Publication Type : Journal Article
Thematic Areas : Medical Sciences, Nanosciences and Molecular Medicine
Publisher : Journal of Materials Chemistry B
Source : Journal of Materials Chemistry B, Volume 2, Number 8, p.989-998 (2014)
Keywords : Diagnosis, Discriminant analysis, Diseases, Hierarchical Nanostructures, Hydrothermal reaction, Principal component analysis, Raman scattering, Raman spectroscopy, Relative standard deviations, Scattering cross section, Silver, squamous cell carcinoma, Substrates, Surface enhanced Raman Scattering (SERS), Surface scattering, Surface-enhanced Raman, tissue engineering, Titanium dioxide, Tumors, Vibrational signature
Campus : Kochi
School : Center for Nanosciences, School of Medicine
Center : Amrita Center for Nanosciences and Molecular Medicine Move, Nanosciences
Department : Head & Neck Surgery, Nanosciences and Molecular Medicine
Year : 2014
Abstract : The unique vibrational signatures of the biochemical changes in tissue samples may enable the Raman spectroscopic detection of diseases, like cancer. However, the Raman scattering cross-section of tissues is relatively low and hence the clinical translation of such methods faces serious challenges. In this study, we report a simple and efficient surface-enhanced Raman scattering (SERS) substrate, for the rapid and label-free detection of oral cancer. Raman active silver (Ag) surfaces were created on three distinct titania (TiO 2) hierarchical nanostructures (needular, bipyramidal and leaf-like) by a process involving a hydrothermal reaction, followed by the sputter deposition of Ag nanoparticles (average size: 30 nm). The resulting SERS substrate efficiencies, measured using crystal violet (CV) as an analyte molecule, showed a highest analytical enhancement factor of ∼106, a detection limit ∼1 nM and a relative standard deviation of the Raman peak maximum of ∼13% for the nano-leafy structure. This substrate was used to analyze tissue sections of 8 oral cancer patients (squamous cell carcinoma of tongue) comprising a total of 24 normal and 32 tumor tissue sections and the recorded spectra were analyzed by principal component analysis and discriminant analysis. The tissue spectra were correctly classified into tumor and normal groups, with a diagnostic sensitivity of 100%, a specificity of 95.83% and the average processing time per patient of 15-20 min. This indicates the potential translation of the SERS method for the rapid and accurate detection of cancer. © 2014 The Royal Society of Chemistry.
Cite this Research Publication : Girish C. M., Dr. Subramania Iyer K., Thankappan, K., Rani, V. V. D., Gowd, G. S., Dr. Deepthy Menon, Nair, S., and Dr. Manzoor K., “Rapid Detection of Oral Cancer using Ag-TiO2 Nanostructured Surface-enhanced Raman Spectroscopic Substrates”, Journal of Materials Chemistry B, vol. 2, pp. 989-998, 2014.