Lung neoplasm diagnostics using Raman spectroscopy and autofluorescence analysis

Authors

  • Valery P. Zakharov Laser and biotechnical systems department, Samara State Aerospace University, Russia
  • Ivan A. Bratchenko Laser and biotechnical systems department, Samara State Aerospace University, Russia
  • Dmitry N. Artemyev Laser and biotechnical systems department, Samara State Aerospace University, Russia
  • Oleg O. Myakinin Laser and biotechnical systems department, Samara State Aerospace University, Russia
  • Dmitry V. Kornilin Laser and biotechnical systems department, Samara State Aerospace University, Russia
  • Sergey V. Kozlov Oncology Department, Samara State Medical University, Russia
  • Alexander A. Moryatov Oncology Department, Samara State Medical University, Russia

DOI:

https://doi.org/10.18287/jbpe-2015-1-1-70

Keywords:

Raman spectroscopy, autofluorescence, optical diagnostics for medicine, spectroscopy, tissue diagnostics, lung cancer

Abstract

A method of lung neoplasm diagnostics is proposed based on the combined analysis of Raman and autofluorescence spectra excited by laser beam with the wavelength 785 nm. Such approach allows fast selection of the pathology region followed by differentiation of the neoplasm type. The developed method demonstrated the sensitivity of 90.9% and the specificity of 71.4% in the differentiation of squamous cell carcinoma and adenocarcinoma cases.

References

P. Boyle, World Cancer Report 2008, International Agency for Research on Cancer, Lyon (2008).

C. D. Mathers, and D. Loncar, “Projections of global mortality and burden of disease from 2002 to 2030,” PLoS Med 3. e442 (2006).

R. J. Friedman, “The diagnostic performance of expert dermatoscopics vs a computer-vision system on small diameters melanomas,” Arch Dermatol. 144(4), 476-482 (2008).

J. Zhao, H. Lui, D.I. McLean, and H. Zeng, “Real-time Raman spectroscopy for noninvasive in vivo skin analysis and diagnosis,” New developments in biomedical engineering 24, 455-474 (2010).

Z. Huang, A. McWilliams, H. Lui, D. I. McLean, S. Lam, and H. Zeng, “Near-infrared Raman spectroscopy for optical diagnosis of lung cancer,” Int J Cancer. 107(6), 1047-1052 (2003).

J. Surmacki, J. Musial, R. Kordek, and H. Abramczyk, “Raman imaging at biological interfaces: Applications in breast cancer diagnosis,” Molecular Cancer, 12(1), 48 (2013).

P. C. Ashok, B. B. Praveen, N. Bellini, A. Riches, K. Dholakia, and C. S. Herrington, “Multi-modal approach using Raman spectroscopy and optical coherence tomography for the discrimination of colonic adenocarcinoma from normal colon,” Biomedical Optics Express 4(10), 2179-2186 (2013).

A. Pavićević, S. Glumac, J. Sopta, A. Popović-Bijelić, M. Mojović, and Goran Bačić, “Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study,” Croat Med J. 53, 551-557 (2012).

J. Zhao, H. Lui, D. I. McLean, and H. Zeng, “Real-time Raman spectroscopy for in vivo skin cancer diagnosis,” Cancer Res. 72(10), 2491-2500 (2012).

N. Bulgakova, V. Sokolov, L. Telegina, K. Vereshchagin, G. Frank, and V. Chissov, “Study of laser-induced autofluorescence emission spectra from normal and malignant bronchial epithelium,” Photonics and Lasers in Medicine 2(2), 93-99 (2013).

H. Pahlevaninezhad, A. M. D. Lee, S. Lam, C. MacAulay, and P. M. Lane, “Coregistered autofluorescence-optical coherence tomography imaging of human lung sections,” Journal of Biomedical Optics, 19(3), 036022 (2014).

M. E. Darvin, N. N. Brandt, and J. Lademann, “Photobleaching as a method of increasing the accuracy in measuring carotenoid concentration in human skin by Raman spectroscopy,” Optics and Spectroscopy (English translation of Optika i Spektroskopiya), 109(2), 205-210 (2010).

R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification, 2nd Edition, Wiley (2000).

O. Yusuke, S. Hideyuki, T. Tatsuji, F. Chie, and S. Hidetoshi, “A Discrimination analysis of human lung cancer cells associated with histological type and malignancy using Raman spectroscopy,” Journal of Biomedical Optics 15(1), 017009 (2010).

J. L. Castro, M. R. Lopez Ramirez, J. F. Arenas, and J. C. Otero, “Vibrational spectra of 3-phenylpropionic acid and L-phenylalanine,” Journal of Molecular Structure 887, 744–747 (2005).

C. De Silva, K. Czarnecki, and M.D. Ryan, “Visible and resonance Raman spectra of low valent iron porphyrins,” Inorganica Chimica Acta 287, 21-26 (1999).

C.-H. Chuang, and Y.-T. Chen, “Raman scattering of L-tryptophan enhanced by surface plasmon of silver nanoparticles: vibrational assignment and structural determination,” J. Raman Spectrosc. 40, 150–156 (2009).

C. Magnon, S. J. Hall, J. Lin, X. Xue, L. Gerber, S. J. Freedland, and P.S. Frenette, “Autonomic Nerve Development Contributes to Prostate Cancer Progression,” Science 341(6142), 1236361 (2013).

A. F. D'Adamo Jr., and F. M. Yatsu, “Acetate metabolism in the nervous system,” Journal of Neurochemistry 13(10), 961–965 (1966).

A. Barth, “The infrared absorption of amino acid side chains,” Progress in Biophysics & Molecular Biology. 74, 141–173 (2000).

P. Kupser, K. Pagel, J. Oomens, N. Polfer, B. Koksch, G. Meijer, and G. von Helden, “Amide-I and -II Vibrations of the Cyclic β-Sheet Model,” J. Am. Chem. Soc. 132(6), 2085–2093 (2010).

M. Keller, E. M. Kanter, and A. Mahadevan-Jansen, “Raman spectroscopy for cancer diagnosis” Spectroscopy 21(11), 33-41 (2006).

I. J. Bigio, and J. R. Mourant, “Optical Biopsy,” Encyclopedia of Optical Engineering, 1577-1593 (2003).

Y. Freund, and R.E. Schapire, “A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting,” Journal of Computer and System Sciences 55(1), 119-139 (1997).

N. Otsu, “A threshold selection method from gray-level histograms,” IEEE Trans. Sys. Man. Cyber. 9, 62-66 (1979).

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Published

2015-03-28

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Articles

How to Cite

Lung neoplasm diagnostics using Raman spectroscopy and autofluorescence analysis. (2015). Journal of Biomedical Photonics & Engineering, 1(1), 70-76. https://doi.org/10.18287/jbpe-2015-1-1-70