
	year = {2018},
	month = {May-05-2019},
	pages = {1317{\textendash}1329},
	publisher = {Springer},
	address = {Berlin Heidelberg},
	abstract = {In myocardial infarction, muscle tissue of the heart is damaged as a result of ceased or severely impaired blood flow. Survivors have an increased risk of further complications, possibly leading to heart failure. Material properties play an important role in determining post-infarction outcome. Due to spatial variation in scarring, material properties can be expected to vary throughout the tissue of a heart after an infarction. In this study we propose a data assimilation technique that can efficiently estimate heterogeneous elastic material properties in a personalized model of cardiac mechanics. The proposed data assimilation is tested on a clinical dataset consisting of regional left ventricular strains and in vivo pressures during atrial systole from a human with a myocardial infarction. Good matches to regional strains are obtained, and simulated equi-biaxial tests are carried out to demonstrate regional heterogeneities in stress{\textendash}strain relationships. A synthetic data test shows a good match of estimated versus ground truth material parameter fields in the presence of no to low levels of noise. This study is the first to apply adjoint-based data assimilation to the important problem of estimating cardiac elastic heterogeneities in 3-D from medical images.},
	issn = {1617-7959},
	doi = {10.1007/s10237-018-1028-5},
	url = {http://link.springer.com/10.1007/s10237-018-1028-5},
	author = {Balaban, Gabriel and Finsberg, Henrik and Simon W {Funke} and Trine F. {H{\r a}land} and Hopp, Einar and Sundnes, Joakim and Wall, Samuel and Marie E. {Rognes}}
}
@article {26238,
	title = {Inversion and computational maturation of drug response using human stem cell derived cardiomyocytes in microphysiological systems},
	journal = {Nature Scientific Reports },
	volume = {8},
	number = {17626},
	year = {2018},
	month = {12/2018},
	publisher = {Springer Nature},
	abstract = {While cardiomyocytes differentiated from human induced pluripotent stems cells (hiPSCs) hold great promise for drug screening, the electrophysiological properties of these cells can be variable and immature, producing results that are significantly different from their human adult counterparts. Here, we describe a computational framework to address this limitation, and show how in silico methods, applied to measurements on immature cardiomyocytes, can be used to both identify drug action and to predict its effect in mature cells. Our synthetic and experimental results indicate that optically obtained waveforms of voltage and calcium from microphysiological systems can be inverted into information on drug ion channel blockage, and then, through assuming functional invariance of proteins during maturation, this data can be used to predict drug induced changes in mature ventricular cells. Together, this pipeline of measurements and computational analysis could significantly improve the ability of hiPSC derived cardiomycocytes to predict dangerous drug side effects.},
	doi = {10.1038/s41598-018-35858-7},
	url = {https://doi.org/10.1038/s41598-018-35858-7},
	author = {Tveito, Aslak and Karoline Horgmo {J{\ae}ger} and Huebsch, Nathaniel and Charrez, B{\'e}r{\'e}nice and Andrew G {Edwards} and Wall, Samuel and Kevin E. {Healy}}
}
@article {Huebsch485169,
	title = {Metabolically-Driven Maturation of hiPSC-Cell Derived Heart-on-a-Chip},
	journal = {{bioRxiv},
	year = {2018},
	publisher = {Cold Spring Harbor Laboratory},
	abstract = {Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CM) are a promising in vitro tool for drug development and disease modeling, but their immature electrophysiology limits their diagnostic utility. Tissue engineering approaches involving aligned and 3D culture enhance hiPSC-CM maturation but are insufficient to induce electrophysiological maturation. We hypothesized that recapitulating post-natal switching of the heart{\textquoteright}s primary adenosine triphosphate source from glycolysis to fatty acid oxidation could enhance maturation of hiPSC-CM. We combined hiPSC-CM with microfabrication to create 3D cardiac microphysiological systems (MPS) that enhanced immediate microtissue alignment and tissue specific extracellular matrix production. Using Robust Experimental design, we identified a maturation media that allowed the cardiac MPS to correctly assess false positive and negative drug response. Finally, we employed mathematical modeling and gene expression data to explain the observed changes in electrophysiology and pharmacology of MPS exposed to maturation media. In contrast, the same media had no effects on 2D hiPSC-CM monolayers. These results suggest that systematic combination of biophysical stimuli and metabolic cues can enhance the electrophysiological maturation of hiPSC-derived cardiomyocytes.},
	doi = {10.1101/485169},
	url = {https://www.biorxiv.org/content/early/2018/12/10/485169},
	author = {Huebsch, Nathaniel and Charrez, Berenice and Siemons, Brian and Steven C. {Boggess} and Wall, Samuel and Charwat, Verena and Jaeger, Karoline and Felipe Lee T. {Montiel} and Nicholas C. {Jeffreys} and Deveshwar, Nikhil and Andrew G {Edwards} and Serrano, Jonathan and Snuderl, Matija and Stahl, Andreas and Tveito, Aslak and Evan W. {Miller} and Kevin E. {Healy}}
}
@misc {25637,
	title = {Assessment of regional myocardial work through adjoint-based data assimilation},
	howpublished = {Oslo, Norway},
	year = {2017},
	type = {International Conference on Computational Science and Engineering,  In memory of Hans Petter Langtangen},
	abstract = {Assessment of regional myocardial work through adjoint-based data assimilationIntroductionTo achieve efficient pumping of blood to the body, the healthy heart contracts in a synchronous manner. However, heart disease can alter how the heart is activated during a beat, and dyssynchronous contraction can occur, reducing the overall pumping efficiency. Advanced treatments exist for such cases,\&nbsp;but selecting patients likely to respond can be challenging. The existing selection criteria, based on organ level measures of activation and contraction, have relatively low specificity. \&nbsp;It is therefore of interest to\&nbsp;extract new biomarkers to help better identify potential responders. Here we explore one example of a potential biomarker, the regional myocardial work [1], a measure of cardiac efficiency, using a computational model of cardiac mechanics optimized to patient specific data using a high level adjoint based data assimilation method.\&nbsp;\&nbsp;MethodsLeft ventricular (LV) geometry was obtained from 4D echocardiography, and the segmented chamber was modelled as an incompressible, continuous hyperelastic body described via an transversely isotropic material law[2]. \&nbsp;Active force development was modeled through additively decomposing stress into passive and active stresses, the latter added along the cardiac fiber direction, defined by a rule based architecture.\&nbsp;\&nbsp;The model was fit to 4D imaging of the LV through the cardiac cycle using an adjoint-based\&nbsp;data assimilation technique, which automatically solves for the gradient of the solution with respect to local active stress, for highly efficient minimization of model misfit against collected data. Simulations were optimized both globally and regionally in 17 delineated segments[3].\&nbsp;With these simulations, the amount of mechanical work performed between time point tm\&nbsp;and tn\&nbsp;could be regionally calculated through -W(tm,\&nbsp;tn)\&nbsp;=\&nbsp;∫ S:\&nbsp;∂tE dt = ∑i\&nbsp;S(ti-{\textonehalf}):\&nbsp;dE(ti-{\textonehalf})\&nbsp;where\&nbsp;S(ti-{\textonehalf}) = 0.5*(S(ti)+S(ti-1))\&nbsp;\&nbsp;and\&nbsp;\&nbsp;dE(ti-{\textonehalf}) = E(ti)-E(ti-1)\&nbsp;Here subscript t indicates the time point, S is the Second Piola-Kirchhoff stress tensor and E is the Green-Lagrange strain tensor.\&nbsp;ResultsWe tested the method on healthy control subjects and patients suffering from left bundle branch block (LBBB). The results show an excellent fit between\&nbsp;measured and simulated strain (R^2 = 0.8) and volume (R^2 = 1.0).\&nbsp;The estimated regional myocardial work, assessed in these segments, shows clear differences between the healthy and diseased patients (e.g Mid Septal longitudinal wasted work ratio[1]: 1.45 (LBBB), 0.24(Healthy)) and can potentially be used as a biomarker to map regional cardiac dysfunction.\&nbsp;References[1]\&nbsp;doi:10.1152/ajpheart.00191.2013\&nbsp;[2] doi:10.1098/rsta.2009.0091\&nbsp;[3] doi:10.1002/cnm.2863\&nbsp;},
