Raj Piyush, Wu Lintong, Almeida Craig, Conway Lauren, Tanwar Swati, Middendorf Jill, Barman Ishan
Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
bioRxiv. 2023 Aug 16:2023.08.14.553328. doi: 10.1101/2023.08.14.553328.
Articular cartilage is a complex tissue, and early detection of osteoarthritis (OA) is crucial for effective treatment. However, current imaging modalities lack molecular specificity and primarily detect late-stage changes. In this study, we propose the use of Spatially Offset Raman Spectroscopy (SORS) for non-invasive, depth-dependent, and molecular-specific diagnostics of articular cartilage. We demonstrate the potential of SORS to penetrate deep layers of cartilage, providing a comprehensive understanding of disease progression. Our SORS measurements were characterized and validated through mechanical and histological techniques, revealing strong correlations between spectroscopic measurements and both Young's modulus and depth of cartilage damage. By longitudinally monitoring enzymatically degraded condyles, we further developed a depth-dependent damage-tracking method. Our analysis revealed distinct components related to sample depth and glycosaminoglycan (GAG) changes, offering a comprehensive picture of cartilage health. Collectively, these findings highlight the potential of SORS as a valuable tool for enhancing OA management and improving patient outcomes.
关节软骨是一种复杂的组织,骨关节炎(OA)的早期检测对于有效治疗至关重要。然而,目前的成像方式缺乏分子特异性,主要检测晚期变化。在本研究中,我们提出使用空间偏移拉曼光谱(SORS)对关节软骨进行非侵入性、深度依赖性和分子特异性诊断。我们证明了SORS穿透软骨深层的潜力,从而全面了解疾病进展。我们通过机械和组织学技术对SORS测量进行了表征和验证,揭示了光谱测量与杨氏模量和软骨损伤深度之间的强相关性。通过纵向监测酶降解的髁突,我们进一步开发了一种深度依赖性损伤跟踪方法。我们的分析揭示了与样本深度和糖胺聚糖(GAG)变化相关的不同成分,提供了软骨健康的全面情况。总的来说,这些发现突出了SORS作为增强OA管理和改善患者预后的有价值工具的潜力。