Experimental characterization and model identification of the nonlinear compressible material behavior of lung parenchyma

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

doi:10.1016/j.jmbbm.2017.08.001

Cited by 16 publications

(33 citation statements)

References 19 publications

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“…[46][47][48] Nevertheless, also other soft tissues showing a natural pattern may be easily analysed using the proposed IR approach. [31][32][33] However, an additional check of the registration quality is recommended using another metric such as SSIM used here, otherwise some unreliable deformation can be found. The potential of full-field methods is especially important for diseased soft tissues such as atherosclerotic arteries, the heterogeneity of which disables creation of a regular specimen shape.…”

Section: Discussionmentioning

confidence: 99%

“…[31] However, neither verification nor reproducibility analyses were described in that study, although the same methodology was applied several times. [32,33] Zhu et al [34] recently compared both methodologies with promising results on synthetic data. Another approach was used by Miga et al [35] who, similarly to the IR based methods, deformed one image to fit the shape of another using finite element simulations.…”

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confidence: 99%

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Evaluation of image registration for measuring deformation fields in soft tissue mechanics

Lisický

Avril

Eydan

et al. 2022

Strain

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High‐fidelity biomechanical models usually involve the mechanical characterisation of biological tissues using experimental methods based on optical measurements. In most experiments, strains are evaluated based on displacements of a few markers and represents an average within the region of interest (ROI). Full‐field measurements may improve description of non‐homogeneous materials such as soft tissues. The approach based on non‐rigid image registration is proposed and compared with standard digital image correlation (DIC) on a set of samples, including (i) complex heterogeneous deformations with sub‐pixel displacement, (ii) a typical uniaxial tension test of aorta, and (iii) an indentation test on skin. The possibility to extend the ROI to the whole sample and the exploitation of a natural tissue pattern represents the main assets of the proposed method whereas the results show similar accuracy as standard DIC when analysing sub‐pixel deformations. Therefore, displacement and strain fields measurement based on image registration is very promising to characterise heterogeneous specimens with irregular shapes and/or small dimensions, which are typical features of soft biological tissues.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Evaluation of image registration for measuring deformation fields in soft tissue mechanics

Lisický

Avril

Eydan

et al. 2022

Strain

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“…The variability in collagen fibre undulations and diameter leads to a wide range of time-constants in the viscoelastic behaviour of lung parenchyma [24]. Both quasistatic and dynamic collagen testing, in which tissue strips of the lung are treated with collagenase to isolate the contributions of collagen, has been reported [25][26][27]. Birzle et al [25] found that the samples treated with collagenase had a larger drop in stiffness at higher strains, indicating a larger collagen contribution at this point, while elastin contribution was more significant at lower strains.…”

Section: Collagenmentioning

confidence: 99%

Computational lung modelling in respiratory medicine

Neelakantan

Xin

Gaver

et al. 2022

J. R. Soc. Interface.

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Computational modelling of the lungs is an active field of study that integrates computational advances with lung biophysics, biomechanics, physiology and medical imaging to promote individualized diagnosis, prognosis and therapy evaluation in lung diseases. The complex and hierarchical architecture of the lung offers a rich, but also challenging, research area demanding a cross-scale understanding of lung mechanics and advanced computational tools to effectively model lung biomechanics in both health and disease. Various approaches have been proposed to study different aspects of respiration, ranging from compartmental to discrete micromechanical and continuum representations of the lungs. This article reviews several developments in computational lung modelling and how they are integrated with preclinical and clinical data. We begin with a description of lung anatomy and how different tissue components across multiple length scales affect lung mechanics at the organ level. We then review common physiological and imaging data acquisition methods used to inform modelling efforts. Building on these reviews, we next present a selection of model-based paradigms that integrate data acquisitions with modelling to understand, simulate and predict lung dynamics in health and disease. Finally, we highlight possible future directions where computational modelling can improve our understanding of the structure–function relationship in the lung.

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“…The lung parenchyma whose primary function is gas exchange is a foam like structure composed of bronchioles, alveoli and the enclosed air volume. On a macroscopic scale that encompasses several alveoli, the parenchyma can be regarded to be a homogeneous structure that behaves isotropically [15], [16]. The mechanical properties of the lung parenchyma reflect its microstructure and play an important role in the functioning of the normal lung and the changes in these parameters index the pathology of the lung [17].…”

Section: Introductionmentioning

confidence: 99%

Effect of Pleural Membrane on the Propagation of Rayleigh Waves in Inflated Porous Lungs–A Study

2019

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In an attempt to include the effects of natural porosity of lung parenchyma into the mathematical study of lung diagnostics, a model describing the propagation of low-frequency Rayleigh waves in relation to the porous architecture of the lung parenchyma is presented. The wave motion is analyzed by assuming that the lung parenchyma behaves as an isotropic elastic half-space containing a distribution of vacuous pores with the visceral pleura as a taut elastic membrane in smooth contact with the half-space. The thinness of the pleural membrane in comparison with the large surface area of contact enables it to be modeled as a material surface in contact with the parenchyma. Utilizing the perturbation technique, an approximate formula for the Rayleigh wave velocity in the parenchyma with allowance for surface tension, mass density, and porosity is derived. In addition, the effect of the tension in the pleural membrane and the porosity in the parenchyma on the propagation of the low-frequency Rayleigh waves is brought out through the dispersion spectrum. It is hoped that the results of this paper would enable a better understanding of the porosity and surface-tension effects on lung parenchyma.

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Experimental characterization and model identification of the nonlinear compressible material behavior of lung parenchyma

Cited by 16 publications

References 19 publications

Evaluation of image registration for measuring deformation fields in soft tissue mechanics

Evaluation of image registration for measuring deformation fields in soft tissue mechanics

Computational lung modelling in respiratory medicine

Effect of Pleural Membrane on the Propagation of Rayleigh Waves in Inflated Porous Lungs–A Study

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