Ab0181 Raman Spectroscopy for Synovial Biopsy Tissue Analysis: A Proof of Concept Study

Background: Raman spectroscopy (RS) is a sensitive molecular technique that allows capturing the vibrational modes of chemical bonds in materials through the emission of photons at specific wavelengths and recording their inelastic scattering properties. These properties have attracted considerable interest in the exploitation of RS for the analysis of biological tissues, as a tool to dissect sensitively widespread changes within the cells and in the extracellular matrix, relying on limited amount of tissue. Despite initial successful results in situ and in vivo in the context of degenerative and neoplastic conditions, the analytical potential of RS in inflammatory disease remains poorly defined. Objectives: Here, we performed a proof-of-concept study evaluating the applicability of synovial tissue analysis at chemical level by RS in the context of human chronic inflammatory arthritis. We hypothesize that RS might be a tool to delineate sub-clinical and sub-histological inflammatory changes based on extremely limited amount of tissue specimens, thus potentially suitable for micro-invasive tissue sampling in difficult to target joints and disease states. Methods: Five patients with rheumatoid arthritis (RA) undergoing ultrasound-guided synovial biopsy and five patients undergoing orthopaedic non-prosthetic surgery (controls, CTRL) were enrolled. Synovial tissue from each patient was snap frozen in OCT. Parallel, 10 um tick sections were used for H&E staining and for RS. In each tissue 5 randomly selected maps were drawn within areas characterized by preserved lining layer. Each map consisted of about 450 spectra. To achieve the best spectral quality, each spectrum was acquired using a confocal Raman microscope in the fingerprint region (350-1900 cm−1) by setting an exposure time of 10 seconds, focusing the green laser source (532 nm) at 50% power, magnifying with a 20× objective and selecting 1800 L/mm grating. Raman data analysis was performed after cosmic rays removal. Savitzky–Golay filter, baseline subtraction and Asymmetric Least Squared Smoothing Baseline algorithm were selected for the pre-processing workflow. Spectra were normalized applying SNV and then cleared from OCT and noise through K-Means clustering. The resulting organic tissue-related spectra were then subjected to principal component analysis (PCA). Results: PC analysis was performed on 19732 Raman spectra over 53 maps. Less than 5% of the spectra acquired were considered not suitable for subsequent analysis. The full dataset was well separated using PCA. PC1 incorporates the highest variance (69%) and the corresponding loading plot spectrum showed well-defined positive peaks at 749, 1130 and 1585 cm-1 porphyrin groups typical molecular vibrations (myeloperoxidase) and negative peaks at 855, 1450 and 1670 cm-1 attributable to proteins. PC4 showed predominantly a lipid character as evidenced by its positive peaks at 1004, 1156, 1520 and 1657 typical of carotenoids and triglycerides, while the negative peaks express a protein character being attributable to Amide I and Amide III (Figure 1). Average PC1 per map and per patient showed a highly discriminative power between RA and CTRL with an AUC of 0.903 and 0.93, respectively. No significant correlations were observed with the Krenn's score (KS) (rho=0.061, p=0.85). Oppositely, PC4 showed a significant correlation with the KS (rho=0.928, p<0.01) despite a lower discriminative power for diagnosis. Restriction of the analysis to the samples with KS<2 (no inflammation, n=2 RA and n=2 CTRL) confirmed a significant difference in PC1 between RA and CTRL (p<0.001). The spectral variations between the CTRL and RA were further highlighted by plotting loading vectors PC1 and PC4 (Figure 2). Conclusion: Results of the current study demonstrate the applicability of RS for chemical analysis of frozen synovial tissue in human chronic inflammatory arthritis. Pilot analyses provide evidence of the potential of RS to highlight chemical differences between RA and CTRL based on the evaluation of a very limited amount of tissue over and above the histopathologic level. REFERENCES: NIL. Acknowledgements: NIL. Disclosure of Interests: None declared.