Use of Raman spectroscopy to evaluate the biochemical composition of normal and tumoral human brain tissues for diagnosis

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art_AGUIAR_Use_of_Raman_spectroscopy_to_evaluate_the_biochemical_2022.PDF (1.26 MB)
Citações na Scopus
11
Tipo de produção
article
Data de publicação
2022
DOI
Scopus
Web of Science
PubMed
Título da Revista
ISSN da Revista
Título do Volume
Editora
SPRINGER LONDON LTD
Autores
AGUIAR, Ricardo Pinto
FALCAO, Edgar Teixeira
SILVEIRA JR., Landulfo
Citação
LASERS IN MEDICAL SCIENCE, v.37, n.1, p.121-133, 2022
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Raman spectroscopy was used to identify biochemical differences in normal brain tissue (cerebellum and meninges) compared to tumors (glioblastoma, medulloblastoma, schwannoma, and meningioma) through biochemical information obtained from the samples. A total of 263 spectra were obtained from fragments of the normal cerebellum (65), normal meninges (69), glioblastoma (28), schwannoma (8), medulloblastoma (19), and meningioma (74), which were collected using the dispersive Raman spectrometer (830 nm, near infrared, output power of 350 mW, 20 s exposure time to obtain the spectra), coupled to a Raman probe. A spectral model based on least squares fitting was developed to estimate the biochemical concentration of 16 biochemical compounds present in brain tissue, among those that most characterized brain tissue spectra, such as linolenic acid, triolein, cholesterol, sphingomyelin, phosphatidylcholine, beta-carotene, collagen, phenylalanine, DNA, glucose, and blood. From the biochemical information, the classification of the spectra in the normal and tumor groups was conducted according to the type of brain tumor and corresponding normal tissue. The classification used in discrimination models were (a) the concentrations of the biochemical constituents of the brain, through linear discriminant analysis (LDA), and (b) the tissue spectra, through the discrimination by partial least squares (PLS-DA) regression. The models obtained 93.3% discrimination accuracy through the LDA between the normal and tumor groups of the cerebellum separated according to the concentration of biochemical constituents and 94.1% in the discrimination by PLS-DA using the whole spectrum. The results obtained demonstrated that the Raman technique is a promising tool to differentiate concentrations of biochemical compounds present in brain tissues, both normal and tumor. The concentrations estimated by the biochemical model and all the information contained in the Raman spectra were both able to classify the pathological groups.
Palavras-chave
Brain tumors, Diagnosis, Raman spectroscopy, Biochemical analysis
URI
https://observatorio.fm.usp.br/handle/OPI/44563
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Coleções
Artigos e Materiais de Revistas Científicas - FM/MPT
Artigos e Materiais de Revistas Científicas - LIM/22