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Updated: Feb 13, 2026

Addressing Practical Issues in Atomic Force Microscopy-Based Micro-Indentation on Human Articular Cartilage Explants
Published on: October 28, 2022
A new mechanical indentation framework for functional assessment of articular cartilage
Zohreh Arabshahi1, Isaac Oluwaseun Afara2, Hayley Ruscoe Moody1
1School of Chemistry, Physics and Mechanical Engineering, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, Australia; Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia.
Abstract:
The conventional mechanical properties of articular cartilage, such as compressive stiffness, have been shown to have limited capacity to distinguish visually normal from degraded cartilage samples. In this study, a new mechanical indentation framework for assessing functional properties of articular cartilage during loading/unloading, i.e. deformation and recovery, was established. The capacity of a ring-shaped indenter integrated with an ultrasound transducer to distinguish mechanically intact from proteoglycan-depleted tissue was investigated. To achieve this, normal and enzymatically degraded bovine osteochondral samples were subjected to loading/unloading while the response of the tissue at the middle was captured by ultrasound at the same time. The enzymatic degradation model was characterized by amount of proteoglycan content, glycosaminoglycan release and proteomic analysis. The mechanical response of a wider continuum of articular cartilage in the loaded area and its surrounding region was captured in this framework leading to investigate two parameters, L and TS, related to the surrounding tissue of the loaded area for functional assessment of cartilage. L is the distance between the ultrasound transducer and articular cartilage surface and TS is the transient strain of articular cartilage during loading and unloading. Classification Analysis based on Principal Component Analysis was used to investigate the capacity of the new parameters to assess the functionality of the tissue. Multivariate statistics based on Partial Least Squares regression was employed to identify the correlation between the response of the tissue in the indented area and its surrounding cartilage. The results of this study indicate that L during loading (deformation) can differentiate normal and mildly proteoglycan-depleted samples from severely depleted samples and L during unloading (recovery) can distinguish between normal and proteoglycan-depleted tissue. However, TS during deformation and recovery is unable to discriminate normal cartilage samples from proteoglycan-depleted tissue. The results also demonstrate a strong correlation between mechanical properties of the loaded area with the response of its surrounding cartilage during recovery. It is therefore concluded that L in this newly established framework can discriminate between normal and proteoglycan-depleted cartilage samples. However, more samples will be needed to verify the demarcation between samples degraded for varying amount of time.
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