ラマン分光法を使った早期の関節炎発見

タイトル: Harnessing Raman spectroscopy and Multimodal Imaging of Cartilage for Osteoarthritis Diagnosis

概要: Osteoarthritis (OA) is a complex disease of cartilage characterised by chronic joint pain, limitations in mobility and function leading to reduced quality of life. Current methods to diagnose OA, such as X- ray, MRI and the invasive synovial fluid analysis lack molecular specificity and are limited to detection of the late stages of the disease. A rapid minimally invasive and non-destructive approach for early diagnosis of OA 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 explored to characterise cartilage tissue. However, current studies are based on whole tissue analysis and do not take into account the different and structurally distinct layers in cartilage. In this work, we used Raman spectroscopy to obtain signatures from superficial and deep layers of healthy and osteoarthritic cartilage obtained from a total of 64 patients (45 OA and 19 controls). Spectra were acquired both in the fingerprint region from 700 to 1720 cm-1 and high-frequency stretching region from 2500 to 3300 cm-1. Principal component and linear discriminant analysis was used to identify the peaks that contributed the most to classification of the different samples. The most pronounced differences were observed at the proline (855 cm-1 and 921 cm-1) and hydroxyproline (877 cm-1 and 938 cm-1), sulphated glycosaminoglycan (sGAG) (1064 cm-1 and 1380 cm-1) for both control and OA as well as the 1245 cm-1 and 1272 cm-1, 1320 cm- 1 and 1345 cm-1, 1451 collagen modes 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 94% and 96%, respectively. OA diseased cartilage was classified with 80% and 87% accuracy based on analysis of the superficial and the deep layers, respectively. Raman spectra from the C-H stretching region (2500-3300 cm-1) did not result in high classification accuracies for OA diseased cartilage. Intriguingly, relatively less differences were found with gender in healthy cartilage indicating that OA brings about significant chemical changes across both genders in both layers. On the other hand, we found significant differences in superficial and deep layer cartilage signatures with age (under 60 and over 60 years). Preliminary images of different layers of cartilage using CARS, SHG and TPF showed Cell clustering in OA, and differences in pericellular matrix and collagen structure in the superficial and the deep layers. The current study demonstrates the potential of Raman Spectroscopy together with multimodal imaging as a potential tool that provides insight into the chemical and structural composition of different layers of cartilage to improve OA diagnosis.