Combining surface-enhanced Raman scattering (SERS) of saliva and two-dimensional shear wave elastography (2D-SWE) of the parotid glands in the diagnosis of Sjögren's syndrome
In this study, we combine the molecular structural information gained by SERS of saliva samples with the morphological data given by two-dimensional shear wave elastography (2D-SWE) (SuperSonic Imagine, Aixplorer) of parotid glands in the case of n = 31 patients with Sjögren's syndrome (SjS) an...
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Published in: | Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Vol. 235; p. 118267 |
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Main Authors: | , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
England
Elsevier B.V
05-07-2020
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Subjects: | |
Online Access: | Get full text |
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Summary: | In this study, we combine the molecular structural information gained by SERS of saliva samples with the morphological data given by two-dimensional shear wave elastography (2D-SWE) (SuperSonic Imagine, Aixplorer) of parotid glands in the case of n = 31 patients with Sjögren's syndrome (SjS) and n = 22 controls, with the aim to discriminate between the two groups. The overall classification accuracy yielded by a hybrid principal component analysis-linear discriminant analysis (PCA-LDA) model based on both SERS and elastography (81%) was superior to that yielded by SERS spectra alone (75%) and elastography data alone (71%). This preliminary study is the first report on the use of 2D-SWE of parotid glands for the diagnosis of SjS as well as the first to describe the diagnosis of SjS based on the SERS spectra of dried saliva samples, the results suggesting that the strategy of combining the two methods could improve the diagnosis of SjS.
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•Patients with Sjögren’s syndrome display higher shear wave modulus of parotid glands compared with control subjects•SERS analysis of dried saliva samples highlights spectral differences between patients with Sjögren’s syndrome and controls•Combined ultrasound elastography and SERS analysis yields better diagnostic accuracy than either methods alone |
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ISSN: | 1386-1425 1873-3557 |
DOI: | 10.1016/j.saa.2020.118267 |