Fiberoptic microindentation technique for early osteoarthritis diagnosis: an in vitro study on human cartilage

Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications

Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.

Detecting early osteoarthritis through changes in biomechanical properties - A review of recent advances in indentation technologies in a clinical arthroscopic setup

Osteoarthritis (OA) is a degenerative joint disease currently affecting half of all women and one-third of all men aged over 65 and it is predicted to even increase in the next decades. In the variety of causes leading to OA, the first common denominator are changes in the extracellular matrix of the cartilage. In later stages, OA affects the whole joint spreading to higher levels of tissue architecture causing irreversible functional and structural damage. To date, the diagnosis of OA is only formulated in the late stages of the disease. This is also, where most present therapies apply. Since a precise diagnosis is a prerequisite for targeted therapy, tools to diagnose early OA, monitor its progression, and accurately stage the disease are wanted. This review article focuses on recent advances in indentation technologies to diagnose early OA through describing biomechanical cartilage characteristics. We provide an overview of microindentation instruments, indentation-type Atomic Force Microscopy, ultrasound, and water-jet ultrasound indentation, Optical Coherence Tomography-based air-jet indentation, as well as fiber Bragg grating.

Proof-of-concept for the detection of early osteoarthritis pathology by clinically applicable endomicroscopy and quantitative AI-supported optical biopsy

OBJECTIVE

Clinical trials for osteoarthritis (OA), the leading cause of global disability, are unable to pinpoint the early, potentially reversible disease with clinical technology. Hence, disease-modifying drug candidates cannot be tested early in the disease. To overcome this obstacle, we asked whether early OA-pathology detection is possible with current clinical technology.

METHODS

We determined the relationship between two sensitive early OA markers, atomic force microscopy (AFM)-measured human articular cartilage (AC) surface stiffness, and location-matched superficial zone chondrocyte spatial organizations (SCSOs), asking whether a significant loss of surface stiffness can be detected in early OA SCSO stages. We then tested whether current clinical technology can visualize and accurately diagnose the SCSOs using an approved probe-based confocal laser-endomicroscope and a random forest (RF) model.

RESULTS

We demonstrated a correlation between AC surface stiffness and the SCSO (r_rm = -0.91; 95%CI: -0.97, -0.73), and an extensive loss of surface stiffness specifically in those ACs with early OA-typical SCSO (95%CIs: string SCSO: 269-173 kPa, double string SCSO: 77-46 kPa). This established the SCSO as a visualizable, functionally relevant surrogate marker of early OA AC surface pathology. Moreover, SCSO-based stiffness discrimination worked well in each patient's AC. We then demonstrated feasibility of visualizing the SCSO by clinical laser-endomicroscopy and, importantly, accurate SCSO diagnosis using RF.

CONCLUSION

We present the proof-of-concept of early OA-pathology detection with available clinical technology, introducing a future-oriented, AI-supported, non-destructive quantitative optical biopsy for early disease detection. Operationalizing SCSO recognition, this approach allows testing for correlations between local tissue architectures with other experimental and clinical read-outs, but needs clinical validation and a larger sample size for defining diagnostic thresholds.

Early Detection of Cartilage Degeneration: A Comparison of Histology, Fiber Bragg Grating-Based Micro-Indentation, and Atomic Force Microscopy-Based Nano-Indentation

We have determined the sensitivity and detection limit of a new fiber Bragg grating (FBG)-based optoelectronic micro-indenter for biomechanical testing of cartilage and compared the results to indentation-type atomic force microscopy (IT-AFM) and histological staining. As test samples, we used bovine articular cartilage, which was enzymatically degraded ex vivo for five minutes using different concentrations of collagenase (5, 50, 100 and 500 µg/mL) to mimic moderate extracellular matrix deterioration seen in early-stage osteoarthritis (OA). Picrosirius Red staining and polarization microscopy demonstrated gradual, concentration-dependent disorganization of the collagen fibrillar network in the superficial zone of the explants. Osteoarthritis Research Society International (OARSI) grading of histopathological changes did not discriminate between undigested and enzymatically degraded explants. IT-AFM was the most sensitive method for detecting minute changes in cartilage biomechanics induced by the lowest collagenase concentration, however, it did not distinguish different levels of cartilage degeneration for collagenase concentrations higher than 5 µg/mL. The FBG micro-indenter provided a better and more precise assessment of the level of cartilage degeneration than the OARSI histological grading system but it was less sensitive at detecting mechanical changes than IT-AFM. The FBG-sensor allowed us to observe differences in cartilage biomechanics for collagenase concentrations of 100 and 500 µg/mL. Our results confirm that the FBG sensor is capable of detecting small changes in articular cartilage stiffness, which may be associated with initial cartilage degeneration caused by early OA.

Osteoarthritis Severely Decreases the Elasticity and Hardness of Knee Joint Cartilage: A Nanoindentation Study

The nanoindentation method was applied to determine the elastic modulus and hardness of knee articular cartilage. Cartilage samples from both high weight bearing (HWB) and low weight bearing (LWB) femoral condyles were collected from patients diagnosed with osteoarthritis (OA). The mean elastic modulus of HWB cartilage was 4.46 ± 4.44 MPa in comparison to that of the LWB region (9.81 ± 8.88 MPa, p < 0.001). Similarly, the hardness was significantly lower in HWB tissue (0.317 ± 0.397 MPa) than in LWB cartilage (0.455 ± 0.434 MPa, p < 0.001). When adjusted to patients’ ages, the mean elastic modulus and hardness were both significantly lower in the age group over 70 years (p < 0.001). A statistically significant difference in mechanical parameters was also found in grade 3 and 4 OA. This study provides an insight into the nanomechanical properties of the knee articular cartilage and provides a starting point for personalized cartilage grafts that are compatible with the mechanical properties of the native tissue.