@article {ALBATAT2021104159,
	title = {Optimal pacing sites in cardiac resynchronization by left ventricular activation front analysis},
	journal = {Computers in Biology and Medicine},
	volume = {128},
	year = {2021},
	pages = {104159},
	publisher = {Elsevier},
	abstract = {Cardiac resynchronization therapy (CRT) can substantially improve dyssynchronous heart failure and reduce mortality. However, about one-third of patients who are implanted, derive no measurable benefit from CRT. Non-response may partly be due to suboptimal activation of the left ventricle (LV) caused by electrophysiological heterogeneities. The goal of this study is to investigate the performance of a newly developed method used to analyze electrical wavefront propagation in a heart model including myocardial scar and compare this to clinical benchmark studies. We used computational models to measure the maximum activation front (MAF) in the LV during different pacing scenarios. Different heart geometries and scars were created based on cardiac MR images of three patients. The right ventricle (RV) was paced from the apex and the LV was paced from 12 different sites, single site, dual-site and triple site. Our results showed that for single LV site pacing, the pacing site with the largest MAF corresponded with the latest activated regions of the LV demonstrated during RV pacing, which also agrees with previous markers used for predicting optimal single-site pacing location. We then demonstrated the utility of MAF in predicting optimal electrode placements in more complex scenarios including scar and multi-site LV pacing. This study demonstrates the potential value of computational simulations in understanding and planning CRT.},
	keywords = {Cardiac resynchronization therapy, Cardiology, Computational modeling, electrophysiology, Heart failure},
	issn = {0010-4825},
	doi = {https://doi.org/10.1016/j.compbiomed.2020.104159},
	url = {http://www.sciencedirect.com/science/article/pii/S001048252030490X},
	author = {Albatat, Mohammad and Arevalo, Hermenegild and Bergsland, Jacob and Str{\o}m, Vilde and Balasingham, Ilangko and Hans Henrik {Odland}}
}
@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 {27666,
	title = {Regional Left Ventricular Fiber Stress Analysis for Cardiac Resynchronization Therapy Response},
	journal = {Journal of Cardiovascular Electrophysiology},
	year = {2020},
	publisher = { Wiley},
	author = {Albatat, Mohammad and Finsberg, Henrik and Arevalo, Hermenegild and Sundnes, Joakim and Bergsland, Jacob and Balasingham, Ilangko and Hans Henrik {Odland}}
}
@article {25817,
	title = {A Centerline Based Model Morphing Algorithm for Patient-Specific Finite Element Modelling of the Left Ventricle},
	journal = {IEEE Transactions on Biomedical Engineering},
	year = {2017},
	month = {09/2017},
	publisher = {IEEE},
	issn = {0018-9294},
	doi = {10.1109/TBME.2017.2754980},
	author = {Behdadfar, Sareh and Navarro, L. and Sundnes, Joakim and Maleckar, Molly and Ross, Stian and Hans Henrik {Odland} and Avril, S.}
}
@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}
}
@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}
}
@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 {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 {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}
}
