# A novel compression device to study the deformation of articular cartilage in murine model through dynamic imaging of mechanical loading

Sarah-Maud Sombris-Picot, Simon Le Floc'h, Patrick Cañadas, Emeline

Perrier-Groult, Laetitia Hudecek, C. Cavinato

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## To cite this version:

Sarah-Maud Sombris-Picot, Simon Le Floc'h, Patrick Cañadas, Emeline Perrier-Groult, Laetitia Hudecek, et al.. A novel compression device to study the deformation of articular cartilage in murine model through dynamic imaging of mechanical loading. Multidisciplinary Biomechanics Journal, 2025, 50th congress of the.., 10.46298/mbj.16244. hal-05191799v2

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# A novel compression device to study the deformation of articular cartilage in murine model through dynamic imaging of mechanical loading

Sarah-Maud Sombris-Picot<sup>a*</sup>, Simon Le Floc'h<sup>a</sup>, Patrick Cañadas<sup>a</sup>, Emeline Perrier-Groult<sup>b</sup>, Laetitia Hudecek<sup>c, d</sup>, Cristina Cavinato<sup>a</sup>

<sup>a</sup> LMGC, Univ. Montpellier, CNRS, Montpellier, France

<sup>b</sup> Institute for Regenerative Medicine & Biotherapy, Univ. Montpellier, INSERM, Montpellier, France

<sup>c</sup> Montpellier Ressources Imagerie, BioCampus, Univ. Montpellier, CNRS, INSERM, Montpellier, France

<sup>d</sup> INM, Univ. Montpellier, INSERM, Montpellier, France

* Corresponding author: sarah-maud.sombris-picot@umontpellier.fr

Received date: 06/04/2025

Accepted date: 27/06/2025

Publication date: 27/10/2025

**Keywords:** articular cartilage, experimental characterization, multi-scale mechanics, microstructure

© 2025 The Authors

Licence CC-BY 4.0

Published by Société de Biomécanique

## 1. Introduction

Articular cartilage is a soft tissue with multiple mechanical functions, ensuring smooth movement between bone surfaces, transmitting mechanical stresses, and absorbing shocks. Its mechanical role is a key aspect for locomotion (Chang & Tang, 2020). This study aims to understand how the articular cartilage of wild-type mouse tibial plateau responds to compression by investigating the micro-mechanisms of deformation and stress that occur throughout the tissue. It has previously been shown that chondrocyte nuclei are greatly influenced by their matrix environment. This highlights the importance of studying deformation from the pericellular zone to the chondrocyte nuclei during mechanical loading of the entire tissue. To achieve this, an innovative compression system has been developed to monitor the tissue components response to load at both the macro and micro scales through imaging (Komeili et al., 2018). This combined approach allows for detailed analysis of the 3D microstructure, focusing on the morphological characterization and the local mechanical fields of chondrocyte nuclei and collagen network in relation to the applied mechanical load.

## 2. Methods

### 2.1 Sample preparation

Tibial articular cartilage from 8-week-old male C57BL/6 mice was carefully dissected immediately

after sacrifice. The tibia was cut 1mm below the plateau surface ensuring a flat surface of support for mechanical testing. Samples were rinsed with phosphate buffer saline and incubated in a nucleic acid staining solution with SYTO13 (Invitrogen™) for 1 hour prior mechanical testing.

### 2.2 Mechanical testing and microscopy

The samples underwent three sequential linear compression steps, each of 12.5% of the initial thickness, applied at a strain rate of 4.16 10⁻⁴ s⁻¹.

Between each step, the compression was maintained for 5, 10 and 15 min, respectively, to allow stress relaxation. To apply the combined mechanical and imaging protocol, a custom-made uniaxial mechanical system (Fig. 1.a) was developed. This setup enables stable 3D images throughout the entire thickness of the cartilage sample at both milli- and micro-metric levels using high-resolution cameras, optical coherence tomography (OCT) and multiphoton microscopy (MPM) (Yang et al., 2023).

