Current Optics and Photonics

  • 제4권1호
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  • Pages.31-43
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  • 2020
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  • 2508-7266(pISSN)
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  • 2508-7274(eISSN)
한국광학회 (Optical Society of Korea)
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Application of Terahertz Spectroscopy and Imaging in the Diagnosis of Prostate Cancer

  • Zhang, Ping (Laboratory of Optics, Terahertz and Non-Destructive Testing, School of Mechanical Engineering and Automation, Fuzhou University) ;
  • Zhong, Shuncong (Laboratory of Optics, Terahertz and Non-Destructive Testing, School of Mechanical Engineering and Automation, Fuzhou University) ;
  • Zhang, Junxi (Urology Surgery, Xiangya School of Medicine Affiliated Haikou Hospital, Central South University) ;
  • Ding, Jian (Digestive Department, the First Affiliated Hospital of Fujian Medical University) ;
  • Liu, Zhenxiang (Urology Surgery, Xiangya School of Medicine Affiliated Haikou Hospital, Central South University) ;
  • Huang, Yi (Laboratory of Optics, Terahertz and Non-Destructive Testing, School of Mechanical Engineering and Automation, Fuzhou University) ;
  • Zhou, Ning (Laboratory of Optics, Terahertz and Non-Destructive Testing, School of Mechanical Engineering and Automation, Fuzhou University) ;
  • Nsengiyumva, Walter (Laboratory of Optics, Terahertz and Non-Destructive Testing, School of Mechanical Engineering and Automation, Fuzhou University) ;
  • Zhang, Tianfu (Laboratory of Optics, Terahertz and Non-Destructive Testing, School of Mechanical Engineering and Automation, Fuzhou University)
  • 투고 : 2019.09.11
  • 심사 : 2019.12.05
  • 발행 : 2020.02.25
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초록

The feasibility of the application of terahertz electromagnetic waves in the diagnosis of prostate cancer was examined. Four samples of incomplete cancerous prostatic paraffin-embedded tissues were examined using terahertz spectral imaging (TPI) system and the results obtained by comparing the absorption coefficient and refractive index of prostate tumor, normal prostate tissue and smooth muscle from one of the paraffin tissue masses examined were reported. Three hundred and sixty cases of absorption coefficients from one of the paraffin tissues examined were used as raw data to classify these three tissues using the Principal Component Analysis (PCA) and Least Squares Support Vector Machine (LS-SVM). An excellent classification with an accuracy of 92.22% in the prediction set was achieved. Using the distribution information of THz reflection signal intensity from sample surface and absorption coefficient of the sample, an attempt was made to use the TPI system to identify the boundaries of the different tissues involved (prostate tumors, normal and smooth muscles). The location of three identified regions in the terahertz images (frequency domain slice absorption coefficient imaging, 1.2 THz) were compared with those obtained from the histopathologic examination. The tissue tumor region had a distinctively visible color and could well be distinguished from other tissue regions in terahertz images. Results indicate that a THz spectroscopy imaging system can be efficiently used in conjunction with the proposed advanced computer-based mathematical analysis method to identify tumor regions in the paraffin tissue mass of prostate cancer.

