Tobacco Consumption Induced Changes in the Healthy Oral Mucosa and its Effect on Differential Diagnosis of Oral Lesions - A Clinical In Vivo Raman Spectroscopic Study


  • Hemant Krishna Homi Bhabha National Institute, Raja Ramanna Centre for Advanced Technology, Indore- 452013, India
  • Sidramesh Muttagi Department of Head and Neck Surgery, Tata Memorial Hospital, Mumbai-400012, India
  • Pranav Ingole Department of Head and Neck Surgery, Tata Memorial Hospital, Mumbai-400012, India
  • Pankaj Chaturvedi Department of Head and Neck Surgery, Tata Memorial Hospital, Mumbai-400012, India
  • Shovan Kumar Majumder Homi Bhabha National Institute, Raja Ramanna Centre for Advanced Technology, Indore- 452013, India



In vivo Raman spectroscopy, tobacco consumption induced changes, oral mucosa, probability based multivariate diagnostic algorithm, multi-class classification of oral lesions, maximum representation and discrimination feature (MRDF), sparse multinomial logistic regression (SMLR).


 Objective: To investigate tobacco consumption induced changes in the in vivo Raman spectra of oral mucosa of healthy volunteers and to study its effect on the differential diagnosis of oral lesions. Materials and Methods: The clinical in vivo study involved 28 healthy volunteers and 171 patients having malignant and potentially malignant lesions of the oral cavity. Twenty of the healthy volunteers had habits of either smoking and/or of chewing tobacco while the rest did not have any tobacco consumption habits. The in vivo Raman spectra were measured using a compact and portable near-infrared Raman spectroscopic system. A probability based multi-class diagnostic algorithm, developed for supervised classification, was employed to classify the whole set of measured tissue Raman spectra into various categories. Results: It was found that the Raman spectra of healthy volunteers with tobacco consumption habits could be separated from the spectra of those without any habit of tobacco consumption with an accuracy of over 95%. Further, it was found that exclusion of the spectral data of the oral cavity of the healthy volunteers from the reference normal database considerably improved the overall classification accuracy (92.3% as against 86%) of the algorithm in separing the oral lesions from the normal oral mucosa. Conclusion: The results of the clinical study demonstrate the potential of Raman spectroscopy in screening tobacco users who are at an increased risk of developing dysplasia or malignancy. Further, the results also show that for accurate discrimination of oral lesions based on their Raman spectra, the reference normal database should exclude spectral data of tobacco using healthy subjects.


Sham A, Cheung LK, Jin LJ, Corbet EF. The effects of tobacco use on oral health. Hong Kong Med J 2003; 9: 271-7.

Boffetta P, Hecht S, Gray N, Gupta P, Straif K. Smokeless tobacco and cancer. Lancet Oncol 2008; 9: 667-75.

Rastogi T, Devesa S, Mangtani P, et al. Cancer incidence rates among South Asians in four geographic regions: India, Singapore, UK and US. Int J Epidemiol 2008; 37: 147-60.

American Cancer Society. Global cancer facts & figures. 3rd ed. Atlanta: American Cancer Society; 2015. Available from:

El-Mofty S. Early detection of oral cancer. Egypt J Oral Maxillofac Surg 2010; 1: 25-31.

Garg P, Karjodkar F. Catch them before it becomes too late- oral cancer detection. Report of two cases and review of diagnostic AIDS in cancer detection. Int J Prev Med 2012; 3: 737-41.

Epstein JB, Zhang L, Rosin M. Advances in the diagnosis of oral premalignant. J Can Dent Assoc 2002; 68: 617-21.

Mahadevan-Jansen A. Raman Spectroscopy: From Benchtop to Bedside. In: Vo-Dinh T editor. Biomedical photonics handbook, Washington DC: CRC Press, 2003; Chapter 30.

Chen P, Shen A, Zhou X, Hu J. Bio-Raman spectroscopy: A potential clinical method assisting in disease diagnosis. Anal Methods 2011; 3: 1257-69.

