Passive diastolic modelling of human ventricles: Effects of base movement and geometrical heterogeneity

Palit, Arnab; Franciosa, Pasquale; Bhudia, Sunil; Arvanitis, Theodoros N.; Turley, Glen A.; Williams, Mark A.

doi:10.1016/j.jbiomech.2016.12.023

Cited by 16 publications

(17 citation statements)

References 44 publications

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“…Functionally, all cases led to EFs in the lower normal range for healthy humans . However, the traditional method of validating myocardial models only by comparing the LV EDVs has been proven to be insufficient . Therefore, the in vivo reference BV behavior was conjointly studied by measuring the in vivo systolic regional strains using the Segment software suite, which lead to the 3540 circumferential and 2880 radial strains in the LV depicted in Figure (plus 1975 longitudinal strain measurements of inferior quality).…”

Section: Discussionmentioning

confidence: 99%

“…32,79 However, the traditional method of validating myocardial models only by comparing the LV EDVs has been proven to be insufficient. 43 Therefore, the in vivo reference BV behavior was conjointly studied by measuring the in vivo systolic regional strains using the Segment software suite, which lead to the 3540 circumferential and 2880 radial strains in the LV depicted in Figure 4 (plus 1975 longitudinal strain measurements of inferior quality). These strains gave expected results (systolic mid, base, and apical radial Green strains were 0.084 ± 0.151, 0.112 ± 0.185, and 0.024 ± 0.062, respectively, whereas the systolic circumferential Green strains were −0.095 ± 0.050, −0.115 ± 0.044, and −0.110 ± 0.029 in the corresponding basal, mid, and apical regions, respectively) and correlated well with published data.…”

Section: Discussionmentioning

confidence: 99%

“…Despite the wide range of (bi) ventricular modeling studies found in literature, no consistent approach in incorporating the effect of external tissue support into these models could be found (we considered a non‐exhaustive subset of (bi) ventricular modeling studies (published over the last decade) where generic kinematic BCs were used:). Overall, most studies adopted the practice to apply Neumann BCs on the endocardial surface and to constrain basal out‐of‐plane motion by constraining the basal nodes not to move along the basal surface's normal direction (be it using an exact or penalty‐method based Dirichlet BC).…”

Section: Currently Used Generic Kinematic Constraintsmentioning

confidence: 99%

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Kinematic boundary conditions substantially impact in silico ventricular function

Peirlinck

Sack

Backer

et al. 2018

Numer Methods Biomed Eng

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Computational cardiac mechanical models, individualized to the patient, have the potential to elucidate the fundamentals of cardiac (patho-)physiology, enable non-invasive quantification of clinically significant metrics (eg, stiffness, active contraction, work), and anticipate the potential efficacy of therapeutic cardiovascular intervention. In a clinical setting, however, the available imaging resolution is often limited, which limits cardiac models to focus on the ventricles, without including the atria, valves, and proximal arteries and veins. In such models, the absence of surrounding structures needs to be accounted for by imposing realistic kinematic boundary conditions, which, for prognostic purposes, are preferably generic and thus non-image derived. Unfortunately, the literature on cardiac models shows no consistent approach to kinematically constrain the myocardium. The impact of different approaches (eg, fully constrained base, constrained epi-ring) on the predictive capacity of cardiac mechanical models has not been thoroughly studied. For that reason, this study first gives an overview of current approaches to kinematically constrain (bi) ventricular models. Next, we developed a patient-specific in silico biventricular model that compares well with literature and in vivo recorded strains. Alternative constraints were introduced to assess the influence of commonly used mechanical boundary conditions on both the predicted global functional behavior of the in-silico heart (cavity volumes, stroke volume, ejection fraction) and local strain distributions. Meaningful differences in global functioning were found between different kinematic anchoring strategies, which brought forward the importance of selecting appropriate boundary conditions for biventricular models that, in the near future, may inform clinical intervention. However, whilst statistically significant differences were also found in local strain distributions, these differences were minor and mostly confined to the region close to the applied boundary conditions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Currently Used Generic Kinematic Constraintsmentioning

confidence: 99%

See 1 more Smart Citation

Kinematic boundary conditions substantially impact in silico ventricular function

Peirlinck

Sack

Backer

et al. 2018

Numer Methods Biomed Eng

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“…Another limitation to be mentioned is that the US images were captured from the basal part and other tissues such as valves, papillary muscles and irregularities were removed. The presence of all these features may affect the local distribution of stresses as the movement of the human heart base is significant compared to the apex movement (Palit et al 2017). This means that most of the conclusions of this study would not hold at a local scale where these features would be resolved.…”

Section: Limitations and Future Workmentioning

confidence: 91%

Importance of material parameters and strain energy function on the wall stresses in the left ventricle

Behdadfar

Navarro

Sundnes

et al. 2017

Computer Methods in Biomechanics and Biomedical Engineering

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Patient-specific estimates of the stress distribution in the left ventricles (LV) may have important applications for therapy planning, but computing the stress generally requires knowledge of the material behaviour. The passive stress-strain relation of myocardial tissue has been characterized by a number of models, but material parameters (MPs) remain difficult to estimate. The aim of this study is to implement a zero-pressure algorithm to reconstruct numerically the stress distribution in the LV without precise knowledge of MPs. We investigate the sensitivity of the stress distribution to variations in the different sets of constitutive parameters. We show that the sensitivity of the LV stresses to MPs can be marginal for an isotropic constitutive model. However, when using a transversely isotropic exponential strain energy function, the LV stresses become sensitive to MPs, especially to the linear elastic coefficient before the exponential function. This indicates that in-vivo identification efforts should focus mostly on this MP for the development of patient-specific finite-element analysis.

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“…As such, these methods require the execution of many mechanical simulations and/or nonlinear optimisation routines, which are accompanied by a significant computational burden. Moreover, there is a limited overlap between the space of deformations in actual data and those reproduced by mechanical simulations, caused by the presence of data artefacts and a series of model assumptions [10,6].…”

Section: Introductionmentioning

confidence: 99%

Solution to the Unknown Boundary Tractions in Myocardial Material Parameter Estimations

Nasopoulou

Nordsletten

Niederer

et al. 2019

Functional Imaging and Modeling of the Heart

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Passive material parameter estimation can facilitate the in vivo assessment of myocardial stiffness, an important biomarker for heart failure stratification and screening. Parameter estimation strategies employing biomechanical models of various degrees of complexity have been proposed, usually involving a significant number of cardiac mechanics simulations. The clinical translation of these strategies however is limited by the associated computational cost and the model simplifications. A simpler and arguably more robust alternative is the use of data-based approaches, which do not involve mechanical simulations and can be based for example on the formulation of the energy balance in the myocardium from imaging and pressure data. This approach however requires the estimation of the mechanical work at the myocardial boundaries and the strain energy stored, tasks that are challenging when external loads are unknown-especially at the base which deforms extensively within the cardiac cycle. In this work we employ the principle of virtual work in a strictly data-based approach to uniquely identify myocardial material parameters by eliminating the effect of the unknown boundary tractions at the base. The feasibility of the method is demonstrated on a synthetic data set using a popular transversely isotropic material model followed by a sensitivity analysis to modelling assumptions and data noise.

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Passive diastolic modelling of human ventricles: Effects of base movement and geometrical heterogeneity

Cited by 16 publications

References 44 publications

Kinematic boundary conditions substantially impact in silico ventricular function

Kinematic boundary conditions substantially impact in silico ventricular function

Importance of material parameters and strain energy function on the wall stresses in the left ventricle

Solution to the Unknown Boundary Tractions in Myocardial Material Parameter Estimations

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