	url = {https://cseconf2017.files.wordpress.com/2017/09/2017-09-28-cseconf2017-complete-program.pdf},
	author = {Finsberg, Henrik and Aalen, John and Larsen, Camilla and Remme, Espen and Sundnes, Joakim and Otto A. {Smiseth} and Wall, Samuel}
}
@article {25635,
	title = {Estimating cardiac contraction through high resolution data assimilation of a personalized mechanical model},
	journal = {Journal of Computational Science},
	volume = {24},
	year = {2017},
	pages = {85-90},
	publisher = {Elsevier},
	keywords = {Adjoint Method, Cardiac Mechanics, Contractility, Data assimilation, PDE-constrained optimization},
	issn = {1877-7503},
	doi = {10.1016/j.jocs.2017.07.013},
	url = {http://www.sciencedirect.com/science/article/pii/S1877750317308190},
	author = {Finsberg, Henrik and Balaban, Gabriel and Ross, Stian and Trine F {H{\r a}land} and Hans Henrik {Odland} and Sundnes, Joakim and Wall, Samuel}
}
@article {24721,
	title = {High resolution data assimilation of cardiac mechanics},
	journal = {International journal for numerical methods in biomedical engineering},
	volume = {33},
	number = {11},
	year = {2017},
	month = {04/2017},
	pages = {e2863},
	publisher = {John Wiley \& Sons, Ltd},
	doi = {10.1002/cnm.2863},
	author = {Balaban, Gabriel and Finsberg, Henrik and Hans Henrik {Odland} and Marie E. {Rognes} and Ross, Stian and Sundnes, Joakim and Wall, Samuel}
}
@misc {25790,
	title = {Integrated Mechanisms of Mechano-Electric feedback in Ischemic Arrhythmogenesis},
	howpublished = {Bergen, Norway},
	year = {2017},
	author = {Timmermann, Viviane and Andrew G {Edwards} and Sundnes, Joakim and Andrew D. {McCulloch} and Wall, Samuel and T. A. {Quinn}}
}
@misc {25792,
	title = {Integrated Mechanisms of Mechano-Electric Feedback in Ischemic Arrhythmogenesis},
	year = {2017},
	month = {09/2017},
	address = {Oslo, Norway},
	author = {Timmermann, Viviane and Wall, Samuel and Sundnes, Joakim and T. A. {Quinn} and Andrew G {Edwards}}
}
@article {25788,
	title = {An integrative appraisal of mechano-electric feedback mechanisms in the heart},
	journal = {Progress in biophysics and molecular biology},
	volume = {130},
	year = {2017},
	pages = {404{\textendash}417},
	publisher = {Elsevier},
	author = {Timmermann, Viviane and Lars A {Dejgaard} and Kristina H {Haugaa} and Andrew G {Edwards} and Sundnes, Joakim and Andrew D. {McCulloch} and Wall, Samuel}
}
@misc {25457,
	title = {Mechanical Analysis of Pulmonary Hypertension via Adjoint based Data Assimilation of a Finite Element Model},
	year = {2017},
	month = {06/2017},
	address = {Summer Biomechanics, Bioengineering, and Biotransport Conference, Tuscon, USA},
	author = {Finsberg, Henrik and Xi, Ce and Tan, JL and Zhong, L and Lee, LC and Sundnes, Joakim and Wall, Samuel}
}
@misc {25789,
	title = {Role of Electromechanical Feedback in Stretch Induced Arrhythmias : From Single Myocyte to Multicellular Level},
	year = {2017},
	month = {02/2017},
	address = {Gordon Research Conference on Arrhythmia Mechanisms, Ventura, California, USA},
	author = {Timmermann, Viviane and Lars A {Dejgaard} and Andrew D. {McCulloch} and Kristina H {Haugaa} and Andrew G {Edwards} and Wall, Samuel}
}
@misc {25419,
	title = {Sensitivity Analysis of Cardiac Growth Models},
	year = {2017},
	address = {FEniCS 2017 conference, Luxembourg},
	abstract = {\&nbsp;Introduction The heart is a dynamic organ capable of changing its shape in response to the body{\textquoteright}s demands. For example, the human heart continuously adapts in size and geometry to meet greater blood flow needs of the growing body during normal development. In this case, a gradually imposed volume overload leads to progressive chamber enlargement. Another example of a normal physiological growth can be found in the athlete{\textquoteright}s heart, where a sustained elevated chamber pressure results in the chamber wall thickening and an overall increase in cardiac mass. Growth processes, however, can also be maladaptive as found in many cardiovascular diseases where structural changes in the heart progressively decompensate cardiac function.In order to better understand this balance between adaptive and maladaptive cardiac growth, we examine the effect of known growth stimuli using a mechanical model of the heart. We perform a sensitivity analysis of existing growth models in order to assess the relative importance of model parameters and respective mechanisms. This work can eventually lead to simplifications in the model systems for prediction of growth, or help in localizing shortcomings that need to be addressed in the existing modeling frameworks.Methods In order to simulate the motion of the heart throughout the cardiac cycle, we use a nonlinear finite element (FE) model of a realistic left ventricle (LV) coupled to a lumped-parameter model of the systemic circulation. Under the quasi-static assumption, this problem is reduced to finding the displacement u, hydrostatic pressure p and LV pressure p LV that minimize the incompressible strain energy functional Π parameterised by the LV volume V LV [1]: The muscular tissue of the heart is modeled as a transversely isotropic hyperelastic material via the strain energy density Ψ [2]:where m = (a, b, a f , b f ) is a set of passive material parameters, C e is the elastic right Cauchy-Green. By introducing an activation parameter γ representing the active tensor, I1 = trC e and I shortening in the fiber direction f 0 at zero-load, the model incorporates muscle contraction using the active strain approach, which is based on a multiplicative decomposision of the deformation gradient F = I + Grad(u) into an elastic and an active parts F = F e F a with F a defined as:The dynamic changes in the ventricular blood pressure and volume over the entire cardiac cycle are modeled by a three-element Windkessel model described by a system of ordinary differential equations [3]. At each time step, the coupling between the FE model and the circulatory model is achieved through an additional Lagrange multiplier p LV which represents the LV cavity pressure. The problem (1) is solved such that the simulated LV cavity volume V (u) matches the target volume value V LV obtained from the circulatory model.Growth process in the heart wall is modeled by deforming the reference unloaded geometry to a new grown configuration, again through a multiplicative decomposition of F into an elastic and, this time, a growth part, where F = F e F g . The constitutive laws for finite growth can be expressed using a generic format for the growth tensor F g = θ f f 0 (x) f 0 + θ s s 0 (x) s 0 + θ n n 0 (x) n 0. The evolution of the local tissue growth parameter θ g = [θ f , θ s , θ n ] T can be defined in terms of a growth activation function φ (F e ) and a growth rate function k(θ θ g ) which specifies the speed and nonlinearity of the growth process [4].Using the above described model it is possible to simulate various physiological conditions together with the associated structural adaptation of the heart walls in response to