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Fan X, Sun AR, Young RSE, Afara IO, Hamilton BR, Ong LJY, Crawford R, Prasadam I. Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications. Bone Res 2024; 12:7. [PMID: 38311627 PMCID: PMC10838951 DOI: 10.1038/s41413-023-00304-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/21/2023] [Accepted: 11/27/2023] [Indexed: 02/06/2024] Open
Abstract
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.
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Affiliation(s)
- Xiwei Fan
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Antonia Rujia Sun
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Reuben S E Young
- Central Analytical Research Facility, Queensland University of Technology, Brisbane, QLD, Australia
- Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Isaac O Afara
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- School of Electrical Engineering and Computer Science, Faculty of Engineering, Architecture and Information Technology, University of Queensland, Brisbane, QLD, Australia
| | - Brett R Hamilton
- Centre for Microscopy and Microanalysis, University of Queensland, Brisbane, QLD, Australia
| | - Louis Jun Ye Ong
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Ross Crawford
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- The Prince Charles Hospital, Brisbane, QLD, Australia
| | - Indira Prasadam
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia.
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Chen YC, Huang HP. Ultraviolet-Visible-Near Infrared Spectroscopy May Aid in the Qualitative Assessment of Early-Stage Cartilage Degradation. Arthrosc Sports Med Rehabil 2024; 6:100842. [PMID: 38414840 PMCID: PMC10897593 DOI: 10.1016/j.asmr.2023.100842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 11/07/2023] [Indexed: 02/29/2024] Open
Abstract
Purpose To assess the potential of ultraviolet-visible near-infrared spectroscopy to provide quantitative information on the cartilage surface at early osteoarthritis. Methods We used a similar source and optical path to a standard arthroscope and constraining input to the range available to a standard detector/camera, further capturing and analyzing spectral information quantitatively in terms of specific electronic absorbance bands and scattering from the cartilage surface, with a focus on the early stages of degradation. Results The ratio of the 320-nm and longer than 500-nm absorbances produced a distinct change from the normal to diseased states. The slopes between the wavelengths of 600 and 980 nm may show the transition of the single fibril to fibril bundles that occurs during early stages disease. Conclusions Ultraviolet-visible near-infrared spectroscopy has good potential for use in integrated arthroscopic assessment. Clinical Relevance This raises the possibility of advancing arthroscopy from a qualitative to a quantitative tool, without requiring modification of either the radiation (the light source and path) or instrumentation (the arthroscope itself) delivered to the patient, thus allowing a low-cost yet potentially high-value technology.
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Affiliation(s)
- Ying-chun Chen
- Botnar Research Centre, NDORMS, University of Oxford, Oxford, United Kingdom
- Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Hsing-Po Huang
- Department of Mechanical Engineering, National Taipei University of Technology. Taipei, Taiwan
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Khan B, Nippolainen E, Shahini F, Torniainen J, Mikkonen S, Nonappa, Popov A, Töyräs J, Afara IO. Refractive index of human articular cartilage varies with tissue structure and composition. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2023; 40:2205-2214. [PMID: 38086029 DOI: 10.1364/josaa.498722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 10/19/2023] [Indexed: 12/18/2023]
Abstract
Optical properties of biological tissues, such as refractive index, are fundamental properties, intrinsically linked to a tissue's composition and structure. This study aims to investigate the variation of refractive index (RI) of human articular cartilage along the tissue depth (via collagen fibril orientation and optical density) and integrity (based on Mankin and Osteoarthritis Research Society International (OARSI) scores). The results show the relationship between RI and PG content (p=0.042), collagen orientation (p=0.037), and OARSI score (p=0.072). When taken into account, the outcome of this study suggests that the RI of healthy cartilage differs from that of pathological cartilage (p=0.072). This could potentially provide knowledge on how progressive tissue degeneration, such as osteoarthritis, affects changes in cartilage RI, which can, in turn, be used as a potential optical biomarker of tissue pathology.
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