Abstract
Discrimination and identification of melanoma (a kind of skin cancer) by using laser-induced breakdown spectroscopy (LIBS) combined with chemometrics methods are reported. The human melanoma and normal tissues are used in the form of formalin-fixed paraffin-embedded (FFPE) blocks as samples. The results demonstrated higher LIBS signal intensities of phosphorus (P), potassium (K), sodium (Na), magnesium (Mg), and calcium (Ca) in melanoma FFPE samples while lower signal intensities in normal FFPE tissue samples. Chemometric methods, artificial neural network (ANN), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and partial least square discriminant analysis (PLS-DA) are used to build the classification models. Different preprocessing methods, standard normal variate (SNV), mean-centering, normalization by total area, and autoscaling, were compared. A good performance of the model (sensitivity, specificity, and accuracy) for melanoma and normal FFPE tissues has been achieved by the ANN and PLS-DA models (all were 100%). The results revealed that LIBS combined with chemometric methods for detection and discrimination of human malignancies is a reliable, accurate, and precise technique.
Highlights
Cancer is an increasing concern worldwide and has become a major threat to human health. e leading causes of death are still due to various types of cancers
For the identification and diagnosis of melanoma skin cancer analytical methods such as synchrotron radiation microanalysis (SXRF) [1,2,3], or transmission electron microscopy combined with energy dispersive X-ray analysis (TEM-EDX) [4, 5], laser ablation inductively coupled plasma spectrometry, mass spectrometry (LA-ICP-MS) [5,6,7,8], and Raman Spectroscopy are already used [9]
In terms of laser-induced breakdown spectroscopy (LIBS) sensitivity and spatial resolution with other techniques such as LA-ICP-MS, TEM, Nano-SIM, EPMA, TEM, and SEM, as indicated in [1], which illustrated that LIBS achieves micrometer scale resolution with part-per-million range sensitivities. e
Summary
Cancer is an increasing concern worldwide and has become a major threat to human health. e leading causes of death are still due to various types of cancers. E performances of the models are determined in terms of accuracy, sensitivity, and specificity along with suitable preprocessing methods, and reported P (phosphorus) line of the FFPE tissue samples, while the above-reported results about melanoma references [13, 15] did not report any P lines in their spectra because of mice samples (tissue, pellets, and blood) and early melanoma diagnosis. Based on these results, we analysed distinguishable elements from melanoma FFPE tissues, reflecting the clinical situation
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