change in loadings. In each case, a growth model can be chosen depending on the nature of the considered physiology. The sensitivity of the system{\textquoteright}s grown state to the prescribed growth model can then be estimated. For this, we define an objective functional J(u), the model output of interest, which is to serve as a qualitative and/or quantitative measure of how well the growth model reproduces the expected behavior. More specifically, if we are to compare the model response to a real measurement, then the objective functional can be defined as the mismatch between the simulated u and the measured u exp grown states at a reference time tref :Finally, the sensitivities of J to θ , where θ is a set of growth parameters specific to a given model, are defined as dJ(u)dθ.The solver has been developed within the FEniCS [5] framework and the functional gradients are computed by solving an automatically derived adjoint equations [6].Results We first focus on implementing and testing a strain-driven growth law to simulate a volume overload state of the left ventricle. To achieve this, the initial physiological equilibrium of the heart is altered by increasing a diastolic filling pressure. This initiates cardiac growth that continues until a new equilibrium state is reached. The model is able to reproduce qualitatively experimental observations reported in the literature, such as LV cavity dilation due to fiber over-stretching and a gradual increase in myocardium volume. At the next step, we perform a sensitivity analysis of the model with respect to the growth model parameters and evaluate its performance in reproducing the expected growth behavior.},
	url = {http://easychair.org/smart-program/FEniCS{\textquoteright}17/2017-06-12.html$\#$talk:45748},
	author = {Nikitushkina, Liubov and Simon W {Funke} and Finsberg, Henrik and Lik Chuan {Lee} and Wall, Samuel}
}
@misc {24969,
	title = {Impact of material parameter uncertainty on stress in patient specific models of the heart},
	howpublished = {SIAM Conference on uncertainty quantification, Lausanne, Switzerland},
	year = {2016},
	author = {Sundnes, Joakim and Kallhovd, Siri and Wall, Samuel}
}
@misc {24970,
	title = {Impact of material parameter variations on stress in patient specific models of the heart},
	howpublished = {World Congress on Computational Mechanics, Seoul, South Korea},
	year = {2016},
	author = {Sundnes, Joakim and Kallhovd, Siri and Wall, Samuel}
}
@article {25483,
	title = {An integrated electromechanical-growth heart model for simulating cardiac therapies},
	journal = {Biomechanics and modeling in mechanobiology},
	volume = {15},
	number = {4},
	year = {2016},
	pages = {791{\textendash}803},
	publisher = {{Springer Berlin Heidelberg},
	abstract = {An emerging class of models has been developed in recent years to predict cardiac growth and remodeling. We recently developed a cardiac  constitutive model that predicts remodeling in response to elevated hemodynamics loading, and a subsequent reversal of the remodeling process when the loading is reduced. Here, we describe the integration of this model to an existing strongly coupled electromechanical model of the heart. },
	author = {Lik Chuan {Lee} and Sundnes, Joakim and Genet, Martin and Jonathan F {Wenk} and Wall, Samuel}
}
@inproceedings {24567,
	title = {Optimization of a Spatially Varying Cardiac Contraction parameter using the Adjoint Method},
	journal = {FEniCS{\textquoteright}16},
	year = {2016},
	abstract = {A cardiac computational model is constrained using clinical measurements such as pressure, volume and regional strain. The problem is formulated as a PDE-constrained optimisation problem where the objective functional represents the misfit between measured and simulated data. The control parameter for the active phase is a spatially varying contraction parameter defined at every vertex in the mesh. This makes gradient calculations using the adjoint approach computationally advantageous over standard finite difference approximations.},
	keywords = {Adjoint Method, Cardiac Mechanics, parameter estimation, PDE-constrained optimization},
	author = {Finsberg, Henrik and Balaban, Gabriel and Marie E. {Rognes} and Sundnes, Joakim and Wall, Samuel}
}
@misc {24417,
	title = {Patient Specific Modeling of Cardiac Mechanics using the Active Strain Formulation},
	howpublished = {Geilo Winter School},
	year = {2016},
	author = {Finsberg, Henrik and Balaban, Gabriel and Wall, Samuel and Sundnes, Joakim and Marie E. {Rognes}}
}
@article {27085,
	title = {Patient-Specific Computational Analysis of Ventricular Mechanics in Pulmonary Arterial Hypertension},
	journal = {Journal of Biomechanical Engineering},
	volume = {1385330362011320421116451331076894730120114795986134127134024171584951413564291214135128562591171196226568296300302289117},
	year = {2016},
	month = {Jan-11-2016},
	publisher = {ASME Digital Collection},
	issn = {0148-0731},
	doi = {10.1115/1.4034559},
	author = {Xi, Ce and Latnie, Candace and Zhao, Xiaodan and Le Tan, Ju and Wall, Samuel and Genet, Martin and Zhong, Liang and Lik Chuan {Lee}}
}
@inproceedings {24991,
	title = {Personalized Cardiac Mechanical Model using a High Resolution Contraction Field},
	journal = {VPH16 Translating VPH to the Clinic},
	year = {2016},
	author = {Finsberg, Henrik and Balaban, Gabriel and Sundnes, Joakim and Marie E. {Rognes} and Hans Henrik {Odland} and Ross, Stian and Wall, Samuel}
}
@article {24650,
	title = {Physics-based computer simulation of the long-term effects of cardiac regenerative therapies},
	journal = {Technology},
	volume = {4},
	number = {01},
	year = {2016},
	pages = {23{\textendash}29},
	publisher = {{World Scientific Publishing Co./Imperial College Press},
	author = {Lik Chuan {Lee} and Sundnes, Joakim and Genet, Martin and Wall, Samuel}
}
@inproceedings {24441,
	title = {Quantitative Measures of Right Ventricular Shape Abnormalities in ARVC Patients},
	journal = {24th Annual Meeting of the International Society for Magnetic Resonance in Medicine },
	year = {2016},
	month = {2016},
	publisher = {ISMRM},
	abstract = {Better understanding of the impact that disease has on ventricular shape remodeling and improved tools for quantifying disease severity are needed in complex diseases such as ARVC. We propose a method to automatically characterise right ventricular shape features in ARVC patients using statistical methods applied to shapes extracted from CMR images in a population of 27 ARVC patients. In addition to characterizing the typical shape features in ARVC, the level of severity of any given shape feature (e.g. dilation) can be measured in a new patient to quantify the degree in which that specific feature is present in that patient.},
	author = {Kristin Sarah {Mcleod} and Wall, Samuel and Saberniak, J{\o}rg},
	editor = {Haugaa, Kristina}
}
@misc {25791,
	title = {Role of Electromechanical Feedback in Mitral Valve Prolapse Arrhythmia},
	year = {2016},
	month = {09/2016},
	publisher = {Conference on Cardiac Mechano-Electric Couping and Arrhythmias},
	address = {Freiburg, Germany},
	author = {Timmermann, Viviane and Andrew G {Edwards} and Sundnes, Joakim and Andrew D. {McCulloch} and Wall, Samuel}
}
@inproceedings {24671,
	title = {Ventricular Shape Correlates to Arrhythmic Events in ARVC Patients},
	journal = {American Heart Association Scientific Sessions },
	year = {2016},
	publisher = {AHA},
	author = {Kristin Sarah {Mcleod} and Wall, Samuel and Ida Skrinde {Leren} and Saberniak, J{\o}rg and Haugaa, Kristina}
}
@article {24844,
	title = {Ventricular structure in ARVC: Going beyond volumes as a measure of risk},
	journal = {Journal of Cardiovascular Magnetic Resonance},
	volume = {18},
	number = {1},
	year = {2016},
	pages = {73},
	publisher = {BioMed Central},
