Noninvasive liver diseases detection based on serum surface enhanced Raman spectroscopy and statistical analysis

In this paper, we investigated the feasibility of using surface enhanced Raman spectroscopy (SERS) of blood serum to discriminate liver cancer and liver cirrhosis patients from normal people. Serum taken from 44 healthy people, 45 liver cancer patients, 42 post-treatment liver cancer patients and 45 liver cirrhosis patients was measured. SERS peaks from these groups were compared and the assignments and biomedical meanings were analyzed and explained. In addition, support vector machine (SVM), partial least square-discriminant analysis (PLS-DA) and artificial neural networks (ANN) was used on the obtained SERS spectra to identify its diagnostic potential for liver diseases. PLS-SVM, PLS-DA and PLS-ANN indicated 91.5%, 89.2% and 90.3% accuracy, respectively. This preliminary study demonstrates that serum SERS can be used for liver cancer screening.