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참고문헌

  1. D. Grischkowsky, S. Keiding, M. V. Exter, and C. Fattinger, "Far-infrared time-domain spectroscopy with terahertz beams of dielectrics and semiconductors," J. Opt. Soc. Am. B 7, 2006-2015 (1990). https://doi.org/10.1364/JOSAB.7.002006
  2. N. Khiabani, Y. Huang, and Y.-C. Shen, "Comparison of ultra-wideband THz generation and detection systems," in Proc. European Conference on Antennas & Propagation (EUCAP), (Rome, Italy, May. 2011), pp. 457-461.
  3. A. J. Huber, F. Keilmann, J. Wittborn, J. Aizpurua, and R. Hillenbrand, "Terahertz near-field nanoscopy of mobile carriers in single semiconductor nanodevices," Nano Lett. 8, 3766-3770 (2008). https://doi.org/10.1021/nl802086x
  4. E. Pickwell and V. P. Wallace, "Biomedical applications of terahertz technology," J. Phys. D: Appl. Phys 38, R301 (2006).
  5. P. H. Siegel, "Terahertz technology in biology and medicine," IEEE Trans. Microwave Theory Tech. 52, 2438-2447 (2004). https://doi.org/10.1109/TMTT.2004.835916
  6. R. M. Woodward, A. J. Fitzgerald, and V. P. Wallace, "Tissue classification using terahertz pulsed imaging," Proc. SPIE 5318, 23-33 (2004).
  7. S. Zhong, Y.-C. Shen, L. Ho, R. K. May, J. A. Zeitler, M. Evans, P. F. Taday, M. Pepper, T. Rades, K. C. Gordon, R, Miller, and P. Kleinebudde, "Non-destructive quantification of pharmaceutical tablet coatings using terahertz pulsed imaging and optical coherence tomography," Opt. Lasers Eng. 49, 361-365 (2011). https://doi.org/10.1016/j.optlaseng.2010.11.003
  8. S. Zhong, "Progress in terahertz nondestructive testing: a review," Front. Mech. Eng. 14, 273-281 (2019). https://doi.org/10.1007/s11465-018-0495-9
  9. E. Pickwell, B. E. Cole, A. J. Fitzgerald, V. P. Wallace, and M. Pepper, "Simulation of terahertz pulse propagation in biological systems," Appl. Phys. Lett. 84, 2190-2192 (2004). https://doi.org/10.1063/1.1688448
  10. H.-T. Chen, S. Kraatz, G. C. Cho, and R. Kersting, "Identification of a resonant imaging process in apertureless near-field microscopy," Phys. Rev. Lett. 93, 267401 (2004). https://doi.org/10.1103/PhysRevLett.93.267401
  11. T. T. L. Kristensen, W. Withayachumnankul, P. U. Jepsen, and D. Abbott, "Modeling terahertz heating effects on water," Opt. Express 18, 4727-4739 (2010). https://doi.org/10.1364/OE.18.004727
  12. G. M. Png, R. Flook, B. W.-H. Ng, and D. Abbott, "Terahertz spectroscopy of snap-frozen human brain tissue: an initial study," Electron. Lett. 45, 343-345 (2009). https://doi.org/10.1049/el.2009.3413
  13. G. M. Png, J. W. Choi, B. W.-H. Ng, S. P. Mickan, D. Abbott, and X.-C. Zhang, "The impact of hydration changes in fresh bio-tissue on THz spectroscopic measurements," Phys. Med. Biol. 53, 3501 (2008). https://doi.org/10.1088/0031-9155/53/13/007
  14. G. M. Png, R. J. Falconer, B. M. Fischer, H. A. Zakaria, S. P. Mickan, A. P. J. Middelberg, and D. Abbott, "Terahertz spectroscopic differentiation of microstructures in protein gels," Opt. Express 17, 13102-13115 (2009). https://doi.org/10.1364/OE.17.013102
  15. B. C. Q. Truong, H. D. Tuan, V. P. Wallace, A. J. Fitzgerald, and H. T. Nguyen, "The potential of the double debye parameters to discriminate between basal cell carcinoma and normal skin," IEEE Trans. Terahertz Sci. Technol. 5, 990-998 (2015). https://doi.org/10.1109/TTHZ.2015.2485208
  16. W. C. D. Groat, "Central neural control of the lower urinary tract," in Neurobiology of Incontinence (John Wiley & Sons, England, 1990).