	abstract = {Background: Altered right ventricular structure is an important feature of Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC), but is challenging to quantify objectively. The aim of this study was to go beyond ventricular volumes and diameters and to explore if the shape of the right and left ventricles could be assessed and related to clinical measures. We used quantifiable computational methods to automatically identify and analyse malformations in ARVC patients from Cardiovascular Magnetic Resonance (CMR) images. Furthermore, we investigated how automatically extracted structural features were related to arrhythmic events.Methods: A retrospective cross-sectional feasibility study was performed on CMR short axis cine images of 27 ARVC patients and 21 ageing asymptomatic control subjects. All images were segmented at the end-diastolic (ED) and end-systolic (ES) phases of the cardiac cycle to create three-dimensional (3D) bi-ventricle shape models for each subject. The most common components to single- and bi-ventricular shape in the ARVC population were identified and compared to those obtained from the control group. The correlations were calculated between identified ARVC shapes and parameters from the 2010 Task Force Criteria, in addition to clinical outcomes such as ventricular arrhythmias.Results: Bi-ventricle shape for the ARVC population showed, as ordered by prevalence with the percent of total variance in the population explained by each shape: global dilation/shrinking of both ventricles (44\%), elongation/shortening at the right ventricle (RV) outflow tract (15\%), tilting at the septum (10\%), shortening/lengthening of both ventricles (7\%), and bulging/shortening at both the RV inflow and outflow (5\%). Bi-ventricle shapes were significantly correlated to several clinical diagnostic parameters and outcomes, including (but not limited to) correlations between global dilation and electrocardiography (ECG) major criteria (p=0.002), and base-to-apex lengthening and history of arrhythmias (p=0.003). Classification of ARVC vs. control using shape modes yielded high sensitivity (96\%) and moderate specificity (81\%).Conclusion: We presented for the first time an automatic method for quantifying and analysing ventricular shapes in ARVC patients from CMR images. Specific ventricular shape features were highly correlated with diagnostic indices in ARVC patients and yielded high classification sensitivity. Ventricular shape analysis may be a novel approach to classify ARVC disease, and may be used in diagnosis and in risk stratification for ventricular arrhythmias.},
	keywords = {ARVC, CMR, principal component analysis, risk assessment, shape modes},
	doi = {10.1186/s12968-016-0291-9},
	url = {http://rdcu.be/lvLr},
	author = {Kristin Sarah {Mcleod} and Wall, Samuel and Ida Skrinde {Leren} and Saberniak, J{\"o}rg and Haugaa, Kristina}
}
@inproceedings {23665,
	title = {A Computational Method for Determining Left Ventricular Diastolic Fiber Strain Relative to a Zero Pressure Geometry},
	journal = {USART Workshop},
	year = {2015},
	month = {09/2015},
	abstract = {Abnormal cardiac fiber stretching has been shown to berelated to the formation of arrhythmias. In this work weestimate this stretching relative to a pressure free state usinga finite element model that has been calibrated to strain andpressure measurements in late diastole.},
	keywords = {Cardiac Mechanics, Fiber Strain, Optimization},
	author = {Balaban, Gabriel and Wall, Samuel}
}
@misc {23710,
	title = {Computational models of electro-mechanical interactions in the heart},
	howpublished = {University of Uppsala},
	year = {2015},
	author = {Sundnes, Joakim and Sjur Urdson {Gjerald} and Wall, Samuel}
}
@misc {23855,
	title = {Dyssynchronous Left Ventricular Stress Estimation},
	howpublished = {Workshop on Advanced Numerical Techniques in Biomedical Computing: Simula Research Laboratory},
	year = {2015},
	abstract = {The heart is a muscular pump that moves approximatly 8,000 litres per day through the human body. It manages to this by a combination of contraction/relaxation along muscle fibers and elastic recoil. These two effects are indistinguishable in a medical image, but can be estimated using a computational model.In our work we use adjoint based optimization techniques in order to determine muscle contraction and elastic recoil in a patient specific left ventricular geometry based on echocardiography and pressure catheter data. Possible applications of the technique include mechanical stress estimation and hypothesis testing in cardiac resynchronization therapy research.},
	author = {Balaban, Gabriel},
	editor = {Finsberg, Henrik and Marie E. {Rognes} and Sundnes, Joakim and Wall, Samuel and Hans Henrik {Odland} and Ross, Stian}
}
@inproceedings {23822,
	title = {Fast Sweeping vs. Fast Marching for Eikonal Methods of Electrophysiology - A Potential for Significantly More Efficient Computation?},
	journal = {Cardiac Physiome Workshop, Auckland, New Zealand},
	year = {2015},
	note = {Cardiac Physiome Workshop, Auckland, New Zealand, April 2015. Poster Presentation by K. McLeod.},
	month = {04/2015},
	type = {Conference Abstract},
	author = {Kristin Sarah {Mcleod} and Wall, Samuel and Noack, Marcus}
}
@misc {23792,
	title = {Fast Sweeping vs. Fast Marching for Elkonal Methods of Electrophysiology - A Potential for Significantly More Efficient Computation?},
	year = {2015},
	author = {McLeod, Kristin and Wall, Samuel and Noack, Marcus}
}
@article {Simula.simula.2704,
	title = {Increased Membrane Capacitance Is the Dominant Mechanism of Stretch-Dependent Conduction Slowing in the Rabbit Heart: a Computational Study},
	journal = {Cellular and Molecular Bioengineering},
	volume = {8},
	year = {2015},
	pages = {237-246},
	publisher = { },
	abstract = {Volume loading of the cardiac ventricles is known to slow electrical conduction in the rabbit heart, but the mech- anisms remain unclear. Previous experimental and modeling studies have investigated some of these mechanisms, including stretch-activated membrane currents, reduced gap junctional conductance, and altered cell membrane capacitance. In order to quantify the relative contributions of these mechanisms, we combined a monomain model of rabbit ventricular electrophysiology with a hyperelastic model of passive ventricular mechanics. After a simplied geometric model with prescribed homogeneous deformation had been used to t model parameters and charcterize individual MEF mechanisms, a 3D model of the rabbit left and right ventricles was compared with experimental measurements from optical electrical mapping studies in the isolated rabbit heart. The model was in ated to an end-diastolic pressure of 30 mmHg, resulting in epicardial strains comparable to those measured in the anterior left ventricular free wall. While the e ects of stretch activated channels did alter epicardial conduction velocity, an increase in cellular capacitance was required to explain previously reported experimental results. The new results suggest that for large strains, various mechanisms can combine and produce a biphasic relationship between strain and conduction velocity. However, at the moderate strains generated by high end-diastolic pressure, a stretch- induced increase in myocyte membrane capacitance is the dominant driver of conduction slowing during ventricular volume loading.},
	author = {Bernardo Lino {de Oliveira} and Sundnes, Joakim and Wall, Samuel and Andrew D. {McCulloch}}
}
@article {23708,
	title = {An integrated electromechanical-growth heart model for simulating cardiac therapies},
	journal = {Biomechanics and Modeling in Mechanobiology},
	volume = {15},
	year = {2015},
	pages = {791-803},
	publisher = {Springer Berlin Heidelberg},
	author = {Lik Chuan {Lee} and Sundnes, Joakim and Genet, Martin and Jonathan F {Wenk} and Wall, Samuel}
}
@inproceedings {7391416,
