Proof of concept clinical study for the rapid diagnosis of Lung cancer from pleural fluid using label free SERS based chemometric approach

We report a label-free Surface Enhanced Raman Spectroscopy (SERS) for pleural fluid analysis to distinguish Lung cancer from controls patients. Herein, we have used a novel silver coated silicon Nanopillar (SCSNP) as SERS substrate to acquire multiple SERS spectra for each pleural fluid sample and advanced chemometrics methods. We report a classification accuracy of 85% along with sensitivity and specificity of 87% and 83% respectively for the detection of Lung cancer over control pleural fluid samples with a receiver operating characteristics (ROC) area under curve value of 0.92 using PLS-DA binary classifier to distinguish between lung cancer over control subjects.