Surface-enhanced Raman spectroscopy of plasma for the noninvasive differentiation of renal-calculi

Renal calculi (kidney stones) that occur in human urethra is considered as one of the most painful urological disorders. Recurrence rates are close to 50%, it affects 5-15% of the population worldwide and the costs to individuals and society are high. Accurate analysis of such calculi plays a vital role in the evaluation of urolithiasis patients and in taking appropriate preventive measures to inhibit the formation or growth of kidney stones. In this paper, surface-enhanced Raman spectroscopy (SERS) was used to detect and analyze the plasma from patients with kidney stones and normal volunteer. In this preliminary experiment, principal component analysis (PCA) was used as a spectral dimensionality reduction method, and linear discriminant analysis (LDA) was used to classify the SERS spectra of plasma samples from patients with kidney stones (n=10) and healthy volunteers (n=10). The high quality SERS spectra were obtained in the range of 400-1800cm-1. The discriminant sensitivity and specificity were 80% and 100%, respectively. The difference spectrum analysis combined with the assignment of SERS bands indicated that there were subtle but significant changes between the normal and the kidney stone plasma, indicating that the contents of nucleic acids, proteins, lipids and other bio-molecules in different cell lines had special changes. The (ROC) curve of receiver performance further confirms the effectiveness of the diagnosis algorithm based on PCA-LDA. This exploratory work shows that the combination of SERS technology and PCA-LDA algorithm has great potential in the development of a label-free, non-invasive and accurate detection and screening of kidney stone.