	title = {Localization and not extent of fibrofatty infiltratio is the primary factor determining conduction disturbance in a computational model of arrhythmogenic cardiomyopathy},
	journal = {2015 E-Health and Bioengineering Conference (EHB)},
	year = {2015},
	month = {Nov},
	pages = {1-6},
	publisher = {ACM IEEE},
	keywords = {action potential, activation sites, arrhythmogenic cardiomyopathy, bioelectric potentials, biological tissues, biomedical MRI, biomembranes, cardiovascular system, cellular biophysics, computational model, Computational modeling, conduction disturbance, conduction properties, disease progression, diseases, electrophysiology, fibrofatty diseased tissue location, fibrofatty infiltration localization, fibrofatty patterns, fibrofatty region, Geometry, global conduction velocity, Heart, human electrophysiology, intercellular junctions, Junctions, Magnetic resonance imaging, Morphology, nonviable tissue, organ-level model, passive membrane, patient heart geometry, physiological models},
	doi = {10.1109/EHB.2015.7391416},
	author = {Kallhovd, Siri and S. U. {Gjerald} and Wall, Samuel and Saberniak, J. and Haugaa, K. and Maleckar, Molly}
}
@article {23718,
	title = {Mathematical Modeling of ST-shifts during Ischemia in the Anisotropic Heart},
	journal = {IEEE - Transactions on Biomedical Engineering},
	year = {2015},
	publisher = {IEEE},
	author = {Ola Marius {Lysaker} and Nielsen, Bj{\o}rn Fredrik and Wall, Samuel}
}
@misc {23711,
	title = {Mechano-electric feedback as a source of ectopic activity},
	howpublished = {Gordon Research Conference on Arrhythmia Mechanisms, Lucca, Italy},
	year = {2015},
	month = {03/2015},
	address = {Gordon Research Conference on Arrhythmia Mechanisms, Lucca, Italy},
	author = {Sundnes, Joakim and Wall, Samuel and Timmermann, Viviane and Tveito, Aslak}
}
@misc {23812,
	title = {Modeling growth and remodeling in heart muscle tissue},
	howpublished = {SIAM Conference on Computational Science and Engineering},
	year = {2015},
	type = {Minisymposium },
	author = {Sundnes, Joakim and Wall, Samuel}
}
@inproceedings {23709,
	title = {Patient{\textendash}Specific Parameter Estimation for a Transversely Isotropic Active Strain Model of Left Ventricular Mechanics},
	journal = {Statistical Atlases and Computational Models of the Heart-Imaging and Modelling Challenges},
	year = {2015},
	pages = {93-104},
	publisher = {Springer International Publishing},
	author = {Sjur Urdson {Gjerald} and Johan Elon {Hake} and Pezzuto, Simone and Sundnes, Joakim and Wall, Samuel}
}
@inproceedings {23720,
	title = {Personalization of a Cardiac Compuational Model using Clinical Measurements},
	journal = {28th Nordic Seminar on Computational Mechanics},
	volume = {28},
	year = {2015},
	month = {10/2015},
	pages = {47-50},
	publisher = {Proceedings of NSCM-28},
	address = {Tallin, Estonia},
	abstract = {Important features in cardiac mechanics that cannot easily be measured in the clinic, can be computed using a computational model that is calibrated to behave in the same way as a patient{\textquoteright}s heart. To construct such a model, clinical measurements such as strain, volume and cavity pressure are used to personalize the mechanics of a cardiac computational model. The problem is formulated as a PDE-constrained optimization problem where the minimization functional represents the misfit between the measured and simulated data. The target parameters are material parameters and a spatially varying contraction parameter. The minimization is carried out using a gradient based optimization algorithm and an automatically derived adjoint equation. The method has been tested on synthetic data, and is able to reproduce a prescribed contraction pattern on the left ventricle.},
	author = {Finsberg, Henrik and Balaban, Gabriel and Sundnes, Joakim and Marie E. {Rognes} and Wall, Samuel}
}
@misc {23937,
	title = {Significance of passive material parameters in mechanical models of the heart},
	howpublished = {Lugano, Switzerland},
	year = {2015},
	type = {Conference presentation at MALT 2015 },
	abstract = {Significance of passive material parameters in mechanicalmodels of the heart},
	author = {Kallhovd, Siri and Sundnes, Joakim and Wall, Samuel}
}
@inproceedings {23821,
	title = {Statistical Analysis of Ventricular Shape of ARVC Patients and Correlation with Clinical Diagnostic Indices.},
	journal = {Journal of Cardiovascular Magnetic Resonance 2015, 18th Annual SCMR Scientific Sessions},
	volume = {17},
	year = {2015},
	note = {SCMR Conference, Nice, France, February 2015.\&nbsp;Poster Presentation by K. McLeod.},
	month = {02/2015},
	pages = {283},
	edition = {Supp 1},
	doi = {10.1186/1532-429X-17-S1-P283},
	url = {http://www.biomedcentral.com/content/pdf/1532-429X-17-S1-P283.pdf},
	author = {Kristin Sarah {Mcleod} and Wall, Samuel and Saberniak, J{\"o}rg and Haugaa, Kristina}
}
@inproceedings {23824,
	title = {Statistical Analysis of Ventricular Shape of ARVC Patients and Correlation with Clinical Diagnostic Indices.},
	journal = {The 7th National PhD Conference in Medical Imaging},
	volume = {1},
	year = {2015},
	note = {MedIM Conference, Fornebu, Norway, November 2015. Poster Presentation by K. McLeod.
},
	month = {11/2015},
	author = {Kristin Sarah {Mcleod} and T{\o}ndel, Kristin and Wall, Samuel and Saberniak, J{\"o}rg and Haugaa, Kristina}
}
@inproceedings {Simula.simula.3024,
	title = {Bidomain Simulations of Subendocardial Ischemia: the Forward and Inverse Problems},
	journal = {Computing in Cardiology Conference},
	volume = {41},
	year = {2014},
	pages = {1149 - 1152 },
	publisher = {IEEE},
	type = {1},
	abstract = {We provide an analysis of the bidomain theory in relation to anterior subendocardial ischemia. Using the static bidomain model, this analysis explains why simulations often do not produce ST depression when the ischemia is introduced into an anisotropic model. More precisely, if the ischemic border zone is represented as a smooth surface, then almost right angles between the normal vector of the border and the tangential plane of the fibers will lead to cancelling effects. The simulated transmembrane current flux, entering the ischemic region, will thus be underestimated, and the expected ST depression in chest leads may not occur.},
	isbn = {978-1-4799-4346-3 },
	issn = {2325-8861 },
	author = {Ola Marius {Lysaker} and Nielsen, Bj{\o}rn Fredrik and Wall, Samuel},
	editor = {Murray, Alan}
}
@article {Lee20143115,
	title = {Bioinjection treatment: Effects of post-injection residual stress on left ventricular wall stress},
	journal = {Journal of Biomechanics},
	volume = {47},
	year = {2014},
	pages = {3115 - 3119},
	publisher = {Elsevier},
	abstract = {Injection of biomaterials into diseased myocardium has been associated with decreased myofiber stress, restored left ventricular (LV) geometry and improved \{LV\} function. However, its exact mechanism(s) of action remained unclear. In this work, we present the first patient-specific computational model of biomaterial injection that accounts for the possibility of residual strain and stress introduced by this treatment. We show that the presence of residual stress can create more heterogeneous regional myofiber stress and strain fields. Our simulation results show that the treatment generates low stress and stretch areas between injection sites, and high stress and stretch areas between the injections and both the endocardium and epicardium. Globally, these local changes are translated into an increase in average myofiber stress and its standard deviation (from 6.9{\textpm}4.6 to 11.2{\textpm}48.8 kPa and 30{\textpm}15 to 35.1{\textpm}50.9 kPa at end-diastole and end-systole, respectively). We also show that the myofiber stress field is sensitive to the void-to-size ratio. For a constant void size, the myofiber stress field became less heterogeneous with decreasing injection volume. These results suggest that the residual stress and strain possibly generated by biomaterial injection treatment can have large effects on the regional myocardial stress and strain fields, which may be important in the remodeling process.},
