3D image-based modelling of collagenous soft tissues

Abstract

Due to their fibrous nature soft collagenous tissues such as skin possess strongly directional mechanical properties which play a key role in ensuring their diverse physiological functions. From a modelling perspective, incorporating information about spatially-dependent fibre orientation is essential for faithfully simulating the micromechanical behaviour of collagen-rich tissues. Current state-of-the-art models of soft tissues only account for local fibre orientation in an averaged (i.e. statistical) sense or are restricted to 2D. The complex 3D architecture of collagen fibres is key in conditioning the mechanics of biological tissues and it is therefore essential to integrate it into the next generation of biophysical models to support basic discovery research and a wide range of industrial applications from medical devices to consumer goods and sport equipment.The aim of this project is to study the micromechanics of collagenous soft tissues (e.g. skin) through the development of novel quantitative and mechanistic tools combining imaging and biomechanical modelling. 1.The first objective of this project was to develop an integrative methodology combining high-resolution imaging techniques (micro-CT, serial block face scanning electron microscopy, 2D histology), fibre orientation extraction algorithm and finite element modelling to extract and efficiently integrate the 3D architecture of collagen fibre networks in biological soft tissues’ models. 2.Using the methodology, the second objective was to generate image-based 3D micromechanical finite element models of human skin to study the interplay of the collagen network characteristics and the mechanical properties of the surrounding matrix, particularly as a result of ageing. This was be done by simulating uniaxial and equibiaxial tensile tests.Against this backdrop, this study reveals several significant contributions:•A robust automated workflow of the conversion of high-resolution images (e.g. SBF-SEM) into voxel-based 8-noded hexahedral finite elements using 3D structure tensor fibre extraction algorithm is designed, paving the way for detailed image-based micromechanical finite element models of collagenous tissues with a new level of bio-fidelity.•The quadratic down sampling of the fibre vector field based on the 27-noded hexahedral element interpolation method brings superior smoothness of the orientation distributions of fibres compared to a simple averaging scheme. The assessment of the down sampling scheme in terms of model results’ accuracy, computing time and convergence performance provides a rational justification for optimal fibre ratio threshold value for full-resolution and down sampled mesh respectively, providing guidance for creation of other image-based models.3• The micromechanical analysis of an image-based RVE of human skim dermis provides novel quantitative insight into how spatially uniform and non-uniform fibre orientation distributions affect RVE’s micromechanics. Specifically, despite lower fibre volume fraction, the realistic skin model (with local fibre assignment) exhibits an order of magnitude higher equivalent nominal stress compared to models with uniform fibre distribution. Additionally, the local maximum logarithmic strain distribution in the realistic model reveals two distinct peaks, whereas the other model captures only one.• Compared to standard continuum fibre-reinforced models which assume spatial uniformity of the fibre orientation vector field my image-based model allows the assignment of fibre direction at finite element level, thus enabling a new level of mechanistic insight into the complex tissue’s anisotropy. Furthermore, our novel approach reveals the need to distinguish between local (i.e. individual element) and RVE’s scales for faithfully capturing local fibre kinematics (smaller local stretches along local fibre longitudinal direction).• Correlative imaging techniques (microCT, SBF-SEM and 2D histology) are extended to capture collagen fibre structure within human skin tissue across microscale, submicroscale and nanoscale. The quantification of age-related changes in collagen fibre features illustrates that the collagen fibre density decreases with age and collagen fibre waviness for the aged skin sample follows a beta distribution ( alpha=2.39, beta=1.194 ).• The fibre orientation distribution and finite element simulation results of young and aged skin models reveal that collagen fibres in the aged skin sample exhibit less variation in orientation compared to those of young skin, leading to higher RVE stiffness even at small strain levels when stretched along the preferred fibre direction. Our results corroborate the convergence toward a more pronounced tissue anisotropy with age which has been widely reported in the literature. The proportion of elastic fibres within skin dermis also decreases with age. These factors explain a reduced mechanical resilience in the aged skin, further illustrating the mechanism behind how young and aged skin distinct biostructural properties have a significant influence on the skin macroscopic mechanical behaviour.

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Identifiers

ORCID for Jia Li: orcid.org/0009-0007-3590-5271

ORCID for Orestis L. Katsamenis: orcid.org/0000-0003-4367-4147

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