Sensitivity of stress and strain calculations to passive material parameters in cardiac mechanical models using unloaded geometries

Kallhovd, Siri; Sundnes, Joakim; Wall, Samuel

doi:10.1080/10255842.2019.1579312

Cited by 8 publications

(10 citation statements)

References 32 publications

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“…Consequently, the quantities computed from the PV-loop, such as EF, were very sensitive to uncertainties in active stress. T ref changes the level of contractility, which in turn affects the pressure and volume of the LV cavity, as reported in [4].…”

Section: Discussionmentioning

confidence: 79%

“…Patient-specific simulations where personalized information from the patient are used as input for the simulation provide an individual understanding of the organ and its functions and can support diagnostics and treatments [2,3]. Simulations can also estimate important quantities that are difficult to be measured directly in patients, such as strain in fibre direction [4], and also myofibre stress, which is an important indicator of disease progression [5]. However, the translation of these simulations to a clinical context depends on the reliability of the model predictions.…”

Section: Introductionmentioning

confidence: 99%

“…A limited number of studies in cardiac mechanics have considered the entire cardiac cycle for performing UQ and SA of input parameters of the model. In particular, a simulation study of the entire cardiac cycle to investigate the impact of passive material parameters and a single contractility parameter was presented in [4], where the impact on myocardial stress and strains of a set of 21 material parameters from the literature was studied. However, the effects of other important input parameters such as fibre orientation, geometry, circulatory model and active stress still need to be investigated for the entire left ventricular cycle using modern and efficient techniques for UQ and SA.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle

Campos

Sundnes

Santos

et al. 2020

Phil. Trans. R. Soc. A.

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Patient-specific computer simulations can be a powerful tool in clinical applications, helping in diagnostics and the development of new treatments. However, its practical use depends on the reliability of the models. The construction of cardiac simulations involves several steps with inherent uncertainties, including model parameters, the generation of personalized geometry and fibre orientation assignment, which are semi-manual processes subject to errors. Thus, it is important to quantify how these uncertainties impact model predictions. The present work performs uncertainty quantification and sensitivity analyses to assess the variability in important quantities of interest (QoI). Clinical quantities are analysed in terms of overall variability and to identify which parameters are the major contributors. The analyses are performed for simulations of the left ventricle function during the entire cardiac cycle. Uncertainties are incorporated in several model parameters, including regional wall thickness, fibre orientation, passive material parameters, active stress and the circulatory model. The results show that the QoI are very sensitive to active stress, wall thickness and fibre direction, where ejection fraction and ventricular torsion are the most impacted outputs. Thus, to improve the precision of models of cardiac mechanics, new methods should be considered to decrease uncertainties associated with geometrical reconstruction, estimation of active stress and of fibre orientation. This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.

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Section: Discussionmentioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle

Campos

Sundnes

Santos

et al. 2020

Phil. Trans. R. Soc. A.

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“…In Kovacheva et al [43], the constitutive parameters were determined by solving an optimization problem using a gradient-free method: the distance between the simulated EDPVR and the one proposed by Klotz et al was minimized together with an additional condition imposed on the unloaded volume. The latter volume relation was again proposed by Klotz et al However, values from different sources contradict each other [96]. Recently, Marx et al [44] presented an automated method to match passive material parameters to the shape of a patient-specific EDPVR and to find an unloaded reference configuration of the heart simultaneously.…”

Section: Passive Stressmentioning

confidence: 99%

Electro-Mechanical Whole-Heart Digital Twins: A Fully Coupled Multi-Physics Approach

et al. 2021

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Mathematical models of the human heart are evolving to become a cornerstone of precision medicine and support clinical decision making by providing a powerful tool to understand the mechanisms underlying pathophysiological conditions. In this study, we present a detailed mathematical description of a fully coupled multi-scale model of the human heart, including electrophysiology, mechanics, and a closed-loop model of circulation. State-of-the-art models based on human physiology are used to describe membrane kinetics, excitation-contraction coupling and active tension generation in the atria and the ventricles. Furthermore, we highlight ways to adapt this framework to patient specific measurements to build digital twins. The validity of the model is demonstrated through simulations on a personalized whole heart geometry based on magnetic resonance imaging data of a healthy volunteer. Additionally, the fully coupled model was employed to evaluate the effects of a typical atrial ablation scar on the cardiovascular system. With this work, we provide an adaptable multi-scale model that allows a comprehensive personalization from ion channels to the organ level enabling digital twin modeling.

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“…update reference vector, X k+1 = X k − βR k 10: while R k ≥ 11: stress-free reference configuration, X * = X k point approaches are simple and versatile and can be coupled to existing FE software packages with relative ease and have thus been applied to a number of biomechanical modeling problems, e.g., [50,8,51].…”

Section: Stress-free Reference Configurationmentioning

confidence: 99%

Efficient identification of myocardial material parameters and the stress-free reference configuration for patient-specific human heart models

Marx,

Niestrawska,

Gsell

et al. 2021

Preprint

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Image-based computational models of the heart represent a powerful tool to shed new light on the mechanisms underlying physiological and pathological conditions in cardiac function and to improve diagnosis and therapy planning. However, in order to enable the clinical translation of such models, it is crucial to develop personalized models that are able to reproduce the physiological reality of a given patient. There have been numerous contributions in experimental and computational biomechanics to characterize the passive behavior of the myocardium. However, most of these studies suffer from severe limitations and are not applicable to high-resolution geometries. In this work, we present a novel methodology to perform an automated identification of in vivo properties of passive cardiac biomechanics. The highly-efficient algorithm fits material parameters against the shape of a patient-specific approximation of the end-diastolic pressurevolume relation (EDPVR). Simultaneously, a stress-free reference configuration is generated, where a novel fail-safe feature to improve convergence and robustness is implemented. Only clinical image data or previously generated meshes at one time point during diastole and one measured data point of the EDPVR are required as an input. The proposed method can be straightforwardly coupled to existing finite element (FE) software packages and is applicable to different constitutive laws and FE formulations. Sensitivity analysis demonstrates that the algorithm is robust with respect to initial input parameters.

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Sensitivity of stress and strain calculations to passive material parameters in cardiac mechanical models using unloaded geometries

Cited by 8 publications

References 32 publications

Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle

Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle

Electro-Mechanical Whole-Heart Digital Twins: A Fully Coupled Multi-Physics Approach

Efficient identification of myocardial material parameters and the stress-free reference configuration for patient-specific human heart models

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