Towards predictive computer simulations in cardiology: Finite element analysis of personalized heart models

Cansız, Barış; Sveric, Krunoslav Michael; Ibrahim, Karim; Strasser, Ruth H.; Linke, Axel; Kaliske, Michael

doi:10.1002/zamm.201800055

Cited by 11 publications

(13 citation statements)

References 48 publications

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“…13. Similar to our previous works [5][6][7], before the final results are obtained, subsequent cycles are carried out until the value of the primary field variables becomes almost constant over the subsequent cycles. In all the simulations, the influence of the mechanical deformation on the source term is neglected withF φ m = 0 mV/ms for the sake of simplicity.…”

Section: Finite Element Simulations In a Personalized LV Modelmentioning

confidence: 98%

“…In this subsection, the performance of the proposed contraction model is demonstrated through several FE simulations in a personalized LV geometry that was generated from 4D echocardiography data [7]. The LV geometry is created at enddiastole and discretized by 18,809 four-node tetrahedral elements over 4116 nodes.…”

Section: Finite Element Simulations In a Personalized LV Modelmentioning

confidence: 99%

“…Regarding the boundary constraints, linear springs, which impose directional constraints, are attached to the nodes on the basal and epicardial surfaces. The stiffness values of the springs are adopted from our previous work [7] with a slight change in the k z value at the basal surface. Those stiffness values are applied to mimic physiological LV deformation patterns such as rotation, twist and longitudinal shortening.…”

Section: Finite Element Simulations In a Personalized LV Modelmentioning

confidence: 99%

“…In this paper, we contribute to the literature by elaborating novel phenomenological equations for intracellular calcium concentration (ICC) and myocardial shortening which are simple and straightforward to implement and, at the same time, enable us to mimic reality in an accurate way and perform efficient computer simulations of the virtual heart models. It should be noted that the equations for the ICC and myocardial contraction were first used by Cansız et al [5] and further adopted by Cansız et al [6,7] in order to describe myocardial contraction. However, a detailed investigation of the equations at the material and organ level will be carried out for the first time in this manuscript.…”

Section: Introductionmentioning

confidence: 99%

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A simple phenomenological approach for myocardial contraction: formulation, parameter sensitivity study and applications in organ level simulations

2021

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Contraction in myocardial tissue is the result of a complex process through which chemical energy on the cellular level is converted into the mechanical energy needed to circulate blood throughout the body. Due to its vital role for the organism, myocardial contractility is one of the most intensively investigated subjects in medical research. In this contribution, we suggest a novel phenomenological approach for myocardial contraction that is capable of producing realistic intracellular calcium concentration (ICC) and myocyte shortening graphs, can be easily calibrated to capture different ICC and contraction characteristics and, at the same time, is straightforward to implement and ensures efficient computer simulations. This study is inspired by the fact that existing models for myocardial contractility either contain a number of complex equations and material parameters, which reduce their feasibility, or are very simple and cannot accurately mimic reality, which eventually influences the realm of computer simulations. The proposed model in this manuscript considers first the evolution of the ICC through a logarithmic-type ordinary differential equation (ODE) having the normalized transmembrane potential as the argument. The ICC is further put into an exponential-type ODE which determines the shortening of the myocyte (active stretch). The developed approach can be incorporated with phenomenological or biophysically based models of cardiac electrophysiology. Through examples on the material level, we demonstrate that the shape of the ICC and myocardial shortening curves can be easily modified and accurately fitted to experimental data obtained from rat and mouse hearts. Moreover, the performance of the model in organ level simulations is illustrated through several multi-field initial-boundary value problems in which we show variations in volume-time relations, heterogeneous characteristics of myocardial contraction and application of a drug in a virtual left ventricle model.

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Section: Finite Element Simulations In a Personalized LV Modelmentioning

confidence: 98%

Section: Finite Element Simulations In a Personalized LV Modelmentioning

confidence: 99%

Section: Finite Element Simulations In a Personalized LV Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A simple phenomenological approach for myocardial contraction: formulation, parameter sensitivity study and applications in organ level simulations

2021

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“…Obvious examples for electroactive tissues are the heart and the stomach. [] and [] propose comprehensive computational models of the electromechanical coupling in these two organs. Although less visible than in the heart or stomach, biochemically controlled muscular contraction also plays an important role in arteries, for example, by regulating blood pressure or blood diffusion of organs.…”

mentioning

confidence: 99%

Preface of the special issue on mathematical and computational modeling in biomechanics

