Paraffin-Embedded Prostate Cancer Tissue Grading Using Terahertz Spectroscopy and Machine Learning
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Paraffin-Embedded Prostate Cancer Tissue Grading Using Terahertz Spectroscopy and Machine Learning Anastasia I. Knyazkova 1,2 & Alexey V. Borisov 1,3 & Lyudmila V. Spirina 3,4 & Yury V. Kistenev 1,3 Received: 13 August 2019 / Accepted: 28 January 2020/ # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
The automatic classification of paraffin-embedded prostate cancer tissue biopsy samples in terms of the Gleason scale is proposed using terahertz (THz) spectroscopy and machine learning. The samples with normal tissues (N=80) and prostate cancer tissues corresponded to the Gleason 4 (N=10), and 8 (N=13) scores, were analyzed. Absorption spectra of paraffin-embedded prostate cancer and healthy tissues were measured in the 0.2–1.5 THz range. The principal component analysis, support vector machine (SVM), and “majority vote” classification were applied to analyze experimental data. The original algorithm of spatial regions of interest selecting was developed to reduce the influence of the plastic base of a paraffin block on the results of a sample classification. The predictive model of the experimental spectral data of the paraffin blocks in the THz range was created using a set of the “One-Vs-One” binary SVM classifiers. We used multiple random splitting of the spectral data on the training and testing sets in 60%:40% proportion to teach the SVM classifiers. Validation of the predictive model showed 100% accuracy of the classification of the samples from the testing set. Keywords THz spectroscopy . Paraffin-embedded samples . Adenocarcinoma-affected tissues . Gleason scale . Machine learning
* Yury V. Kistenev [email protected]
1
Tomsk State University, 36 Lenin Ave., Tomsk 634050, Russian Federation
2
Institute of Strength Physics and Materials Science SB RAS, Academichesky Ave., 2/4, 634055 Tomsk, Russian Federation
3
Siberian State Medical University, 2 Moskovsky trakt, Tomsk 634050, Russian Federation
4
Tomsk National Research Medical Center of the RAS, 5 Kooperativny str, Tomsk 634009, Russian Federation
Journal of Infrared, Millimeter, and Terahertz Waves
1 Introduction Prostate cancer is at the second position of commonly occurring cancer for men and the fourth one among the most frequently occurring cancers overall. According to the statistics, 1.3 million new prostate cancer cases were diagnosed in 2018 [1]. The gold standard in cancer validation is a histological analysis of a tissue biopsy. To provide the ability to work with the tissue biopsy for a long time, clinicians usually use a special technique of tissue conservation, which includes the tissue dehydration, preservation, and paraffin embedding. All these steps are carried out according to the standard protocol [2]. It allows comparing results of paraffin blocks analysis anywhere. The prostate cancer stage estimation, using tissue biopsy histological analysis, is based on the Gleason grading system. The latter has become a standard since 2003 and has been widely adopted for pathologists around the world [3]. To get a
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