	doi = {http://dx.doi.org/10.1016/j.jbiomech.2014.06.026},
	url = {http://www.sciencedirect.com/science/article/pii/S0021929014003650},
	author = {Lik Chuan {Lee} and Wall, Samuel and Genet, Martin and Hinson, Andy and Julius M. {Guccione}}
}
@misc {Simula.simula.3020,
	title = {Computational Models of Electro-Mechanical Interactions in the Heart},
	howpublished = {Invited mini symposium presentation at the European Conference for Mathematics in Industry, Taormina, Italy.},
	year = {2014},
	month = {June},
	keywords = {Conference},
	author = {Sundnes, Joakim and Wall, Samuel and Pezzuto, Simone and Johan Elon {Hake} and Bernardo Lino {de Oliveira}}
}
@misc {23368,
	title = {A generic right ventricle model for simulating patient-specific pacing procedures from echocardiography data},
	howpublished = {Workshop on Models for surgical decision support at VPH2014 in Trondheim},
	year = {2014},
	author = {Sjur Urdson {Gjerald} and Sarvari, S. and Hans Henrik {Odland} and Wall, Samuel}
}
@article {Simula.simula.1594,
	title = {Improved Discretisation and Linearisation of Active Tension in Strongly Coupled Cardiac Electro-Mechanics Simulations},
	journal = {Computer Methods in Biomechanics and Biomedical Engineering},
	volume = {17},
	number = {6},
	year = {2014},
	pages = {604-15},
	publisher = { },
	abstract = {Mathematical models of cardiac electro-mechanics typically consist of three tightly coupled parts: systems of ordinary differential equations describing electro-chemical reactions and cross-bridge dynamics in the muscle cells, a system of partial differential equations modelling the propagation of the electrical activation through the tissue and a nonlinear elasticity problem describing the mechanical deformations of the heart muscle. The complexity of the mathematical model motivates numerical methods based on operator splitting, but simple explicit splitting schemes have been shown to give severe stability problems for realistic models of cardiac electro-mechanical coupling. The stability may be improved by adopting semi-implicit schemes, but these give rise to challenges in updating and linearising the active tension. In this paper we present an operator splitting framework for strongly coupled electro-mechanical simulations and discuss alternative strategies for updating and linearising the active stress component. Numerical experiments demonstrate considerable performance increases from an update method based on a generalised Rush-Larsen scheme and a consistent linearisation of active stress based on the first elasticity tensor.},
	author = {Sundnes, Joakim and Wall, Samuel and Osnes, Harald and Thorvaldsen, Tom and Andrew D. {McCulloch}}
}
@inproceedings {19099,
	title = {Metamodelling of Structural Abnormalities in the ARVC Heart},
	journal = {VPH conference workshop on Metamodelling methodology for easing model construction and validation},
	year = {2014},
	publisher = { },
	author = {Kristin Sarah {Mcleod} and T{\o}ndel, Kristin and Wall, Samuel and Saberniak, J{\o}rg}
}
@misc {Simula.simula.3018,
	title = {Patient Specific Models of Cardiac Electro-Mechanics},
	howpublished = {Seminar at Ecole des Mines, St Etienne, France},
	year = {2014},
	month = {February},
	author = {Sundnes, Joakim and Wall, Samuel and Sjur Urdson {Gjerald} and Johan Elon {Hake} and Bernardo Lino {de Oliveira}}
}
@inbook {gjerald2014patient,
	title = {Patient{\textendash}Specific Parameter Estimation for a Transversely Isotropic Active Strain Model of Left Ventricular Mechanics},
	booktitle = {Lecture Notes in Computer Science},
	volume = {8896},
	year = {2014},
	pages = {93{\textendash}104},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	author = {Sjur Urdson {Gjerald} and Johan Elon {Hake} and Pezzuto, Simone and Sundnes, Joakim and Wall, Samuel}
}
@article {Simula.simula.2238,
	title = {Algisyl-LVR With Coronary Artery Bypass Grafting Reduces Left Ventricular Wall Stress and Improves Function in the Failing Human Heart},
	journal = {International Journal of Cardiology},
	volume = {168},
	number = {3},
	year = {2013},
	month = {October},
	pages = {2022-2028},
	keywords = {Workshop},
	author = {Lik Chuan {Lee} and Wall, Samuel and Klepach, Doron and Ge, Liang and Zhang, Zhihong and Lee, Randall and Hinson, Andy and Joseph H. {Gorman} and Gorman, Robert and Guccione, Julius}
}
@misc {Simula.simula.2698,
	title = {Cardiac Modelling and Applications},
	howpublished = {INRIA Sophia Antipolis},
	year = {2013},
	author = {Wall, Samuel}
}
@misc {Simula.simula.2706,
	title = {Computational Models of Electro-Mechanical Interactions in the Heart},
	howpublished = {SIAM conference on computational science and engineering, Boston},
	year = {2013},
	month = {February},
	keywords = {Conference},
	author = {Sundnes, Joakim and Wall, Samuel}
}
@misc {Simula.simula.2156,
	title = {Computing Ischemic Regions in the Heart: on the Use of Internal Electrodes},
	howpublished = {Computing in Cardiology},
	year = {2013},
	month = {September 22-25},
	author = {Ola Marius {Lysaker} and Nielsen, Bj{\o}rn Fredrik and Wall, Samuel}
}
@inproceedings {Simula.simula.2158,
	title = {Computing Ischemic Regions in the Heart: on the Use of Internal Electrodes},
	journal = {Computing in Cardiology Conference (CinC)},
	year = {2013},
	pages = {675-678},
	publisher = {IEEE},
	type = {1},
	author = {Ola Marius {Lysaker} and Nielsen, Bj{\o}rn Fredrik and Wall, Samuel},
	editor = {Murray, Alan}
}
@misc {Simula.simula.2694,
	title = {The Effects of Mechanoelectrical Feedback on Conduction Velocity: a Computational Study},
	year = {2013},
	publisher = {Cardiac Physiome Workshop},
	abstract = {Mechanical deformation is know to have an influence on the velocity of the electrical conduction in cardiac tissue. Several experimental and computational studies have investigated this and a wide variety of different strain-conduction velocity relationships have been reported. In short, there are increasing, decreasing, constant and biphasic relationships reported. The objective of this study is to develop a computational model that includes multiple mechanoelectrical feedback mechanisms and is capable of reproducing the different strain-conduction velocity relationships reported.},
	author = {Bernardo Lino {de Oliveira} and Wall, Samuel and Sundnes, Joakim}
}
@misc {Simula.simula.2696,
	title = {Evaluation of Cardiac Tissue Engineering Applications Using Strongly Coupled Electromechanical Models of the Left Ventricle},
	howpublished = {Computer Methods in Biomechanics and Biomedical Engineering, Utah},
	year = {2013},
	keywords = {Internal Seminar, University of Oslo},
	author = {Wall, Samuel and Sundnes, Joakim and Guccione, Julius}
}
@misc {Simula.simula.2578,
	title = {Patient-Specific Models of Cardiac Electro-Mechanics},
	howpublished = {Federal University of Juiz de Fora},
	year = {2013},
	month = {October},
	author = {Sundnes, Joakim and Wall, Samuel and Sjur Urdson {Gjerald} and Johan Elon {Hake} and Bernardo Lino {de Oliveira}}
}
@misc {Simula.simula.2700,
	title = {Strongly Coupled Electromechanical Models of the Heart},
	howpublished = {Biomechanics and Medical Imaging Mini-Symposium, UCSF},
	year = {2013},
	keywords = {Conference},
	author = {Wall, Samuel and Sundnes, Joakim}
}
@misc {Simula.simula.1620,
	title = {Computational Models of Electro-Mechanical Interactions in the Infarct Injured Heart},
	howpublished = {National PhD conference in medical Imaging, Trondheim, Norway},
	year = {2012},
	author = {Sundnes, Joakim and Wall, Samuel}
}
@misc {Simula.simula.1614,
