弹性成像
唾液
线性判别分析
主成分分析
化学
病理
生物医学工程
材料科学
医学
放射科
内科学
人工智能
超声波
计算机科学
作者
Vlad Moisoiu,Maria Bădărînză,Andrei Ştefancu,Ștefania D. Iancu,Oana Șerban,Nicolae Leopold,Daniela Fodor
标识
DOI:10.1016/j.saa.2020.118267
摘要
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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