Research PaperHigh resolution three-dimensional strain measurements in human articular cartilage
Introduction
Articular cartilage is typically a robust soft tissue, transmitting forces during motion through to the subchondral bone over decades whilst maintaining excellent tribological properties. Yet articular cartilage can easily be damaged and is frequently injured through sporting activities, traumatic accidents and active lifestyles which are sustained long into retirement. Small injuries heal, yet larger damage, or regions not given sufficient rest, will tend to not regenerate correctly even with surgical intervention (Mollon et al., 2013). Successful tissue regeneration is driven in part by providing appropriate mechanical stimuli (Armiento et al., 2018; Athanasiou et al., 2015) which drive chondrogenic differentiation of progenitor cells (Panadero et al., 2016). A potential cause for the current lack of efficacy may be that the mechanical environment in available interventionsleads to the formation of inferior fibrocartilage (Mollon et al., 2013). Overcoming this problem with new solutions requires intimate knowledge of the mechanical properties of the host tissue, chiefly its strain response.
As with many biological tissues, articular cartilage is non-homogenous, anisotropic and multi-phase. It is composed largely of collagen, proteoglycans and a low density of chondrocytes, saturated with an interstitial fluid phase. The composition and arrangement of these components vary through the cartilage height in distinct zones (Hunziker et al., 2002). Traditional methods of measuring strain, for example displacement transducers, provide a single value of strain for an entire specimen. This can be useful for exploring strain rate dependency (Li et al., 2003), but is less suited to quantify the strain gradient within the material (Kerin et al., 1998). The latter is essential data when considering tissue engineered scaffolds that require specific strain gradients to form the correct tissue type.
To generate strain gradient data 2D surface strain measurement techniques have been developed such as digital image correlation (DIC) (Palanca et al., 2015a), which may be applied to an exposed surface (Schinagl et al., 1997), or within 100 μm of the edge of the sample (Guilak et al., 1995). Such surface methods provide more data than displacement transducers, but do not account for out of plane deformation (Disney et al., 2018), damage during sample extraction (Madden et al., 2013), release of residual strain (Michalek et al., 2009) and cannot measure strain at the tissue-biomaterial interface (Sukjamsri et al., 2015; Fernandez et al., 2019). When applied to cartilage, strain surface measurements also have limited ability to consider the 3D arcing arrangement of collagen fibrils which are integral to the cartilage's mechanical properties (Bhosale and Richardson, 2008). Collagen fibrils are oriented vertically in the deep cartilage zone but transition to a horizontal orientation in the superficial zone (Buckwalter et al., 1994). It follows that severing these fibrils to expose a surface for 2D measurement may negatively affect the model's physiological robustness and the superficial zone is at particular risk (Motavalli et al., 2014). 3D volumetric measurement would negate these concerns by allowing measurement across the sample interior, far from disruption of the collagen network caused by sample extraction.
Confocal laser scanning allows 3D measurements (Fick et al., 2014) but the technique inherently lacks penetration depth due to diffusion and scattering, therefore again covers a very limited depth of the sample, likely not being representative of the interior structure (Wong et al., 2001). Ideally the tissue should remain physiologically intact and imaged in 3D over a large field of view to represent the internal deformation accurately (Walton et al., 2015).
Digital volume correlation (DVC) offers the opportunity to create full-field three dimensional displacement and strain maps by using a combination of 3D imaging and in-situ loading. First proposed for bone (Bay et al., 1999), DVC has now been expanded to tissue-biomaterial interfaces (Fernandez et al., 2019; Clark et al., 2020a), implant micromotion (Sukjamsri et al., 2015) and soft tissues such as intervertebral disks (Disney et al., 2019) and lungs (Arora et al., 2017). The technique relies upon features within the tissue which can be imaged and the displacement of such features subsequently tracked during loading. Articular cartilage is not easily imaged in 3D with the required spatial resolution and sufficient intra-tissue contrast. However, a recent study has shown that various staining methods can show the chondrocyte distribution in micro CT imaging (Clark et al., 2020b). Applying the DVC method to human cartilage could provide information on the strain gradients within the material, and thus be useful for scaffold designs that aim to regenerate cartilage. Thus our hypothesis is that the DVC method may be used to measure strain in 3D through the full thickness of human articular cartilage.
Section snippets
Specimen preparation
Ethical approval for this study was sought from the Imperial College Human Tissue Bank (R15022-6A) and the work was covered by REC Wales approval 17/WA/0161. Four 3 mm diameter osteochondral plugs were harvested from fresh-frozen right femoral condyles of two cadaveric human donors (Fig. 1a). Three of the four plugs were taken from the medial condyle and one from the lateral condyle. Plugs were taken from the least curved surface in the loadbearing region of the knees with a thickness of
Imaging human cartilage using laboratory Micro-CT
Micro-CT scanning permitted visualisation of cellular features within the human articular cartilage (Fig. 2a and b) which were successfully located in successive scans (Fig. 2c), creating a unique pattern for DVC. Tracking features within subsets of size 80 voxels (Fig. 2b) with 50% overlap fulfilled the maximum acceptable error criteria (<1% strain error) for all strain components in all regions of the tissue (Fig. 2d): providing a measurement point spatial resolution of 75 μm. On average this
Discussion
The most important finding of this study is that strain can be measured in human cartilage using the DVC method. Using this method, we were able to measure the strain gradient in 3D through the thickness of the cartilage material, and report a non-uniform strain distribution through the depth of cartilage. The DVC method achieved displacement random error of under 1 μm and strain errors of under 1% strain. This has been accomplished with laboratory equipment, avoiding synchrotron facilities for
Author statement
Jeff Clark: Conception and design of the study, Acquisition of data, Interpretation of data, Drafting and revision of the manuscript and final approval for all aspects of the work. Ulrich Hansen: Conception and design of the study, Interpretation of data, Drafting and revision of the manuscript and final approval for all aspects of the work. Jonathan Jeffers: Conception and design of the study, Interpretation of data, Drafting and revision of the manuscript and final approval for all aspects of
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
We are grateful to Geoffrey Ng for providing samples. The authors gratefully acknowledge the financial support of EPSRC (Engineering and Physical Sciences Research Council) funding, United Kingdom (EP/N025059/1 and EP/K027549/1) and the first author holds the Imperial College Class of 1964 Scholarship, United Kingdom.
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