Improving sensitivity and specificity in breast cancer detection using raman spectroscopy and bayesian classification

Spectroscopy Letters

Volumn 48, Issue 1, 2015, Pages 40-52

  Martínez Romo, Julio César ^a   Luna Rosas, Francisco Javier ^a   Mendoza González, Ricardo ^a   Padilla Díaz, Alejandro ^b   Mora González, Miguel ^c   Martínez Cano, Evelia ^c  

^a INSTITUTO TECNOLÓGICO DE AGUASCALIENTES   (Mexico)

^b UNIVERSIDAD AUTÓNOMA DE AGUASCALIENTES   (Mexico)

^c UNIVERSITY OF GUADALAJARA   (Mexico)

Author keywords

Bayesian classification; breast cancer; holdout method; Raman spectroscopy; real time detection

Indexed keywords

EID: 84946175652     PISSN: 00387010     EISSN: 15322289     Source Type: Journal    
DOI: 10.1080/00387010.2013.855640     Document Type: Article

References (46)

1. American Cancer Society. September 2013. Online. http://www.cancer.org/ cancer/breastcancer/detailedguide/breast-cancer-key-statistics.
2. Bonnacio, H. Roswell Park Cancer Institute. October 2013. Online. https://www.roswellpark.org/cancertalk/201303/mammography-remains-gold-standard- breast-cancer-detection.
3. Faridah, Y. Digital versus screen film mammography: A clinical comparison. Biomed. Imaging Intervent. J. 2009, 4 (4), 1-6.
4. Beljebbar, A.; Manfait, M. Fourier transform infrared microspectroscopy for cancer diagnostic of C6 glioma on animal model. In Fourier Transforms-New Analytical Approaches and FTIR Strategies; Nikolic, G., Ed.; Intech: Rijeka, Croatia, 2013, pp. 131-146.
5. Leong, A. S.-Y.; Zhuang, Z. The changing role of pathology in breast cancer diagnosis and treatment. Pathobiology 2011, 78, 99-114.
6. Keller, M. D.; Kanter, E. M.; Mahadevan-Jansen, A. Raman spectroscopy for cancer diagnosis. Spectroscopy 2006, 22 (11). Online.
7. Tu, Q.; Chang, C. Diagnostic applications of Raman spectroscopy. Nanomed. Nanotechnol. Biol. Med. 2012, 8, 545-558.
8. Alfano, R. R.; Liu, C. H.; Sha, W. L.; Zhu, H. R.; Akins, D. L.; Cleary, J.; Prudente, R.; Cellmer, E. Human breast tissues studied by IR Fourier transform Raman spectroscopy. Lasers Life Sci. 1991, 4 (1), 23-28.
9. Shafer-Peltier, K. E.; Haka, A. S.; Fitzmaurice, M.; Crowe, J.; Myles, J.; Dasari, R. R.; Feld, M. S. Raman microespectroscopic model of human breast tissue: Implications for breast cancer diagnosis in vivo. J. Raman Spectrosc. 2002, 33, 552-563.
10. Haka, A. S.; Shafer-Peltier, K. E.; Fitzmaurice, M.; Crowe, J.; Dasari, R. S.; Feld, M. S. Diagnosing breast cancer by using Raman spectroscopy. Proc. Natl. Acad. Sci. USA 2005, 12 (35), 12371-12376.
11. Haka, A. S.; Volynskaya, Z.; Gardecki, J. A.; Nazemi, J.; Lyons, J.; Hicks, D.; Fitzmaurice, M.; Dasari, R. R.; Crowe, J. P.; Feld, M. S. In vivo margin assessment during partial mastectomy breast surgery using Raman spectroscopy. Cancer Res. 2006, 66, 3317-3322.
12. Motz, J. T.; Hunter, M.; Galindo, L. H. Optical fiber probe for biomedical Raman spectroscopy. Appl. Opt. 2004, 43, 542-554.
13. Jolliffe, I. T. Principal Component Analysis; Springer Series in Statistics, 2nd ed.; Springer-Verlag: New York, 2002; 487 pp.
