| Full text | |
| Author(s): |
Aguiar, Ricardo Pinto
[1]
;
Falcao, Edgar Teixeira
[2]
;
Pasqualucci, Carlos Augusto
[3]
;
Silveira, Jr., Landulfo
[1]
Total Authors: 4
|
| Affiliation: | [1] Univ Anhembi Morumbi UAM, Ctr Innovat Technol & Educ CITE, Parque Tecnol Sao Jose Campos, BR-12247106 Sao Jose Dos Campos, SP - Brazil
[2] Hosp Sao Jose, Santa Casa Misericordia Ilheus, Ladeira Vitoria 113, BR-45653420 Ilheus, BA - Brazil
[3] Univ Sao Paulo, Dept Pathol, Fac Med, Av Dr Arnaldo 455, BR-01246903 Sao Paulo, SP - Brazil
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | Lasers in Medical Science; v. 37, n. 1, p. 121-133, FEB 2022. |
| Web of Science Citations: | 2 |
| 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, 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. (AU) | |
| FAPESP's process: | 09/01788-5 - Dispersive Raman spectroscopy using optical fibers "Raman probe" applied to the diagnosis of neoplasia in the skin and prostate |
| Grantee: | Landulfo Silveira Junior |
| Support Opportunities: | Regular Research Grants |