Advertisement

In vivo Raman spectroscopic characteristics of different sites of the oral mucosa in healthy volunteers

  • Luis Felipe C. S. CarvalhoEmail author
  • Marcelo Saito NogueiraEmail author
  • Tanmoy Bhattacharjee
  • Lazaro P. M. Neto
  • Lucas Daun
  • Thiago O. Mendes
  • Ramu Rajasekaran
  • Maurílio Chagas
  • Airton A. Martin
  • Luis Eduardo S. Soares
Original Article

Abstract

Objectives

Investigate the biochemistry of in vivo healthy oral tissues through Raman spectroscopy. We aimed to characterize the biochemical features of healthy condition in oral subsites (buccal mucosa, lip, tongue, and gingiva) of healthy subjects. More specifically, we investigated Raman spectral characteristics and biochemical content of in vivo healthy tissues on Brazilian population. This characterization can be used to better define normal tissue and improve the detection of oral premalignant conditions in future studies.

Materials and methods

For spectroscopic analysis a Raman spectrometer (Kaiser Optical Systems imaging spectrograph Holospec, f / 1.8i-NIR) coupled with a laser 785 nm, 60 mW was used. Raman measurements were obtained by means of an optical fiber (EMVision fiber optic probe) coupled between the laser and the spectrometer. Three spectra per site were acquired from the lip, buccal mucosa, tongue, and gingiva of ten healthy volunteers. This resulted in 30 spectra per oral sub-site and in total 120 spectra.

Results

We report detailed biochemical information on these subsites and their relative composition based on deconvolution studies of their spectra. Finally, we also report classification efficiency of 61, 83, 41, and 93% for buccal, gingiva, lip, and tongue respectively after applying multivariate statistical tools.

Conclusions

We quantitated the contribution of various biochemicals in terms of percentage, and this will enable comparison not only across anatomical sites but also across studies. Raman spectroscopy can rapidly probe tissue biochemistry of healthy oral regions. Moreover, the study suggests the possibility of using Raman spectroscopy combined with signal processing and multivariate analysis methods to differentiate the oral sites in healthy conditions and compare with pathological conditions in future studies.

Clinical relevance

The spectral characterization of the healthy condition of oral tissues by a noninvasive, label-free, and real-time analytical techniques is important to create a spectral reference for future diagnosis of pathological conditions.

Keywords

In vivo Oral pathology Clinical 

Notes

Acknowledgments

The authors would like to acknowledge Eric Marple from EmVision LLC.

Author contributions

L. F. C. S. C. participated in the study design, spectra collection, manuscript writing, managed the data analysis, and paper final remarks; M.S.N. participated in manuscript writing and revision, data analysis, paper final remarks, carried out all the classification, and spectral pre- and post-processing presented in the section “Accuracy improvement by other normalization and classification methods”; T. B. participated in manuscript writing, data analysis, paper final remarks, and carried out the spectral deconvolution and fitting. L. P. M. N. carried out spectra collection, L. D. carried out spectra collection, T. O. M. participated in data analysis, R. R. carried out spectra collection, M. C. participated in the study design, A. A. M. participated in the study design, and L. E. S. S. participated in the paper final remarks.

Funding

The work was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP-2014/05978-1) through Luis Felipe CS Carvalho’s scholarship. Luis Felipe das Chagas and Silva de Carvalho also thank FAPESP - 2018/03636-7, and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) PNPD Odontologia - Universidade de Taubaté, and Centro Universitário Braz Cubas for the Scientific Initiation Program and Coordenação de Aperfeicoamento de Pessoal de Nível Superior (CAPES) through Tanmoy Bathacharjee’s scholarship.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by Research Ethics Committee of Universidade do Vale do Paraíba (UNIVAP) via Plataforma Brasil-Brazil (number 1132237-2015).

