In vivo hyperspectral analysis of skin hemoglobin and melanin content for neoplasia detection

Ivan A. Bratchenko (Login required)
Department of Laser and Biotechnical Systems, Samara National Research University, Russia

Oleg O. Myakinin
Department of Laser and Biotechnical Systems, Samara National Research University, Russia

Violetta P. Sherendak
Department of Laser and Biotechnical Systems, Samara National Research University, Russia

Pavel N. Volkhin
Department of Laser and Biotechnical Systems, Samara National Research University, Russia

Yulia A. Khristoforova
Department of Laser and Biotechnical Systems, Samara National Research University, Russia

Lyudmila A. Bratchenko
Department of Laser and Biotechnical Systems, Samara National Research University, Russia

Dmitry N. Artemyev
Department of Laser and Biotechnical Systems, Samara National Research University, Russia

Alexander A. Moryatov
Department of Oncology, Samara State Medical University, Russia

Olga V. Polschikova
Scientific and Technological Center of Unique Instrumentation, RAS, Moscow, Russia

Alexander S. Machikhin
Scientific and Technological Center of Unique Instrumentation, RAS, Moscow, Russia

Vitold E. Pozhar
Scientific and Technological Center of Unique Instrumentation, RAS, Moscow, Russia

Sergey V. Kozlov
Department of Oncology, Samara State Medical University, Russia

Valery P. Zakharov
Department of Laser and Biotechnical Systems, Samara National Research University, Russia


Paper #3310 received 17 Oct 2018; revised manuscript received 12 Dec 2018; accepted for publication 20 Dec 2018; published online 31 Dec 2018.

DOI: 10.18287/JBPE18.04.040301

Abstract

We present results of main skin chromophores (melanin and hemoglobin) optical analysis. Analysis of 91 in vivo skin tissues (50 benign and 41 malignant) was performed in visible spectral region with hyperspectral imaging technique. To assess the malignancy of skin tissues we proposed two methods for calculating the integral index of tissue optical density and performed a comparison of their effectiveness and effectiveness of physician survey. As the main diagnostic feature, we propose to use data of integral optical index dispersion from the studied tissue and healthy tissue area. The results of skin tissues classification with discriminant analysis are presented. The possibility of the proposed approaches application in the clinical practice is shown.

Keywords

Hyperspectral imaging; skin cancer; melanoma; basal cell carcinoma; skin chromophores

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References


1. F. Bray, M. Colombet, L. Mery, M. Piñeros, A. Znaor, R. Zanetti, and J. Ferlay, Cancer Incidence in Five Continents. Vol. XI, International Agency for Research on Cancer, Lyon (2017).

2. R. Siegel, D. Nai-shadham, and A. Jemal, “Cancer statistics,” CA: A Cancer Journal for Clinicians 62(1), 10-29 (2012). Crossref

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

4. A. D. Kaprin, V. V. Starinsky, and G. V. Petrova, Malignant neoplasms in Russia in 2015 (morbidity and mortality), P. A. Hertsen Moscow Oncology Research Center, Moscow (2017).

5. P. E. Gross, K. Strasser-Weippl, B. L. Lee-Bychkovsky, et al., “Challenges to effective cancer control in China, India, and Russia,” The Lancet Oncology 15(5), 489-538 (2014). Crossref

6. C. B. L. M. Majoie, F.-J. H. Hulsmans, J. A. Castelijns, A. Walter, J. Bras, and F. L. M. Peeters, “Perineural tumor extension of facial malignant melanoma: CT and MRI,” Journal of Computer Assisted Tomography 17(6), 973–975 (1993). Crossref

7. G. Argenziano, H. P. Soyer, “Dermoscopy of pigmented skin lesions - a valuable tool for early diagnosis of melanoma,” The Lancet Oncology 2(7), 443-449 (2001). Crossref

8. I. A. Bratchenko, D. N. Artemyev, O. O. Myakinin, Y. A. Khristoforova, A. A. Moryatov, S. V. Kozlov, and V. P. Zakharov, “Combined Raman and autofluorescence ex vivo diagnostics of skin cancer in near-infrared and visible regions,” Journal of Biomedical Optics 22(2), 027005 (2017). Crossref

9. L. Lim, B. Nichols, M. Migden, N. Rajaram, J. Reichenberg, M. K. Markey, M. I. Ross, and J. W. Tunnell, “Clinical study of noninvasive in vivo melanoma and nonmelanoma skin cancers using multimodal spectral diagnosis,” Journal of Biomedical Optics 19(11), 117003 (2014). Crossref

10. M. A. Calin, V. Sorin, D. Savastru, and M. Dragos, “Hyperspectral Imaging in the Medical Field: Present and Future,” Applied Spectroscopy Reviews 49(6), 435–447 (2014). Crossref