14. Andrade-Bitar, R.; da Silva-Martinho, H.; Zambelli-Ramalho, L. N.; Rodrigues dos Santos Junior, A.; Silva-Ramalho, F.; Raniero, L.; Martin, A. A. In Biomedical Vibrational Spectroscopy V: Advances in Research and Industry. Proc. SPIE 8219, California, USA, January 29, 2012, pp. 141-147.
15. Pichardo-Molina, J. L.; Frausto-Reyes, C.; Barbosa-García, O.; Huerta-Franco, R.; González-Trujillo, J. L.; Ramírez-Alvarado, C. A.; Gutiérrez-Juárez, G.; Medina-Gutiérrez, C. Raman spectroscopy and multivariate analysis of serum samples from breast cancer patients. Lasers Med. Sci. 2007, 22 (4), 229-236.
16. Chalmers, J. M.; Griffiths, P. R. Handbook of Vibrational Spectroscopy, Vol. 5. Application in Life, Pharmaceutical and Natural Science; Wiley: New York, 2002, 3862 pp.
17. Choi, J.; Choo, J.; Chung, H.; Gweon, D. G.; Park, J.; Kim, H. J.; Park, S.; Oh, C. H. Direct observation of spectral differences between normal and basal cell carcinoma (BCC) tissues using confocal Raman spectroscopy. Biopolymers 2005, 77, 264-272.
18. Wu, Y.; McEwen, G. D.; Harihar, S.; Baker, S. M.; DeWald, D. B.; Zhou, A. BRMS1 expression alters the ultrastructural, biomechanical and biochemical properties of MDA-MB-25 human breast carcinoma cells: An AFM and Raman microspectrosctopy study. Cancer Lett. 2010, 293, 82-91.
19. Duraipandian, S.; Bergholt, M. S.; Zheng, W.; Yu-Ho, K.; Teh, M.; Yeoh, K. G.; Yan-So, J. B.; Shabbir, A.; Huang, Z. Real-time Raman spectroscopy for in vivo, online gastric cancer diagnosis during clinical endoscopic examination. J. Biomed. Opt. 2012, 17 (8), 0814181-0814188.
20. Motz, J. T.; Gandhi, S. J.; Scepanovic, O. R.; Haka, A. S.; Kramer, J. R.; Dasari, R. R.; Feld, M. S. Real-time Raman system for in vivo disease diagnosis. J. Biomed. Opt. 2005, 10 (3), 0311131-0311137.
21. Bishop, C. M. Pattern Recognition and Machine Learning; Springer-Verlag: New York, 2006; 738 pp.
22. Duda, R. O.; Hart, P. E.; Stork, D. G. Pattern Classification, 2nd ed.; John Wiley & Sons, Inc.: New York, 2000; 680 pp.
23. Chowdary, M. V. P.; Kaylan-Kumar, K.; Mathew, S.; Rao, L.; Murali-Krishna, C.; Kurien, J. Biochemical correlation of Raman spectra of normal, benign and malignant breast tissues: a spectral deconvolution study. Biopolymers 2009, 91 (7), 539-546.
24. Lui, H.; Zhao, J.; McLean, D. Real-time Raman spectroscopy for in-vivo skin cancer diagnosis. Cancer Res. 2012, 72, 2491-2500.
25. Widjaja, E.; Zheng, W.; Huang, Z. Classification of colonic tissues using near-infrared Raman spectroscopy and support vector machines. Int. J. Oncol. 2007, 32, 653-662.
26. Barman, I.; Chari-Dingari, N.; Saha, A.; McGee, S.; Galindo, L. H.; Liu, W.; Plecha, D.; Klein, N.; Rao-Dasari, R.; Fitzmaurice, M. Application of Raman spectroscopy to identify microcalcifications and underlying breast lesions at stereotactic core needle biopsy. Cancer Res. 2013, 73 (11), 3206-3215.
27. Sattlecker, M.; Bessant, C.; Smith, J.; Stone, N. Investigation of support vector machines and Raman spectroscopy for lymph node diagnostics. Analyst 2010, 135, 895-901.
28. Zhou, Y.; Liu, C.; Li, J.; Zhou, L.; He., Sun, Y.; Pu, Y.; Zhu, K.; Liu, Y.; Li, Q.; Cheng, G.; Alfano, R. R. In Proc. SPIE 8577 Optical Biopsy XI, California, Feb. 2-7, 2013.