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. 1.
    de Carvalho LFCS et al (2010) Spectral region optimization for Raman-based optical biopsy of inflammatory lesions. Photomed Laser Surg 28:S-111–S-117.  https://doi.org/10.1089/pho.2009.2673 CrossRefGoogle Scholar
  2. 2.
    Carvalho LF et al (2015) Raman micro-spectroscopy for rapid screening of oral squamous cell carcinoma. Exp Mol Pathol 98:502–509.  https://doi.org/10.1016/j.yexmp.2015.03.027 CrossRefPubMedGoogle Scholar
  3. 3.
    Barroso EM et al (2015) Discrimination between oral cancer and healthy tissue based on water content determined by Raman spectroscopy. Anal Chem 87:2419–2426.  https://doi.org/10.1021/ac504362y CrossRefPubMedGoogle Scholar
  4. 4.
    Bonnier F et al (2012) Analysis of human skin tissue by Raman microspectroscopy: dealing with the background. Vib Spectrosc 61:124–132.  https://doi.org/10.1016/j.vibspec.2012.03.009 CrossRefGoogle Scholar
  5. 5.
    Feng X et al (2017) Raman active components of skin cancer. Biomed Optics Express 8:2835–2850.  https://doi.org/10.1364/BOE.8.002835 CrossRefGoogle Scholar
  6. 6.
    Harris AT et al (2010) Raman spectroscopy in head and neck cancer. Head Neck Oncol 2:26CrossRefGoogle Scholar
  7. 7.
    Huang Z et al (2003) Near-infrared Raman spectroscopy for optical diagnosis of lung cancer. Int J Cancer 107:1047–1052CrossRefGoogle Scholar
  8. 8.
    Malini R et al (2006) Discrimination of normal, inflammatory, premalignant, and malignant oral tissue: a Raman spectroscopy study. Biopolymers 81:179–193CrossRefGoogle Scholar
  9. 9.
    Oliveira AP, Bitar RA, Silveira L Jr, Zângaro RA, Martin AA (2006) Near-infrared Raman spectroscopy for oral carcinoma diagnosis. Photomed Laser Ther 24:348–353CrossRefGoogle Scholar
  10. 10.
    Singh S, Deshmukh A, Chaturvedi P, Krishna CM (2012) Raman spectroscopy in head and neck cancers: toward oncological applications. J Cancer Res Ther 8:126CrossRefGoogle Scholar
  11. 11.
    Singh S, Sahu A, Deshmukh A, Chaturvedi P, Krishna CM (2013) In vivo Raman spectroscopy of oral buccal mucosa: a study on malignancy associated changes (MAC)/cancer field effects (CFE). Analyst 138:4175–4182CrossRefGoogle Scholar
  12. 12.
    Venkatakrishna K et al (2001) Optical pathology of oral tissue: a Raman spectroscopy diagnostic method. Curr Sci Bangalore 80:665–668Google Scholar
  13. 13.
    Singh S, Deshmukh A, Chaturvedi P, Krishna CM (2012) In vivo Raman spectroscopic identification of premalignant lesions in oral buccal mucosa. J Biomed Opt 17:1050021–1050029CrossRefGoogle Scholar
  14. 14.
    de Paula Campos C et al (2017) Fluorescence spectroscopy in the visible range for the assessment of UVB radiation effects in hairless mice skin. Photodiagn Photodyn Ther 20:21–27.  https://doi.org/10.1016/j.pdpdt.2017.08.016 CrossRefGoogle Scholar
  15. 15.
    Saito Nogueira M, Kurachi C (2016) Assessing the photoaging process at sun exposed and non-exposed skin using fluorescence lifetime. Spectroscopy 9703:97031W.  https://doi.org/10.1117/12.2209690 CrossRefGoogle Scholar
  16. 16.
    Saito Nogueira, M. et al. (2016) Evaluation of actinic cheilitis using fluorescence lifetime spectroscopy. Proceedings of the SPIE 9703(97031U):6.  https://doi.org/10.1117/12.2209689
  17. 17.
    D’Almeida CDP, Campos C, Saito Nogueira M, Pratavieira S, Kurachi C (2015) Time-resolved and steady-state fluorescence spectroscopy for the assessment of skin photoaging process. Proc. SPIE 9531, Biophotonics South America, 953146.  https://doi.org/10.1117/12.2180975
