A coupled approach for identification of nonlinear and compressible material models for soft tissue based on different experimental setups – Exemplified and detailed for lung parenchyma

Birzle, Anna M.; Martin, Christian; Uhlig, Stefan; Wall, Wolfgang A.

doi:10.1016/j.jmbbm.2019.02.019

Cited by 23 publications

(41 citation statements)

References 29 publications

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“…The models revealed the relationships between lung pressure, volume, and alveolar stress [39] and between lung elasticity and alveolar wall stiffness and distortion [38,40,67,68]. Constitutive lung models have applied strain energy functions based on the behavior of bulk lung tissue in uni-axial tensile tests [45,69,70] and the pressure-volume changes that occur at physiological stretch [37]. Our geometric model reflects the normal and tumor geometries observed in mouse models and human histopathology (Fig.…”

Section: Discussionmentioning

confidence: 99%

“…To ensure that the constitutive model and associated material coefficients that we used for the alveolar walls provided an accurate representation of lung tissue material behavior, we implemented a hyperelastic constitutive model in FEBio that was developed previously by Birzle et al to describe the continuum level behavior of lung tissue [37]. We fit the material coefficients of a neo-Hookean hyperelastic constitutive model representing the alveolar walls so that the alveolar structural behavior matched that predicted by the Birzle constitutive model.…”

Section: Parameter Optimization Based On Bulk Lung Constitutive Modelmentioning

confidence: 99%

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Mechanics of lung cancer: A finite element model shows strain amplification during early tumorigenesis

Zitnay

Herron

Carney

et al. 2022

Preprint

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Early lung cancer lesions develop within a unique microenvironment that undergoes constant cyclic stretch from respiration. While tumor stiffening is an established driver of tumor progression, the contribution of stress and strain to lung cancer is unknown. We developed tissue scale finite element models of lung tissue to test how early lesions alter respiration-induced strain. We found that an early tumor, represented as alveolar filling, amplified the strain experienced in the adjacent alveolar walls. Tumor stiffening further increased the amplitude of the strain in the adjacent alveolar walls and extended the strain amplification deeper into the normal lung. In contrast, the strain experienced in the tumor proper was less than the applied strain, although regions of amplification appeared at the tumor edge. Measurements of the alveolar wall thickness in clinical and mouse model samples of lung adenocarcinoma (LUAD) showed wall thickening adjacent to the tumors, consistent with cellular response to strain. Modeling alveolar wall thickening by encircling the tumor with thickened walls moved the strain amplification radially outward, to the next adjacent alveolus. Simulating iterative thickening in response to amplified strain produced tracks of thickened walls. We observed such tracks in early-stage clinical samples. The tracks were populated with invading tumor cells, suggesting that strain amplification in very early lung lesions could guide pro-invasive remodeling of the tumor microenvironment. The simulation results and tumor measurements suggest that cells at the edge of a lung tumor and in surrounding alveolar walls experience increased strain during respiration that could promote tumor progression.Author SummaryLung cancer is the leading cause of cancer-related death in the world. Efforts to identify and treat patients early are hampered by an incomplete understanding of the factors that drive early lesion progression to invasive cancer. We aimed to understand the role of mechanical strain in early lesion progression. The lung is unique in that it undergoes cyclic stretch, which creates strain across the alveolar walls. Computational models have provided fundamental insights into the stretch-strain relationship in the lung. In order to map the strain experienced in the alveolar walls near a tumor, we incorporated a tumor into a tissue scale model of the lung under stretch. We used finite element modeling to apply physiological material behavior to the lung and tumor tissue. Based on reported findings and our measurements, tumor progression was modeled as stiffening of the tumor and thickening of the tumor-adjacent alveolar walls. We found that early tumors amplified the strain in the tumor-adjacent alveolar walls. Strain amplification also arose at the tumor edges. Simulating strain-mediated wall stiffening generated tracks of thickened walls. We experimentally confirmed the presence of tracks of thickened extracellular matrix in clinical samples of LUAD. Our model is the first to interrogate the alterations in strain in and around a tumor during simulated respiration and suggests that lung mechanics and strain amplification play a role in early lung tumorigenesis.

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Section: Discussionmentioning

confidence: 99%

Section: Parameter Optimization Based On Bulk Lung Constitutive Modelmentioning

confidence: 99%

Mechanics of lung cancer: A finite element model shows strain amplification during early tumorigenesis

Zitnay

Herron

Carney

et al. 2022

Preprint

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“…In the past we have already succesfully applied such algorithms for identification of constitutive laws and parameters of hyper-and visco-elastic biomechanical problems (see e.g. for problems with single type of experiments [34,35] and also the combination of different experiments on the same specimen [36]).…”

Section: Levenberg-marquardt Optimizationmentioning

confidence: 99%

“…In such applications, questions of scales and weights of the contribution to the residual r in the objective function must be answered, to not blindly weigh highest displacements the highest. Nevertheless it has been shown in [36] that also results from different experiments on the same specimen can be scaled and used in a single Levenberg-Marquardt based inverse analysis.…”

Section: Combination Of Datamentioning

confidence: 99%

Inverse analysis of material parameters in coupled multi-physics biofilm models

Willmann¹,

Wall²

2021

Preprint

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In this article we propose an inverse analysis algorithm to find the best fit of multiple material parameters in different coupled multi-physics biofilm models. We use a nonlinear continuum mechanical approach to model biofilm deformation that occurs in flow cell experiments. The objective function is based on a simple geometrical measurement of the distance of the fluid biofilm interface between model and experiments. A Levenberg-Marquardt algorithm based on finite difference approximation is used as an optimizer. The proposed method uses a moderate to low amount of model evaluations. For a first presentation and evaluation the algorithm is applied and tested on different numerical examples based on generated numerical results and the addition of Gaussian noise. Achieved numerical results show that the proposed method serves well for different physical effects investigated and numerical approaches chosen for the model. Presented examples show the inverse analysis for multiple parameters in biofilm models including fluid-solid interaction effects, poroelasticity, heterogeneous material properties and growth.

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“…Indentation of soft materials is also studied in [ 8 ], where the authors performed a theoretical and finite element study using Hertzian contact and generalizing for large hyperelastic deformation including material non-linearities. Suitable nonlinear compressible material model for soft materials is also derived in [ 9 ], with its parameters identified for lung parenchyma using experimental results and inverse analysis.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven GENERIC Modeling of Poroviscoelastic Materials

Ghnatios

Alfaro

González

et al. 2019

Entropy

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Biphasic soft materials are challenging to model by nature. Ongoing efforts are targeting their effective modeling and simulation. This work uses experimental atomic force nanoindentation of thick hydrogels to identify the indentation forces are a function of the indentation depth. Later on, the atomic force microscopy results are used in a GENERIC general equation for non-equilibrium reversible–irreversible coupling (GENERIC) formalism to identify the best model conserving basic thermodynamic laws. The data-driven GENERIC analysis identifies the material behavior with high fidelity for both data fitting and prediction.

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A coupled approach for identification of nonlinear and compressible material models for soft tissue based on different experimental setups – Exemplified and detailed for lung parenchyma

Cited by 23 publications

References 29 publications

Mechanics of lung cancer: A finite element model shows strain amplification during early tumorigenesis

Mechanics of lung cancer: A finite element model shows strain amplification during early tumorigenesis

Inverse analysis of material parameters in coupled multi-physics biofilm models

Data-Driven GENERIC Modeling of Poroviscoelastic Materials

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