Current Optics and Photonics

Optical Society of Korea (한국광학회)
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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)
  • Received : 2019.09.11
  • Accepted : 2019.12.05
  • Published : 2020.02.25
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Abstract

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.

Keywords

References

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