Lieber CA, Majumder SK, Ellis DL, Billheimer DD, Mahadevan-Jansen A. In-vivo non melanoma skin cancer diagnosis using Raman micro spectroscopy. Lasers Surg Med 2008; 40: 461-7.

Haka AS, Volynskaya Z, Gardecki JA et al. In vivo margin assessment during partial mastectomy breast surgery using Raman spectroscopy. Cancer Res 2006; 66: 3317-22.

Teh SK, Zheng W, Ho KY, Teh M, Yeoh KG, Huang Z. Diagnostic potential of near-infrared Raman spectroscopy in the stomach: differentiating dysplasia from normal tissue. Br J Cancer 2008; 98: 457-65.

Bergholt MS, Zheng W, Lin K et al. Combining near infrared-excited autofluorescence and Raman spectroscopy improves in-vivo diagnosis of gastric cancer. Biosens Bioelectron 2011; 26: 4104-10.

Stone N, Kendall CA. Raman spectroscopy for early cancer detection, diagnosis and elucidation of disease specific biochemical changes. In: Pavel M, Morris M D editors. Emerging Raman Applications and Techniques in Biomedical and Pharmaceutical Fields, Berlin: Springer 2010; p. 315-46.

Malini R, Venkatakrishna K, Kurien J, et al. Discrimination of normal, inflammatory, premalignant, and malignant oral tissue: A Raman spectroscopy study. Biopolymers 2006; 81: 179-93.

Li Y, Wen ZN, Li LJ, Li ML, Gao N, Guo YZ. Research on the Raman spectral character and diagnostic value of squamous cell carcinoma of oral mucosa. J Raman Spectrosc 2010; 41: 142-47.

Guze K, Short M, Zeng H, Lermana M, Sonis S. Comparison of molecular images as defined by Raman spectra between normal mucosa and squamous cell carcinoma in the oral cavity. J Raman Spectrosc 2011; 42: 1232-9.

Sunder NS, Rao NN, Kartha VB, Ullas G, Kurien J. Laser Raman spectroscopy: A novel diagnostic tool for oral cancer. J Orofac Sci 2011; 3: 15-9.

Deshmukh A, Singh SP, Chaturvedi P, Krishna CM. Raman spectroscopy of normal oral buccal mucosa tissues: study on intact and incised biopsies. J Biomed Opt 2011; 16: 127004.

Devpura S, Thakur JS, Dethi S, Naik VM, Naik R. Diagnosis of head and neck squamous cell carcinoma using Raman spectroscopy: Tongue tissue. J Raman Spectrosc 2012; 43: 490-6.

Su L, Sun YF, Chen Y, Chen et al. Raman spectral properties of squamous cell carcinoma of oral tissues and cells. Laser Phys 2012; 22: 311-6.

Schut TCB, Witjes MJH, Sterenborg HJCM, et al. In-vivo detection of dysplastic tissue by Raman spectroscopy. Anal Chem 2000; 72: 6010-8.

Oliveira AP, Bitar RA, Silveria L, Zangaro RA, Martin AA. Near-Infrared Raman spectroscopy for oral carcinoma diagnosis. Photomed Laser Surg 2006; 24: 348-53.

Guze K, Short M, Sonis S, Karimbux N, Chan J, Zeng H. Parameters defining the potential applicability of Raman spectroscopy as a diagnostic tool for oral disease. J Biomed Opt 2009; 14: 014016.

Bergholt MS, Zheng W, Huang Z. Characterizing variability in in-vivo Raman spectroscopic properties of different anatomical sites of normal tissue in the oral cavity. J Raman Spectrosc 2012; 43: 255-62.

Singh SP, Deshmukh A, Chaturvedi P, Krishna CM. In vivo Raman spectroscopic identification of premalignant lesions in oral cavity. J Biomed Opt 2012; 17: 105002.