11. F. Nachbar, W. Stolz, T. Merkle, A. B. Cognetta, T. Vogt, M. Landthaler, P. Bilek, O. Braun-Falco, and G. Plewig, “The ABCD rule of dermatoscopy. High prospective value in the diagnosis of doubtful melanocytic skin lesions,” Journal of the American Academy of Dermatology 30(4), 551-559 (1994). Crossref

12. H. A. Haenssle, B. Korpas, C. Hansen-Hagge, T. Buhl, K. M. Kaune, A. Rosenberger, U. Krueger, M. P. Schön, and S. Emmert, “Seven-point checklist for dermatoscopy: performance during 10 years of prospective surveillance of patients at increased melanoma risk,” Journal of the American Academy of Dermatology 62(5), 785-793 (2010). Crossref

13. P. Bourne, C. Rosendahl, J. Keir, and A. Cameron, “BLINCK—A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings,” Dermatology Practical & Conceptual 2(2), 55-61 (2012). Crossref

14. G. Argenziano, G. Fabbrocini, P. Carli, V. De Giorgi, E. Sammarco, and M. Delfino, “Epiluminescence microscopy for the diagnosis of doubtful melanocytic skin lesions,” Archives of Dermatology 134, 1563–1570 (1998). Crossref

15. I. Bratchenko, V. Sherendak, O. Myakinin, D. Artemyev, A. Moryatov, E. Borisova, L. Avramov, L. Zherdeva, A. Orlov, S. Kozlov, and V. Zakharov, “In vivo hyperspectral imaging of skin malignant and benign tumors in visible spectrum,” Journal of Biomedical Photonics & Engineering 4(1), 010301 (2018). Crossref

16. I. Diebele, I. Kuzmina, A. Lihachev, J. Kapostinsh, A. Derjabo, L. Valeine, and J. Spigulis, “Clinical evaluation of melanomas and common nevi by spectral imaging,” Biomedical Optics Express 3(3), 467-472 (2012). Crossref

17. A. Machihin, V. Batshev, and V. Pozhar, “Aberration analysis of AOTF-based spectral imaging systems,” Journal of the Optical Society of America A 34(7), 1109-1113 (2017). Crossref

18. I. A. Bratchenko, M. V. Alonova, O. O. Myakinin, A. A. Moryatov, S. V. Kozlov, and V. P. Zakharov, “Hyperspectral visualization of skin pathologies in visible region,” Computer Optics 40(2), 240-248 (2016). Crossref

19. L. A. Zherdeva, I. A. Bratchenko, O. O. Myakinin, A. A. Moryatov, S. V. Kozlov, and V. P. Zakharov, “In vivo hyperspectral imaging and differentiation of skin cancer,” Proceedings of SPIE 10024, 100244G (2015). Crossref

20. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification, Wiley (2001).

21. K. Hajian-Tilaki, “Receiver Operating Characteristic (ROC) Curve Analysis for Medical Diagnostic Test Evaluation,” Caspian Journal of Internal Medicine 4(2), 627–635 (2013).

22. M. Brenner, V. J. Hearing, “The Protective Role of Melanin Against UV Damage in Human Skin,” Photochemistry and Photobiology 84(3), 539–549 (2008). Crossref

23. N. S. Eikje, K. Aizawa, and Y. Ozaki, “Vibrational spectroscopy for molecular characterisation and diagnosis of benign, premalignant and malignant skin tumours,” Biotechnology Annual Review 11, 191-225 (2005). Crossref

24. A. Lihachev, A. Derjabo, I. Ferulova, M. Lange, I. Lihacova, and J. Spigulis, “Autofluorescence imaging of basal cell carcinoma by smartphone RGB camera,” Journal of Biomedical Optics 20(12), 120502 (2015). Crossref

25. L. Lihacova, K. Bolocko, and A. Lihachev, “Semi-automated non-invasive diagnostics method for melanoma differentiation from nevi and pigmented basal cell carcinomas,” Proceedings of SPIE 10592, 1059206 (2017). Crossref

26. T. Nagaoka, A. Nakamura, H. Okutani, Y. Kiyohara, H. Koga, T. Saida, and T. Sota, “Hyperspectroscopic screening of melanoma on acral volar skin,” Skin Research & Technology 19(1), e290–e296 (2013). Crossref

27. A. Esteva, B. Kuprel, R. A. Novoa, J. Ko, S. M. Swetter, H. M. Blau, and S. Thrun, “Dermatologist-level classification of skin cancer with deep neural networks,” Nature 542, 115–118 (2017). Crossref






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