	title = {Computer Models of Electro-Mechanical Interactions in the Contracting Heart},
	howpublished = {Seminar at the Norwegian Defence Research Establishment},
	year = {2012},
	month = {September},
	author = {Sundnes, Joakim and Wall, Samuel}
}
@misc {Simula.simula.1610,
	title = {Computer Models of Electro-Mechanical Interactions in the Contracting Heart},
	howpublished = {Workshop on computational models in biomedicine, Federal University of Juiz de Fora, Brazil},
	year = {2012},
	month = {July},
	author = {Sundnes, Joakim and Wall, Samuel}
}
@misc {Simula.simula.1606,
	title = {Computer Simulations of Electro-Mechanical Interactions in the Heart},
	howpublished = {CBC Workshop on Adjoint-Based Methods for Transient Problems: Software and Applications},
	year = {2012},
	month = {March},
	author = {Sundnes, Joakim and Wall, Samuel}
}
@article {Simula.simula.544,
	title = {Electromechanical Feedback With Reduced Cellular Connectivity Alters Electrical Activity in an Infarct Injured Left Ventricle - a Finite Element Model Study},
	journal = {American Journal of Physiology - Heart and Circulatory Physiology},
	number = {302},
	year = {2012},
	month = {Jan},
	pages = {H206-H214},
	abstract = {Myocardial infarction (MI) significantly alters the structure and function of the heart. As abnormal strain may drive heart failure and the generation of arrhythmias, we used computational methods to simulate a left ventricle with an MI over the course of a heartbeat to investigate strains and their potential implications to electrophysiology. We created a fully coupled finite element model of myocardial electromechanics consisting of a cellular physiological model, a bidomain electrical diffusion solver, and a nonlinear mechanics solver. A geometric mesh built from magnetic resonance imaging (MRI) measurements of an ovine left ventricle suffering from a surgically induced anteroapical infarct was used in the model, cycled through the cardiac loop of inflation, isovolumic contraction, ejection, and isovolumic relaxation. Stretch-activated currents were added as a mechanism of mechanoelectric feedback. Elevated fiber and cross fiber strains were observed in the area immediately adjacent to the aneurysm throughout the cardiac cycle, with a more dramatic increase in cross fiber strain than fiber strain. Stretch-activated channels decreased action potential (AP) dispersion in the remote myocardium while increasing it in the border zone. Decreases in electrical connectivity dramatically increased the changes in AP dispersion. The role of cross fiber strain in MI-injured hearts should be investigated more closely, since results indicate that these are more highly elevated than fiber strain in the border of the infarct. Decreases in connectivity may play an important role in the development of altered electrophysiology in the high-stretch regions of the heart.},
	keywords = {Workshop},
	doi = {10.1152/ajpheart.00272.2011},
	author = {Wall, Samuel and Guccione, Julius and Ratcliffe, Mark and Sundnes, Joakim}
}
@misc {Simula.simula.2192,
	title = {Impact of Mechanical Deformation on Conduction Velocity of Cardiac Tissue},
	howpublished = {World Congress on Computational Mechanics},
	year = {2012},
	abstract = {Impact of mechanical deformation on conduction velocity of cardiac tissue The heart is an electromechanical pump responsible of circulating blood in the body. The contraction of the heart is initiated by an electrical wave which spreads through the tissue. This stimulus triggers a chain of reactions that generates active force and consequently contraction, the so-called excitation-contraction coupling. However, there are several feedback loops that enable mechanical deformation to regulate the electrical activity, commonly referred to as mechano-electric feedback. Some examples of these mechanisms are deformation dependent conductivities, length and tension dependent binding rates, and stretch-activation channels, among others. The relevance of each of these mechanisms and the relationships between them are still poorly understood and need to be further investigated. Computational models that account both excitation-contraction and mechano-electric feedback are called strongly coupled models. These models are very complex and have already demonstrated to be an important tool to test new hypothesis and enhance understanding. Studies have investigated the relations between mechanical deformation and changes on electrical conduction velocity on mammalian ventricles. Some models try to mimic this effect by including deformation dependent conductivity, but, there is no detailed experimental data to support these assumptions. In this work a strongly coupled cardiac electromechanics simulation framework was developed, based on bidomain equations and large deformation theory. The simulations were used to compare different approaches and develop a model capable of better representing the dependency of conduction velocity on mechanical deformation that was reported in recent experimental studies.},
	keywords = {Conference},
	author = {Bernardo Lino {de Oliveira} and Wall, Samuel and Sundnes, Joakim}
}
@misc {Simula.simula.2194,
	title = {Multiple Mechanoelectrical Feedback Mechanisms Affect Conduction Velocity},
	howpublished = {CaMo/CMRG Workshop, San Diego},
	year = {2012},
	abstract = {Mechanical deformation is know to have an influence on the velocity of the electrical conduction in cardiac tissue. Although this is an acknowledged phenomenon, there is still controversy with respect to the underlying biophysical mechanisms. Several experimental and computational studies have investigated this and a wide variety of different strain-conduction velocity relationships have been reported. In short, there are increasing, decreasing, constant and biphasic relationships reported. The objective of this study is to develop a computational model that includes multiple mechanoelectrical feedback mechanisms and is capable of reproducing different strain-conduction velocity relationships reported on experiments.},
	author = {Bernardo Lino {de Oliveira} and Wall, Samuel and Sundnes, Joakim}
}
@misc {Simula.simula.2702,
	title = {Multiple Mechanoelectrical Feedback Mechanisms Affect Conduction Velocity},
	year = {2012},
	publisher = {Cardiac Physiome Workshop},
	abstract = {Mechanical deformation is know to have an influence on the velocity of the electrical conduction in cardiac tissue. Although this is an acknowledged phenomenon, there is still controversy with respect to the underlying biophysical mechanisms. Several experimental and computational studies have investigated this and a wide variety of different strain-conduction velocity relationships have been reported. In short, there are increasing, decreasing, constant and biphasic relationships reported. The objective of this study is to develop a computational model that includes multiple mechanoelectrical feedback mechanisms and is capable of reproducing different strain-conduction velocity relationships reported on experiments.},
	author = {Bernardo Lino {de Oliveira} and Wall, Samuel and Sundnes, Joakim}
}
@misc {Simula.simula.1608,
	title = {Numerical Methods for Strongly Coupled Simulations of Cardiac Electro-Mechanics},
	howpublished = {Workshop on efficient solvers in biomedical applications, Graz, Austria},
	year = {2012},
	month = {July},
	author = {Sundnes, Joakim and Wall, Samuel}
}
@misc {Simula.simula.1612,
	title = {On the Stability of Operator Splitting Schemes for Strongly Coupled Cardiac Electro-Mechanics},
	howpublished = {World Congress on Computational Mechanics, Sao Paulo, Brazil},
	year = {2012},
	month = {July},
	author = {Sundnes, Joakim and Wall, Samuel}
}
@misc {Simula.simula.1618,
	title = {Strongly Coupled Simulations of Cardiac Electro-Mechanics},
	howpublished = {CBC seminar},
