Harnessing Raman spectroscopy and Multimodal Imaging of Cartilage for Osteoarthritis Diagnosis
Harnessing Raman spectroscopy and Multimodal Imaging of Cartilage for Osteoarthritis Diagnosis
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利用拉曼光谱和软骨多模态成像进行骨关节炎诊断
DOI：
10.1101/2023.09.05.23294936
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Crisford A
中科院分区：
文献类型：
--
作者：
Crisford A
骨关节炎（OA）是一种复杂的软骨疾病，其特征是关节疼痛、功能受限和生活质量降低，关节运动受影响，导致疼痛和活动受限。目前诊断OA的方法主要限于X射线、MRI和侵入性关节液分析，所有这些方法都缺乏化学或分子特异性，并且仅限于在后期检测疾病。快速微创和非破坏性的疾病诊断方法是一个关键的未满足的需求。诸如拉曼光谱（RS）、相干反斯托克斯拉曼散射（汽车）、二次谐波产生（SHG）和双光子荧光（TPF）的无标记技术正越来越多地用于软骨组织。然而，目前的研究是基于整个组织分析，并没有考虑软骨中不同的和结构上不同的层。在这项工作中，我们使用拉曼光谱，以获得签名的浅（顶部）和深（底部）层的健康和骨关节炎软骨样本64例（19名对照和45 OA）。在700至1720 cm-1的“指纹”区域和2500至3300 cm-1的高频拉伸区域都获得了光谱。主成分和线性判别分析被用来确定的峰值，显着贡献的不同样品的分类精度。最明显的差异是在脯氨酸（855 cm− 1和921 cm− 1）和羟脯氨酸（877 cm− 1和938 cm− 1），硫酸化糖胺聚糖（sGAG）（1064 cm− 1和1380 cm− 1）频率，以及1245 cm− 1和1272 cm− 1、1320 cm− 1和1345 cm− 1，OA样本中1451 cm− 1胶原模式发生改变，与预期的胶原结构变化一致。对照组的浅层和深层软骨的拉曼指纹光谱分析的基础上的分类精度被发现是97%和93%，使用个人/所有光谱，100%和95%，分别使用平均光谱每个病人。基于对浅层和深层的分析，对OA患病软骨进行分类，个体/所有光谱的准确度分别为88%和84%，每个患者的平均光谱的准确度分别为96%和95%。来自C-H拉伸区域（2500-3300 cm-1）的拉曼光谱导致用于鉴定不同层和OA患病软骨的高分类准确度，但用于对照的低准确度。随着年龄的增长（60岁以下和60岁以上），观察到浅层和深层软骨特征的差异性变化，相比之下，观察到的性别差异不太显著。利用汽车、SHG和TPF初步成像了软骨不同层中显著的化学变化。拉曼光谱分析显示，OA中细胞聚集，细胞周围基质和胶原结构在浅层和深层存在差异。目前的研究表明，拉曼光谱和多模态成像的潜力，询问软骨组织，并提供了深入了解其不同层的化学和结构组成的OA诊断的日益老龄化的人口的显着影响。
Osteoarthritis (OA) is a complex disease of cartilage characterised by joint pain, functional limitation, and reduced quality of life with affected joint movement leading to pain and limited mobility. Current methods to diagnose OA are predominantly limited to X-ray, MRI and invasive joint fluid analysis, all of which lack chemical or molecular specificity and are limited to detection of the disease at later stages. A rapid minimally invasive and non-destructive approach to disease diagnosis is a critical unmet need. Label-free techniques such as Raman Spectroscopy (RS), Coherent anti-Stokes Raman scattering (CARS), Second Harmonic Generation (SHG) and Two Photon Fluorescence (TPF) are increasingly being used to characterise cartilage tissue. However, current studies are based on whole tissue analysis and do not consider the different and structurally distinct layers in cartilage. In this work, we use Raman spectroscopy to obtain signatures from the superficial (top) and deep (bottom) layer of healthy and osteoarthritic cartilage samples from 64 patients (19 control and 45 OA). Spectra were acquired both in the ‘fingerprint’ region from 700 to 1720 cm− 1and high-frequency stretching region from 2500 to 3300 cm− 1. Principal component and linear discriminant analysis was used to identify the peaks that contributed significantly to classification accuracy of the different samples. The most pronounced differences were observed at the proline (855 cm− 1and 921 cm− 1) and hydroxyproline (877 cm− 1and 938 cm− 1), sulphated glycosaminoglycan (sGAG) (1064 cm− 1and 1380 cm− 1) frequencies for both control and OA as well as the 1245 cm− 1and 1272 cm− 1, 1320 cm− 1and 1345 cm− 1, 1451 cm− 1collagen modes were altered in OA samples, consistent with expected collagen structural changes. Classification accuracy based on Raman fingerprint spectral analysis of superficial and deep layer cartilage for controls was found to be 97% and 93% on using individual/all spectra and, 100% and 95% on using mean spectra per patient, respectively. OA diseased cartilage was classified with an accuracy of 88% and 84% for individual/all spectra, and 96% and 95% for mean spectra per patient based on analysis of the superficial and the deep layers, respectively. Raman spectra from the C-H stretching region (2500–3300 cm− 1) resulted in high classification accuracy for identification of different layers and OA diseased cartilage but low accuracy for controls. Differential changes in superficial and deep layer cartilage signatures were observed with age (under 60 and over 60 years), in contrast, less significant differences were observed with gender. Prominent chemical changes in the different layers of cartilage were preliminarily imaged using CARS, SHG and TPF. Cell clustering was observed in OA together with differences in pericellular matrix and collagen structure in the superficial and the deep layers correlating with the Raman spectral analysis. The current study demonstrates the potential of Raman Spectroscopy and multimodal imaging to interrogate cartilage tissue and provides insight into the chemical and structural composition of its different layers with significant implications for OA diagnosis for an increasing aging demographic.
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影响因子：
1.1
作者：
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DOI：
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2.4
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DOI：
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影响因子：
3.4
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