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

Reliability and Accuracy of the Outerbridge Classification in Staging of Cartilage Defects

OBJECTIVE

The decision on whether or not and how to treat a local cartilage defect is still made intraoperatively based on the visual presentation of the cartilage and findings from indentations with an arthroscopic probe. The treatment decision is then usually based on grading according to established classifications systems, which, therefore, need to have high reliability and accuracy. The aim of the present study was to evaluate the reliability and accuracy of the Outerbridge classification in staging cartilage defects.

METHODS

We performed an observer arthroscopic study using the Outerbridge classification on seven fresh-frozen human cadaveric knees, which collectively exhibited nine cartilage defects. To evaluate accuracy, defect severity was verified through histological examination. Interrater and intrarater reliabilites were calculated using Cohen's kappa and the intra-class correlation coefficient (ICC 3.1).

RESULTS

The interrater and intrarater reliability for the Outerbridge classification ranged from poor to substantial, with 0.24 ≤ κ ≤ 0.70 and κ = 0.55 to κ = 0.66, respectively. The accuracy evaluated by comparison with the histological examination was 63% overall. The erroneous evaluations were, however, still often at the discrimination of grade 2 and 3. We did not find any relationship between higher experience and accuracy or intraobserver reliability. Taken together, these results encourage surgeons to further use diagnostic arthroscopy for evaluating cartilage lesions. Nevertheless, especially in grade 2 and 3, deviations from the histology were observed. This is, however, the point where a decision is made on whether to surgically address the defect or not.

CONCLUSION

Diagnostic arthroscopy is the standard for cartilage lesion assessment, yet interobserver reliability is fair to substantial. Caution is warranted in interpreting varied observer results. The accuracy of the "simpler" Outerbridge classification is insufficient compared to histological examinations, highlighting the need for improved techniques in guideline-based intraoperative decision-making.

Atomic force microscopy in disease-related studies: Exploring tissue and cell mechanics

Despite significant progress in human medicine, certain diseases remain challenging to promptly diagnose and treat. Hence, the imperative lies in the development of more exhaustive criteria and tools. Tissue and cellular mechanics exhibit distinctive traits in both normal and pathological states, suggesting that "force" represents a promising and distinctive target for disease diagnosis and treatment. Atomic force microscopy (AFM) holds great promise as a prospective clinical medical device due to its capability to concurrently assess surface morphology and mechanical characteristics of biological specimens within a physiological setting. This review presents a comprehensive examination of the operational principles of AFM and diverse mechanical models, focusing on its applications in investigating tissue and cellular mechanics associated with prevalent diseases. The findings from these studies lay a solid groundwork for potential clinical implementations of AFM. RESEARCH HIGHLIGHTS: By examining the surface morphology and assessing tissue and cellular mechanics of biological specimens in a physiological setting, AFM shows promise as a clinical device to diagnose and treat challenging diseases.

The Revolution in Breast Cancer Diagnostics: From Visual Inspection of Histopathology Slides to Using Desktop Tissue Analysers for Automated Nanomechanical Profiling of Tumours

We aim to develop new portable desktop tissue analysers (DTAs) to provide fast, low-cost, and precise test results for fast nanomechanical profiling of tumours. This paper will explain the reasoning for choosing indentation-type atomic force microscopy (IT-AFM) to reveal the functional details of cancer. Determining the subtype, cancer stage, and prognosis will be possible, which aids in choosing the best treatment. DTAs are based on fast IT-AFM at the size of a small box that can be made for a low budget compared to other clinical imaging tools. The DTAs can work in remote areas and all parts of the world. There are a number of direct benefits: First, it is no longer needed to wait a week for the pathology report as the test will only take 10 min. Second, it avoids the complicated steps of making histopathology slides and saves costs of labour. Third, computers and robots are more consistent, more reliable, and more economical than human workers which may result in fewer diagnostic errors. Fourth, the IT-AFM analysis is capable of distinguishing between various cancer subtypes. Fifth, the IT-AFM analysis could reveal new insights about why immunotherapy fails. Sixth, IT-AFM may provide new insights into the neoadjuvant treatment response. Seventh, the healthcare system saves money by reducing diagnostic backlogs. Eighth, the results are stored on a central server and can be accessed to develop strategies to prevent cancer. To bring the IT-AFM technology from the bench to the operation theatre, a fast IT-AFM sensor needs to be developed and integrated into the DTAs.