29. Lyng, F.; Gazi, E.; Gardner, P. Preparation of tissues and cells for infrared and Raman spectroscopy and imaging. In Biomedical Applications of Synchrotron Infrared Microspectroscopy, D. Moss, Ed.; RSC Analytical Spectroscopy Monographs, No. 11, Royal Society of Chemistry, 2011, 147-185.
30. Huang, Z.; McWilliams, A.; Lam, S.; English, J.; McLean, D. I.; Lui, H.; Zeng, H. Effect of formalin fixation on the near-infrared Raman spectroscopy of normal and cancerous human bronchial tissues. Int. J. Oncol. 2003, 23, 649-655.
31. Orfanidis, S. J. Introduction to Signal Processing; Prentice-Hall: Upper Saddle River, NJ, 1996; 798 pp.
32. Cao, A.; Pandya, A. K.; Serhatkulu, G. K.; Weber, R. E.; Dai, H.; Thakur, J. S.; Naik, V. M.; Naik, R.; Aunner, G. W.; Rabah, R.; Freeman, D. C. A robust method for automated background subtraction of tissue fluorescence. J. Raman Spectrosc. 2007, 38 (9), 1199-1225.
33. Zhao, J.; Lui, H.; McLean, D. I.; Zeng, H. Real-time Raman spectroscopy for noninvasive in vivo skin analysis and diagnosis. In New Developments in Biomedical Engineering; Campolo, D., Ed.; InTech: Austria, 2010; 455-474.
34. Zhao, J.; Lui, H.; McLean, D. I.; Zeng, H. Automated autofluorescence background subtraction algorithm for biomedical Raman spectroscopy. Appl. Spectrosc. 2007, 61 (11), 1225-1232.
35. Huang, N.; Short, M.; Zaho, J.; Wang, H.; Lui, H.; Korbelik, M.; Zeng, H. Full characterization of the Raman spectra of organs in a murine model. Opt. Exp. 2011, 19 (23), 22892-22909.
36. Rinnan, A.; Berg, F.; Engelsen, S. B. Review of the most common pre-processing techniques for near-infrared spectra. Trends Anal. Chem. 2009, 28 (10), 1201-1222.
37. Zheng, F.; Chen, K. Sensitivity map of laser tweezers Raman spectroscopy for single-cell analysis of colorectal cancer. J. Biomed. Opt. 2007, 12, 034002.
38. Koutroumbas, K.; Theodoridis, S. Pattern Recognition, 4th ed.; Academic Press: San Diego, CA, 2008; 984 pp.
39. Abramczyc, H.; Brozek-Pluzka, B.; Surmacki, J.; Jablonska, J.; Kordek, R. The label-free Raman imaging of human breast cancer. J. Mol. Liquids 2011.
40. Abramczyk, H.; Surmacki, J.; Brozek-Pluska, B.; Morawiec, Z.; Tazbir, M. The hallmarks of breast cancer by Raman spectroscopy. J. Mol. Struct. 2009, 924 (926), 175-182.
41. Abramczyk, H.; Brozek-Pluska, B.; Surmacki, J.; Jablonska-Gajewicz, J.; Kordek, R. Raman optical biopsy of human breast cancer. Progr. Biophys. Molec. Biol. 2012, 108, 74-81.
42. Brozek-Pluska, B.; Placek, I.; Kurczewski, K.; Morawiec, Z.; Tazbir, M.; Abramczyk, H. Breast cancer diagnostics by Raman spectroscopy. J. Mol. Liquids 2008, 141, 145-148.
43. What-when-how: In-depth tutorials and information. February 2013. Online. http://what-when-how.com/molecular-biology/vibrational-spectrocopy-part-1- molecular-biology
44. De Gelder, J.; De Gussem, K.; Vandenabeele, P.; Moens, L. Reference database of Raman spectra of biological molecules. J. Raman Spectrosc. 2007, 38, 1133-1147.
45. Haka, A. S.; Shafer-Peltier, K. E.; Fitzmaurice, M.; Crowe, J.; Dasari, R. R.; Feld, M. S. Identifying microcalcifications in benign and malignant breast lesions by probing differences in chemical composition using Raman spectroscopy. Cancer Res. 2002, 62, 5375-5380.
46. Tsoukalas, L. H.; Uhrig, R. E. Fuzzy and Neural Approaches in Engineering; John Wiley & Sons, Inc.: New York, 1997; 224 pp.