	year = {2012},
	month = {November},
	author = {Sundnes, Joakim and Wall, Samuel}
}
@misc {Simula.simula.1616,
	title = {Towards Patient-Specific Models of Strongly Coupled Cardiac Electro-Mechanics},
	howpublished = {Cardiac Physiome Workshop, San Diego},
	year = {2012},
	month = {November},
	author = {Sundnes, Joakim and Wall, Samuel and Sjur Urdson {Gjerald}}
}
@misc {Simula.simula.550,
	title = {Modeling the Infarct Injured Heart, Insights Into Mechanical Dysfunction},
	howpublished = {SIAM CSE Reno, Nevada, USA},
	year = {2011},
	author = {Wall, Samuel}
}
@misc {Simula.simula.1202,
	title = {Multi-Scale Modeling of the Heart - Computational Approaches and Applications to Biomedicine},
	howpublished = {Scientific Computing and Imaging Institute, University of Utah,},
	year = {2011},
	month = {July},
	author = {Wall, Samuel}
}
@misc {Simula.simula.1602,
	title = {Strongly Coupled Electro-Mechanics Simulations of the Infarct Injured Heart},
	howpublished = {International Conference on Numerical Methods and Applied Mathematics, Greece},
	year = {2011},
	month = {September},
	author = {Sundnes, Joakim and Wall, Samuel}
}
@misc {Simula.simula.1598,
	title = {Strongly Coupled Electro-Mechanics Simulations of the Infarct Injured Heart},
	howpublished = {Workshop on cardiac modeling, Federal University of Juiz de Fora, Brazil},
	year = {2011},
	month = {January},
	keywords = {Conference},
	author = {Sundnes, Joakim and Wall, Samuel}
}
@misc {Simula.simula.1600,
	title = {Strongly Coupled Electro-Mechanics Simulations of the Infarct Injured Heart},
	howpublished = {Computational Science Seminar, University of Basel, Switzerland},
	year = {2011},
	author = {Sundnes, Joakim and Wall, Samuel}
}
@misc {Simula.simula.296,
	title = {Basic Electromechanical Simulations},
	howpublished = {CBC Seminar Series on Computational Cardiac Modeling},
	year = {2010},
	author = {Wall, Samuel}
}
@article {Simula.simula.556,
	title = {Biomimetic Extracellular Matrices for Stem Cell Transplantation and Myocardial Stabilization},
	journal = {Journal of Biomedical Material Research, Part A},
	volume = {95A},
	number = {4},
	year = {2010},
	pages = {1055-1066},
	publisher = {John Wiley \& Sons},
	author = {Wall, Samuel and Yeh, Che-Chung and Tu, Richard and Mann, Michael and Healy, Kevin}
}
@article {Simula.simula.560,
	title = {Effect of Adjustable Passive Constraint on the Failing Left Ventricle: a Finite-Element Model Study},
	journal = {Annals of Thoracic Surgery},
	volume = {89},
	number = {1},
	year = {2010},
	pages = {132-138},
	publisher = {PubMed Central},
	doi = {10.1016/j.athoracsur.2009.08.075},
	author = {Choon-Sik, Jhun and Wenk, Jonathan and Zhang, Zhihong and Wall, Samuel and Sun, Kay and Sabbah, Hani and Ratcliffe, Mark and Guccione, Julius}
}
@inbook {Simula.simula.546,
	title = {Left Ventricular Implantation of Biomaterials},
	booktitle = {Computational Cardiovascular Mechanics - Modeling and Applications in Heart Failure},
	year = {2010},
	pages = {227-239},
	publisher = {Springer},
	organization = {Springer},
	chapter = {14},
	isbn = {978-1-4419-0729-5},
	author = {Wall, Samuel and Wenk, Johnathan and Jhun, Choon-Sik and Guccione, Julius},
	editor = {Julius M. {Guccione} and Ghassan S. {Kassab} and Mark B. {Ratcliffe}}
}
@misc {Simula.sc.712,
	title = {Computer Modeling of Cardiac Electro-Mechanics - Models and Numerical Methods},
	howpublished = {Talk at Cardiac Modeling seminar, Simula Research Laboratory},
	year = {2009},
	month = {February},
	author = {Sundnes, Joakim and Wall, Samuel and Osnes, Harald}
}
@misc {Simula.simula.552,
	title = {Computer Modeling of Electro-Mechanics, Applications to Acute Myocardial Infarctions and Heart Failure},
	howpublished = {Simula Mini-symposium},
	year = {2009},
	author = {Wall, Samuel}
}
@misc {Simula.simula.562,
	title = {Electromechanical Modeling of the Infarct Injured Failing Ovine Heart},
	year = {2009},
	author = {Wall, Samuel and Sundnes, Joakim and Ratcliffe, Mark and Guccione, Julius}
}
@article {Simula.simula.558,
	title = {A Method for Automatically Optimizing Medical Devices for Treating Heart Failure: Designing Polymeric Injection Patterns},
	journal = {Journal of Biomedical Engineering},
	volume = {131},
	number = {12},
	year = {2009},
	publisher = {American Society of Mechanical Engineers},
	author = {Wenk, Jonathan and Wall, Samuel and Peterson, Robert and Helgerson, Sam and Sabbah, Hani and Ratcliffe, Mark and Burger, Mike and Stander, Neil and Guccione, Julius}
}
@misc {Simula.sc.716,
	title = {Simulation of Strongly Coupled Electro-Mechanics in an Infarcted Left Ventricle},
	howpublished = {Invited talk at the workshop Bidomain 2009, University of Graz},
	year = {2009},
	author = {Sundnes, Joakim and Wall, Samuel and Osnes, Harald}
}
@article {Simula.simula.554,
	title = {Multivalency of Sonic Hedgehog Conjugated to Linear Polymer Chains Modulates Protein Potency},
	journal = {Bioconjugate Chemistry},
	volume = {19},
	number = {4},
	year = {2008},
	pages = {806-812},
	author = {Wall, Samuel and Saha, Kris and Schaffer, David and Healy, Kevin}
}
@article {Simula.SC.526,
	title = {Theoretical Impact of the Injection of Material Into the Myocardium - a Finite Element Model Simulation},
	journal = {Circulation},
	volume = {114},
	number = {24},
	year = {2006},
	month = {Dec},
	pages = {2627-2635},
	author = {Wall, Samuel and Walker, Joseph and Ratcliffe, Mark and Healy, Kevin and Guccione, Julius}
}
@article {doi:10.14814/phy2.13392,
	title = {Organ-level validation of a cross-bridge cycling descriptor in a left ventricular finite element model: effects of ventricular loading on myocardial strains},
	journal = {Physiological Reports},
	volume = {5},
	number = {21},
	pages = {e13392},
	publisher = { Wiley},
	abstract = {Abstract Although detailed cell-based descriptors of cross-bridge cycling have been applied in finite element (FE) heart models to describe ventricular mechanics, these multiscale models have never been tested rigorously to determine if these descriptors, when scaled up to the organ-level, are able to reproduce well-established organ-level physiological behaviors. To address this void, we here validate a left ventricular (LV) FE model that is driven by a cell-based cross-bridge cycling descriptor against key organ-level heart physiology. The LV FE model was coupled to a closed-loop lumped parameter circulatory model to simulate different ventricular loading conditions (preload and afterload) and contractilities. We show that our model is able to reproduce a linear end-systolic pressure volume relationship, a curvilinear end-diastolic pressure volume relationship and a linear relationship between myocardial oxygen consumption and pressure{\^a}volume area. We also show that the validated model can predict realistic LV strain-time profiles in the longitudinal, circumferential, and radial directions. The predicted strain-time profiles display key features that are consistent with those measured in humans, such as having similar peak strains, time-to-peak-strain, and a rapid change in strain during atrial contraction at late-diastole. Our model shows that the myocardial strains are sensitive to not only LV contractility, but also to the LV loading conditions, especially to a change in afterload. This result suggests that caution must be exercised when associating changes in myocardial strain with changes in LV contractility. The methodically validated multiscale model will be used in future studies to understand human heart diseases.},
	keywords = {Cardiac energetics, finite element modeling, left ventricle, myocardial strain},
	doi = {10.14814/phy2.13392},
	url = {https://physoc.onlinelibrary.wiley.com/doi/abs/10.14814/phy2.13392},
	author = {Sheikh Mohammad {Shavik} and Wall, Samuel and Sundnes, Joakim and Burkhoff, Daniel and Lik Chuan {Lee}}
}