Holzapfel

Cyron

2018

Z Angew Math Mech

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Preface of the special issue on mathematical and computational modeling in biomechanicsBiomechanics is one of the fastest growing areas of mechanics research. While less than 1000 researchers participated in the 3 rd World Congress on Biomechanics in 1998, more than 4000 participants were counted at the 8 th World Congress on Biomechanics held in 2018 in Dublin, which makes biomechanics nowadays one of the largest research communities in the area of mechanics. The fast rising number of scientists working in biomechanics is in the first place the consequence of a change of paradigm that has taken place in life sciences mainly over the last three decades. For centuries, biochemistry was considered the primary subject area for understanding the functioning of living organisms. However, the recent rise of mechanobiology has revealed that many of the most fundamental mechanisms in living organisms are in fact not -or at least not exclusively -controlled biochemically but rather mechanically. Unraveling the role of mechanics in living organisms has proven to be highly rewarding but also highly challenging. In particular, due to ethical concerns and the inherent complexity of living organisms, experiments in biomechanics usually take much more time and resources than in classical mechanics. Mathematical and computational modeling can be the key for reducing experimental efforts. Developing and using this key can be expected to be one of the most promising areas of research for investigators in mechanics and applied mathematics over the next decades. This special issue in ZAMM seeks to cover the whole range of questions and problems in biomechanics from fundaments to clinical research.Given the above-mentioned key role of mechanobiology in the fast rise of biomechanics over the last decades, it is natural that many of the articles in this special issue focus specifically not only on mechanical aspects alone but rather on the interplay between mechanical and biological processes, that is, on mechanobiology in the broadest sense. In this special issue, the two probably most prominent sub-areas of mechanobiology are addressed, which are mechano-regulated growth and remodeling of biological tissues and electrophysiologically and biochemically controlled muscular contractions. Within the area of mechanoregulated growth and remodeling, the review article [1] focuses on the cellular and sub-cellular foundations, in particular on cellular mechanotransduction and contractility. These phenomena translate on the tissue scale into characteristic mechano-regulated growth and remodeling processes.[2] and [3] propose novel mathematical models for these processes in arteries. Such models always rely not only on information about the cellular foundations of mechanobiology but also on a detailed understanding of the mechanics of soft biological tissues, which is crucially governed by their fibrous microstructure. Understanding the role of this microstructure during macroscopic tissue deformations remains an ongoing area of research that i...

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Fast and reliable reduced‐order models for cardiac electrophysiology

Chellappa,

Cansız,

Feng

et al. 2023

GAMM-Mitteilungen

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Mathematical models of the human heart increasingly play a vital role in understanding the working mechanisms of the heart, both under healthy functioning and during disease. The ultimate aim is to aid medical practitioners diagnose and treat the many ailments affecting the heart. Towards this, modeling cardiac electrophysiology is crucial as the heart's electrical activity underlies the contraction mechanism and the resulting pumping action. Apart from modeling attempts, the pursuit of efficient, reliable, and fast solution algorithms has been of great importance in this context. The governing equations and the constitutive laws describing the electrical activity in the heart are coupled, nonlinear, and involve a fast moving wave front, which is generally solved by the finite element method. The numerical treatment of this complex system as part of a virtual heart model is challenging due to the necessity of fine spatial and temporal resolution of the domain. Therefore, efficient surrogate models are needed to predict the electrical activity in the heart under varying parameters and inputs much faster than the finely resolved models. In this work, we develop an adaptive, projection‐based reduced‐order surrogate model for cardiac electrophysiology. We introduce an a posteriori error estimator that can accurately and efficiently quantify the accuracy of the surrogate model. Using the error estimator, we systematically update our surrogate model through a greedy search of the parameter space. Furthermore, using the error estimator, the parameter search space is dynamically updated such that the most relevant samples get chosen at every iteration. The proposed adaptive surrogate model is tested on three benchmark models to illustrate its efficiency, accuracy, and ability of generalization.

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Towards predictive computer simulations in cardiology: Finite element analysis of personalized heart models

Cited by 11 publications

References 48 publications

A simple phenomenological approach for myocardial contraction: formulation, parameter sensitivity study and applications in organ level simulations

A simple phenomenological approach for myocardial contraction: formulation, parameter sensitivity study and applications in organ level simulations

Preface of the special issue on mathematical and computational modeling in biomechanics

Fast and reliable reduced‐order models for cardiac electrophysiology

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