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

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Abstract

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, β-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.

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Acknowledgments

Silveira Jr. thanks FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) for the acquisition of the Raman spectrometer (Proc. No. 2009/01788-5) and CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) for the research productivity fellowship (Process No. 306344/2017-3). R. P. Aguiar thanks CAPES (Coordination for the Improvement of Higher Education Personnel) and UAM (Universidade Anhembi Morumbi) for their doctoral fellowship.

Funding

This study has been supported in part by FAPESP (São Paulo Research Foundation, Brazil) who granted the Raman spectrometer (Grant No. 2009/01788-5).

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Authors and Affiliations

  1. Center for Innovation, Technology and Education – CITÉ, Universidade Anhembi Morumbi – UAM, Parque Tecnológico de São Jose dos Campos, Estr. Dr. Altino Bondensan, 500, São José dos Campos, SP, 12247-106, Brazil

    Ricardo Pinto Aguiar & Landulfo Silveira Jr

  2. Hospital São José, Santa Casa de Misericórdia de Ilhéus, Ladeira da Vitória, 113, Ilhéus, BA, 45653-420, Brazil

    Edgar Teixeira Falcão

  3. Department of Pathology, Faculty of Medicine, Universidade de São Paulo – USP, Av. Dr. Arnaldo, 455, São Paulo, SP, 01246-903, Brazil

    Carlos Augusto Pasqualucci

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  1. Ricardo Pinto Aguiar
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  2. Edgar Teixeira Falcão
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  3. Carlos Augusto Pasqualucci
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  4. Landulfo Silveira Jr
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Correspondence to Landulfo Silveira Jr.

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This study complies with the Resolution No. 466/2012, of the Brazilian National Health Council and was approved by the Research Ethics Committee of the Universidade Brasil, São Paulo, SP, Brazil, protocol no. 1,903,652 of 02/01/2017.

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Aguiar, R.P., Falcão, E.T., Pasqualucci, C.A. et al. Use of Raman spectroscopy to evaluate the biochemical composition of normal and tumoral human brain tissues for diagnosis. Lasers Med Sci 37, 121–133 (2022). https://doi.org/10.1007/s10103-020-03173-1

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