Sahu A, Deshmukh A, Ghanate AD, Singh SP, Chaturvedi P, Krishna CM. Raman spectroscopy of oral buccal mucosa: A study on age-related physiological changes and tobacco-related pathological changes. Technol Cancer Res Treat 2012; 11: 529-41.

Sahu A, Tawde S, Venkatesh P, et al. Raman spectroscopy and cytopathology of oral exfoliated cells for oral cancer diagnosis, Anal Methods 2015; 7: 7548-59.

Krishna H, Majumder SK, Muttagi S, Chaturvedi P, Gupta PK. In vivo Raman spectroscopy for detection of oral neoplasia: A pilot clinical study. J Biophotonics 2014; 7: 690-702.

Krishna H, Majumder SK, Chaturvedi P, Gupta PK, Anatomical variability of in-vivo Raman spectra of normal oral cavity and its effect on oral tissue classification. Biomed Spectrosc Imaging 2013; 2: 199-217.

Krishna H, Majumder SK, Gupta PK. Range-independent background subtraction algorithm for recovery of Raman spectra of biological tissue. J Raman Spectrosc 2012; 43: 1884-94.

Cohen J. Statistical power analysis for the behavioral sciences. 2nd edn. New Jersey: Lawrence Erlbaum Associates; 1988.

Majumder SK, Gebhart SC, Johnson MD, Thompson R, Lin WC, Mahadevan-Jansen A. A probability-based spectroscopic diagnostic algorithm for simultaneous discrimination of brain tumor and tumor margins of normal brain tissue. Appl Spectrosc 2007; 61: 548-57.

Talukder A. Nonlinear feature extraction for pattern recognition applications. PhD Thesis, Pennsylvania: Carnegie Mellon University, 1999.

Krishnapuram B, Cari L, Figueiredo MAT. Sparse multinomial logistic regression: Fast algorithums and generalization bounds. IEEE Trans Pattern Anal Machine Intell 2005; 27: 957-68.

Majumder SK, Keller MD, Boulos FI, Kelley MC, Mahadevan-Jansen A. Comparison of autofluorescence, diffuse reflectance, and Raman spectroscopy for breast tissue discrimination. J Biomed Opt 2008; 13: 054009.

Hand DJ, Till RJ. A simple generalization of the area under the ROC curve for multiclass classification problems. Mach Learn 2001; 45: 171-86.

Khanna A, Gautam DS, Mukherjee P. Genotoxic effects of tobacco chewing. Toxicol Int 2012; 19: 322-6.

Doll R, Peto R, Wheatley K, Gray R, Sutherland I. Mortality in relation to smoking: 40 years' observation on male British doctors. Br Med J 1994; 309: 901-11.

Wall MA, Johnson J, Jacob P, Benowitz NL. Cotinine in the serum, saliva, and urine of nonsmokers, passive smokers, and active smokers. Am J Public Health. 1988; 78: 699-701.

Al-Delaimy WK, Hair as a biomarker for exposure to tobacco smoke. Tob Control 2002; 11: 176-82.

Tipton DA, Dabbous MK. Effects of nicotine on proliferation and extracellular matrix production of human gingival fibroblasts in vitro. J Periodontol 1995; 66: 1056-64.

Taybos G. Oral changes associated with tobacco use. Am J Med Sci 2003; 326: 179-82.

Cortes C, Vapnik V. Support-vector networks. Mach Learn 1995; 20: 273-297.

Jolliffe IT. Principal Component Analysis. 2nd ed. New York: Springer; 2002.

Duda RO, Hart PE,Stork DG. Pattern Classification. 2nd ed. New York: Wiley 2001.




How to Cite

Hemant Krishna, Sidramesh Muttagi, Pranav Ingole, Pankaj Chaturvedi, & Shovan Kumar Majumder. (2016). Tobacco Consumption Induced Changes in the Healthy Oral Mucosa and its Effect on Differential Diagnosis of Oral Lesions - A Clinical In Vivo Raman Spectroscopic Study. Journal of Analytical Oncology, 5(3),  110–123.




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