RESUMO
OBJECTIVE: The objective of this study is to evaluate the performance and feasibility of surface-enhanced Raman spectroscopy coupled with a filter membrane and advanced multivariate data analysis on identifying and differentiating benign and malignant thyroid tumors from blood plasma. PATIENTS AND METHODS: We proposed a membrane filter SERS technology for the differentiation between benign thyroid tumor and thyroid cancer. That is to say, by using filter membranes with optimal pore size, the blood plasma samples from thyroid tumor patients were pretreated with the macromolecular proteins being filtered out prior to SERS measurement. The SERS spectra of blood plasma ultrafiltrate obtained using filter membranes from 102 patients with thyroid tumors (70 thyroid cancers and 32 benign thyroid tumors) were then analyzed and compared. Two multivariate statistical analyses, principal component analysis-linear discriminate analysis (PCA-LDA) and Lasso-partial least squares-discriminant analysis (Lasso-PLS-DA), were performed on the SERS spectral data after background subtraction and normalization, as well as the first derivative processing, to analyze and compare the differential diagnosis of benign thyroid tumors and thyroid cancer. RESULTS: SERS measurements were performed in blood plasma acquired from a total of 102 thyroid tumor patients (benign thyroid tumor N=32; thyroid cancer N=70). By using filter membranes, the macromolecular proteins in blood plasma were effectively filtered out to yield high-quality SERS spectra. 84.3% discrimination accuracy between benign and malignant thyroid tumor was achieved using PCA-LDA method, while Lasso-PLS-DA yields a discrimination accuracy of 90.2%. CONCLUSION: Our results demonstrate that SERS spectroscopy, coupled with ultrafiltration and multivariate analysis has the potential of providing a non-invasive, rapid, and objective detection and differentiation of benign and malignant thyroid tumors.
