Use of Raman spectroscopy to evaluate the biochemical composition of normal and tumoral human brain tissues for diagnosis.
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| Title: | Use of Raman spectroscopy to evaluate the biochemical composition of normal and tumoral human brain tissues for diagnosis. |
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| Authors: | Aguiar, Ricardo Pinto1 (AUTHOR), Falcão, Edgar Teixeira2 (AUTHOR), Pasqualucci, Carlos Augusto3 (AUTHOR), Silveira Jr, Landulfo1 (AUTHOR) landulfo.silveira@gmail.com |
| Source: | Lasers in Medical Science. Feb2022, Vol. 37 Issue 1, p121-133. 13p. |
| Subjects: | Raman spectroscopy, Fisher discriminant analysis, Cerebellar tumors, Brain tumors, Linolenic acids, Carotenes, Tissues, Collagen |
| 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Lasers in Medical Science is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 154982888 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Use of Raman spectroscopy to evaluate the biochemical composition of normal and tumoral human brain tissues for diagnosis. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Aguiar%2C+Ricardo+Pinto%22">Aguiar, Ricardo Pinto</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Falcão%2C+Edgar+Teixeira%22">Falcão, Edgar Teixeira</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pasqualucci%2C+Carlos+Augusto%22">Pasqualucci, Carlos Augusto</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Silveira+Jr%2C+Landulfo%22">Silveira Jr, Landulfo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> landulfo.silveira@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Lasers+in+Medical+Science%22">Lasers in Medical Science</searchLink>. Feb2022, Vol. 37 Issue 1, p121-133. 13p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Raman+spectroscopy%22">Raman spectroscopy</searchLink><br /><searchLink fieldCode="DE" term="%22Fisher+discriminant+analysis%22">Fisher discriminant analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Cerebellar+tumors%22">Cerebellar tumors</searchLink><br /><searchLink fieldCode="DE" term="%22Brain+tumors%22">Brain tumors</searchLink><br /><searchLink fieldCode="DE" term="%22Linolenic+acids%22">Linolenic acids</searchLink><br /><searchLink fieldCode="DE" term="%22Carotenes%22">Carotenes</searchLink><br /><searchLink fieldCode="DE" term="%22Tissues%22">Tissues</searchLink><br /><searchLink fieldCode="DE" term="%22Collagen%22">Collagen</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Lasers in Medical Science is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10103-020-03173-1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 121 Subjects: – SubjectFull: Raman spectroscopy Type: general – SubjectFull: Fisher discriminant analysis Type: general – SubjectFull: Cerebellar tumors Type: general – SubjectFull: Brain tumors Type: general – SubjectFull: Linolenic acids Type: general – SubjectFull: Carotenes Type: general – SubjectFull: Tissues Type: general – SubjectFull: Collagen Type: general Titles: – TitleFull: Use of Raman spectroscopy to evaluate the biochemical composition of normal and tumoral human brain tissues for diagnosis. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Aguiar, Ricardo Pinto – PersonEntity: Name: NameFull: Falcão, Edgar Teixeira – PersonEntity: Name: NameFull: Pasqualucci, Carlos Augusto – PersonEntity: Name: NameFull: Silveira Jr, Landulfo IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 02688921 Numbering: – Type: volume Value: 37 – Type: issue Value: 1 Titles: – TitleFull: Lasers in Medical Science Type: main |
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