Force signals were collected using a custom Python program for real-time data acquisition. Second-harmonic generation (SHG) and green fluorescence imaging were used to investigate the local orientation of the constituents and the local tissue deformation with a focus on type II collagen and chondrocyte nuclei.
<figure><img src="image_4.png" /><figcaption>**Figure 1.** (a) Illustration of the uniaxial compression device mounted under the MPM objective. (b) SHG microscopy images before and after 37.5% compression, and histogram of the pericellular holes orientation (c) Regions of Interest (ROIs) obtained with Cellpose and 3D reconstruction of the pericellular holes.</figcaption></figure>

Credit: Sarah-Maud Sombris-Picot*<sup>a</sup>

## 2.3 Image analysis

The MPM acquired images had a size of 1500x1500 pixels, with a pixel resolution in the x-y plane (parallel to the cartilage surface) of 0.41 µm x 0.41 µm and an interval of 1µm between each stack's slice along the depth or z direction.

Several image analysis strategies were implemented, including the analysis of constituents' orientation and morphological changes. Focus was placed on the pericellular holes in the collagen network (Fig. 1.b-c). To study their orientation, the OrientationJ analysis tool (OrientationJ Plugins (Rezakhaniha et al., 2012)) was used to provide a histogram of local angles. For the morphological analysis, Cellpose (Stringer et al., 2021) was used as a segmentation tool.

## 3. Results and discussion

OCT-based cartilage thickness quantification yielded an average of 120 µm, used as the reference for calculating applied strain across all samples. The SHG images clearly revealed the type II collagen network, specifically the regions hosting the cartilage cells, i.e., chondrocytes. The orientation analysis revealed a slight local reorientation of the collagen fibers surrounding the pericellular holes after each compression (Fig. 1b), with the greatest effect noticed in the superficial layers

of cartilage. The quantified collagen reorganization and the deformation of both collagen and nuclei align with the depth-dependent mechanical properties and histological heterogeneities of the healthy murine articular cartilage.

Next, Cellpose was used and trained on the 3D stack images to perform repeatable analysis of the nuclei deformation and reorientation within the step of compression (Fig. 1.c).

To further quantify the local mechanical fields around the cells and their reorientation, the images will be analysed using Fast Fourier Transform and thresholding techniques to extract quantitative information. Alongside those studies, digital volume correlation for volumetric displacement and strain measurement will also be carried out to understand more deeply the mechanical response of the articular cartilage under compression.

## 4. Conclusions

This study shows that the collagen II network within the articular cartilage deforms in response to load. Given the depth-dependent properties of the tissue, our experiments highlight the importance of studying the micro-mechanisms of deformation and stress throughout the whole tissue during movement. Future experiments will extend this study by examining the impact of osteoarthritis on the deformation of the collagen and chondrocyte network.

## Acknowledgements

The authors thank the imaging facility Montpellier Ressources Imagerie (MRI), the Réseau des Animaleries de Montpellier (RAM), and Gille Camp (Expérimentation et Calcul Scientifique, LMGC) for their support.

## Conflict of Interest Statement

None.

## Contributor Roles

SMSP: Conceptualization, Formal analysis, Investigation, Methodology, Visualization, Writing-original draft; SLF: Conceptualization, Supervision, Writing-review & editing; PC: Conceptualization, Supervision, Writing-review & editing; EPG: Conceptualization, Resources, Supervision, Writing-review & editing; LH: Resources; CC: Conceptualization, Supervision, Funding acquisition, Methodology, Project administration, Writing-review & editing.
## Funding

Work supported by the French National Research Agency, ANR-22-CPJ1-0090-01 to CC and ANR-10-INBS-04, 'Investments for the future' to MRI facility.

## References

Chang, A., & al. (2020). Determination of the depth- and time- dependent mechanical behavior of mouse articular cartilage using cyclic reference point indentation. *CARTILAGE, 11*(3), 358-363. https://doi.org/10.1177/1947603518786554

Komeili, A., & al. (2018). A compression system for studying depth-dependent mechanical properties of articular cartilage under dynamic loading conditions. *Medical Engineering & Physics, 60*, 103-108. https://doi.org/10.1016/j.medengphy.2018.07.004

Rezakhaniha, R. & al. (2012). Experimental investigation of collagen waviness and orientation in the arterial adventitia using confocal laser scanning microscopy. *Biomechanics and Modeling in Mechanobiology, 11*(3-4), 461-473. https://doi.org/10.1007/s10237-011-0325-z

Stringer, C. & al. (2021). Cellpose: a generalist algorithm for cellular segmentation. *Nature Methods, 18*(1), 100-106. https://doi.org/10.1038/s41592-020-01018-x

Yang, F. & al. (2023). In situ observation of cartilage matrix based on two-photon fluorescence microscopy. *Biochemical and Biophysical Research Communications, 682*, 64-70. https://doi.org/10.1016/j.bbrc.2023.09.057