  17. A. M. Hovels, R. A. M. Heesakkers, E. M. Adang, G. J. Jager, S. Strum, Y. L. Hoogeveen, J. L. Severens, and J. O. Barentsz, "The diagnostic accuracy of CT and MRI in the staging of pelvic lymph nodes in patients with prostate cancer: a meta-analysis," Clin. Radiol. 63, 387-395 (2008). https://doi.org/10.1016/j.crad.2007.05.022
  18. R. W. Cootney, "Ultrasound imaging: principles and applications in rodent research," ILAR J. 42, 233-247 (2001). https://doi.org/10.1093/ilar.42.3.233
  19. M. I. Abdulmajed, D. Hughes, and I. S. Shergill, "The role of transperineal template biopsies of the prostate in the diagnosis of prostate cancer: a review," Expert Rev. Med. Devices 12, 175-182 (2014). https://doi.org/10.1586/17434440.2015.990376
  20. A. J. Fitzgerald, V. P. Wallace, M. Jimenez-Linan, L. Bobrow, R. J. Pye, A. D. Purushotham, and D. D. Arnone, "Terahertz pulsed imaging of human breast tumors," Radiology 239, 533-540 (2006). https://doi.org/10.1148/radiol.2392041315
  21. L. Duvillaret, F. Garet, and J. L. Coutaz, "A reliable method for extraction of material parameters in terahertz time-domain spectroscopy," IEEE J. Sel. Topics Quantum Electron. 2, 739-746 (2002).
  22. T. D. Dorney, R. G. Baraniuk, and D. M. Mittleman, "Material parameter estimation with terahertz time-domain spectroscopy," J. Opt. Soc. Am. A 18, 1562-1571 (2001). https://doi.org/10.1364/JOSAA.18.001562
  23. C. Cortes and V. Vapnik, "Support-vector networks," Mach. Learn. 20, 273-297 (1995). https://doi.org/10.1007/BF00994018
  24. C. J. C. Burges, "A tutorial on support vector machines for pattern recognition," Data Min. Knowl. Disc. 2, 121-167 (1998). https://doi.org/10.1023/A:1009715923555
  25. V. N. Vapnik, "An overview of statistical learning theory," IEEE Trans. Neural. Netw. 10, 988-999 (1999). https://doi.org/10.1109/72.788640
  26. J. A. K. Suykens and J. Vandewalle, "Least squares support vector machine classifiers," Neural Process. Lett. 9, 293-300 (1999). https://doi.org/10.1023/A:1018628609742
  27. S. Yamaguchi, Y. Fukushi, O. Kubota, T. Itsuji, T. Ouchi, and S. Yamamoto, "Origin and quantification of differences between normal and tumor tissues observed by terahertz spectroscopy," Phys. Med. Biol. 61, 6808 (2016). https://doi.org/10.1088/0031-9155/61/18/6808
  28. F. Wahaia, I. Kasalynas, D. Seliuta, G. Molis, A. Urbanowicz, C. D. C. Silva, F. Carneiro, G. Valusis, and P. L. Granja, "Study of gastric cancer samples using terahertz techniques," Proc. SPIE 9286, 92864H (2014).
  29. V. P. Wallace, A. J. Fitzgerald, E. Pickwell, R. J. Pye, P. F. Taday, N. Flanagan, and T. Ha, "Terahertz pulsed spectroscopy of human Basal cell carcinoma," Appl. Spectmsc. 60, 1127-1133 (2006). https://doi.org/10.1366/000370206778664635
  30. H. Chen, T.-H. Chen, T.-F. Tseng, J.-T. Lu, C.-C. Kuo, S.-C. Fu, W.- J. Lee, Y.-F. Tsai, Y.-Y. Huang, E. Y. Chuang, Y.-J. Hwang, and C.-K. Sun, "High-sensitivity in vivo THz transmission imaging of early human breast cancer in a subcutaneous xenograft mouse model," Opt. Express 19, 21552-21562 (2011). https://doi.org/10.1364/OE.19.021552
  31. P. Doradla, K. Alavi, C. S. Joseph, and R. H. Giles, "Development of terahertz endoscopic system for cancer detection," Proc. SPIE 9747, 97470F (2016).
  32. P. Doradla, C. Joseph, and R. H. Giles, "Terahertz endoscopic imaging for colorectal cancer detection: Current status and future perspectives," World J. Gastrointest. Endosc. 9, 346-358 (2017). https://doi.org/10.4253/wjge.v9.i8.346