  18. 18.
    Sahu A, Deshmukh A, Hole AR, Chaturvedi P, Krishna CM (2016) In vivo subsite classification and diagnosis of oral cancers using Raman spectroscopy. J Innov Opt Health Sci 9:1650017.  https://doi.org/10.1142/s1793545816500176 CrossRefGoogle Scholar
  19. 19.
    Kumar P, Bhattacharjee T, Ingle A, Maru G, Krishna CM (2016) Raman spectroscopy of experimental oral carcinogenesis: study on sequential cancer progression in hamster buccal pouch model. Technol Cancer Res Treat 15:NP60–NP72CrossRefGoogle Scholar
  20. 20.
    Kumar P et al (2016) Raman spectroscopy in experimental oral carcinogenesis: investigation of abnormal changes in control tissues. J Raman Spectrosc 47:1318–1326.  https://doi.org/10.1002/jrs.4977 CrossRefGoogle Scholar
  21. 21.
    Bergholt MS, Zheng W, Huang Z (2012) Characterizing variability in in vivo Raman spectroscopic properties of different anatomical sites of normal tissue in the oral cavity. J Raman Spectrosc 43:255–262.  https://doi.org/10.1002/jrs.3026 CrossRefGoogle Scholar
  22. 22.
    Crow P et al (2005) The use of Raman spectroscopy to differentiate between different prostatic adenocarcinoma cell lines. Br J Cancer 92:2166–2170.  https://doi.org/10.1038/sj.bjc.6602638 CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Feng S et al (2010) Nasopharyngeal cancer detection based on blood plasma surface-enhanced Raman spectroscopy and multivariate analysis. Biosens Bioelectron 25:2414–2419.  https://doi.org/10.1016/j.bios.2010.03.033 CrossRefPubMedGoogle Scholar
  24. 24.
    Crow P et al (2005) Assessment of fiberoptic near-infrared raman spectroscopy for diagnosis of bladder and prostate cancer. Urology 65:1126–1130.  https://doi.org/10.1016/j.urology.2004.12.058 CrossRefPubMedGoogle Scholar
  25. 25.
    Teh SK et al (2008) Diagnostic potential of near-infrared Raman spectroscopy in the stomach: differentiating dysplasia from normal tissue. Br J Cancer 98:457–465.  https://doi.org/10.1038/sj.bjc.6604176 CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Pires L, Nogueira MS, Pratavieira S, Moriyama LT, Kurachi C (2014) Time-resolved fluorescence lifetime for cutaneous melanoma detection. Biomed Opt Express 5:3080–3089.  https://doi.org/10.1364/BOE.5.003080 CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Cosci A et al (2016) Time-resolved fluorescence spectroscopy for clinical diagnosis of actinic cheilitis. Biomed Opt Express 7:4210–4219.  https://doi.org/10.1364/BOE.7.004210 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Luis Felipe C. S. Carvalho
    • 1
    • 2
    • 3
    Email author
  • Marcelo Saito Nogueira
    • 4
    Email author
  • Tanmoy Bhattacharjee
    • 5
  • Lazaro P. M. Neto
    • 6
  • Lucas Daun
    • 7
  • Thiago O. Mendes
    • 6
  • Ramu Rajasekaran
    • 7
  • Maurílio Chagas
    • 1
  • Airton A. Martin
    • 6
  • Luis Eduardo S. Soares
    • 1
  1. 1.Laboratory of Dentistry and Applied MaterialsUnivap/Instituto de Pesquisa e DesenvolvimentoSão José dos CamposBrazil
  2. 2.Faculdade De OdontologiaDa Universidade De Taubaté (Unitau)TaubateBrazil
  3. 3.Centro Universitário Braz CubasMogi das CruzesBrazil
  4. 4.Tyndall National InstituteCorkIreland
  5. 5.Laboratory of NanosensorsUnivap/Instituto de Pesquisa e DesenvolvimentoSão José dos CamposBrazil
  6. 6.Biomedical Engineering innovation Center-Biomedical Vibrational Spectroscopy GroupUniversidade Brasil-UnBrItaqueraBrazil
  7. 7.Univap/Instituto de Pesquisa e DesenvolvimentoSão José dos CamposBrazil

Personalised recommendations