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.

骨关节炎 (OA) 是一种影响多个关节组织的衰弱性退行性疾病，包括软骨、骨、滑膜和脂肪组织。 OA 呈现出多种临床表型和独特的分子内型，包括炎症、代谢、机械、遗传和滑膜变异。因此，需要创新技术来支持有效诊断和精准治疗方法的开发。由于技术限制，对大量 OA 组织提取物的传统分析存在局限性，这给区分关节组织中的各种生理和病理表型带来了挑战。这个问题导致了标准化困难并阻碍了临床试验的成功。深入了解 OA 组织中细胞和分子结构的空间变化（包括 DNA、RNA、代谢物和蛋白质）及其化学性质、元素组成和机械属性，有助于更全面地了解该疾病亚型。空间分辨生物学使生物学家能够在组织微环境的背景下研究细胞，从而提供更全面的细胞功能视图。创新空间生物学技术的最新进展现在允许使用各种组学镜头（例如基因组学、转录组学、蛋白质组学和代谢组学）以及空间数据来检查完整的组织切片。这种方法的融合为研究人员提供了在精确的空间坐标下了解细胞和组织的分子组成和功能的重要见解。此外，先进的成像技术，包括高分辨率显微镜、高光谱成像和质谱成像，可以实现生物分子、细胞和组织的空间分布的可视化和分析。将这些分子成像输出与传统组织组织学联系起来可以促进更全面地表征疾病表型。这篇综述总结了分子成像模式和深入空间分析方法的最新进展。它探讨了它们在 OA 领域的应用、挑战和潜在机遇。此外，本综述还为这些当代方法的潜在研究方向提供了视角，这些方法可以满足骨关节炎临床诊断的要求和建立治疗靶点。