Alteration in cartilage matrix stiffness as an indicator and modulator of osteoarthritis

Osteoarthritis (OA) is characterized by cartilage degeneration and destruction, leading to joint ankylosis and disability. The major challenge in diagnosing OA at early stage is not only lack of clinical symptoms but also the insufficient histological and immunohistochemical signs. Alteration in cartilage stiffness during OA progression, especially at OA initiation, has been confirmed by growing evidences. Moreover, the stiffness of cartilage extracellular matrix (ECM), pericellular matrix (PCM) and chondrocytes during OA development are dynamically changed in unique and distinct fashions, revealing possibly inconsistent conclusions when detecting cartilage matrix stiffness at different locations and scales. In addition, it will be discussed regarding the mechanisms through which OA-related cartilage degenerations exhibit stiffened or softened matrix, highlighting some critical events that generally incurred to cartilage stiffness alteration, as well as some typical molecules that participated in constituting the mechanical properties of cartilage. Finally, in vitro culturing chondrocytes in various stiffness-tunable scaffolds provided a reliable method to explore the matrix stiffness-dependent modulation of chondrocyte metabolism, which offers valuable information on optimizing implant scaffolds to maximally promote cartilage repair and regeneration during OA. Overall, this review systematically and comprehensively elucidated the current progresses in the relationship between cartilage stiffness alteration and OA progression. We hope that deeper attention and understanding in this researching field will not only develop more innovative methods in OA early detection and diagnose but also provide promising ideas in OA therapy and prognosis.

Prognostic potential and pathological validation of a diagnostic application using Raman spectroscopy in the characterization of degenerative changes in the cartilage of the humeral head

SIGNIFICANCE

Raman spectroscopy is a well-established analytical method in the fields of chemistry, industry, biology, pharmaceutics, and medicine. Previous studies have investigated optical imaging and Raman spectroscopy for osteoarthritis (OA) diagnosis in weight-bearing joints such as hip and knee joints. However, to realize early diagnosis or a curable treatment, it is still challenging to understand the correlations with intrinsic factors or patients’ background.

AIM

To elucidate the correlation between the Raman spectral features and pathological variations of human shoulder joint cartilage.

APPROACH

Osteoarthritic cartilage specimens excised from the humeral heads of 14 patients who underwent shoulder arthroplasty were assessed by a confocal Raman microscope and histological staining. The Raman spectroscopic dataset of degenerative cartilage was further analyzed by principal component analysis and hierarchical cluster analysis.

RESULTS

Multivariate association of the Raman spectral data generated three major clusters. The first cluster of patients shows a relatively high Raman intensity of collagen. The second cluster displays relatively low Raman intensities of proteoglycans (PGs) and glycosaminoglycans (GAGs), whereas the third cluster shows relatively high Raman intensities of PGs and GAGs. The reduced PGs and GAGs are typical changes in OA cartilage, which have been confirmed by safranin–O staining. In contrast, the increased Raman intensities of collagen, PGs, and GAGs may reflect the instability of the cartilage matrix structure in OA patients.

CONCLUSIONS

The results obtained confirm the correlation between the Raman spectral features and pathological variations of human shoulder joint cartilage. Unsupervised machine learning methods successfully yielded a clinically meaningful classification between the shoulder OA patients. This approach not only has potential to confirm severity of cartilage defects but also to determine the origin of an individual’s OA by evaluating the cartilage quality.