CC BY
2*
ALT'23
The 30th International Conference on Advanced Laser Technologies
B-I-16
Multimodal approach to the diagnosis of human skin cancer in vivo
E. Genina12, I. Serebryakova12, Y. Surkov12, Y. Kuzinova3, E. Lazareva12, O. Konopatskova3,
V. Tuchin12,4
1-Institution of Physics, Saratov State University, 83, Astrakhanskaya St., Saratov, 410012 Russia 2- Laboratory of Laser Molecular Imaging and Machine Learning, National Research Tomsk State University, 36, Lenin Ave.,
Tomsk, 634050 Russia
3- Department of Faculty Surgery and Oncology, Saratov State Medical University, 112, Bolshaya Kazachya St., Saratov, 410012
Russia
4- Institute of Precision Mechanics and Control, FRC "Saratov Scientific Centre of the Russian Academy of Sciences", 24, Rabo-
chaya St., Saratov, 410028 Russia
eagenina@yandex. ru
Despite the development of medicine, cancer remains one of the most dangerous diseases nowadays. Many recent technological innovations have used physics principles, such as optics and coherent photonics, to improve early diagnostic and therapeutic procedures to reduce cancer incidence and mortality. In this study, the development of technologies for biomedical imaging of skin cancer is presented. Modern optical technologies combined with optical clearing of tissues based on reducing light scattering in tissues by partially replacing interstitial fluid with biologically compatible hyperosmotic immersion agents, increase the effectiveness of optical cancer diagnostics methods.
The study involved 60 neoplasms in 38 volunteers of both sexes (benign neoplasms was 13 and BCC was 47). A combination of high-resolution ultrasound examination and optical methods (Raman spectroscopy, optical coherence tomography (OCT), and backscattered diffuse reflectance spectroscopy) with biocompatible optical clearing agents was used for the study of basal cell carcinoma (BCC) and benign neoplasms in humans.
Texture analysis of pixel brightness changes within the area of interest in OCT images allowed us to differentiate various types of BCC, melanoma, and benign neoplasms (Fig. 1).
Fig. 1. OCT images of several types of BCC: a) Infiltrative-ulcerative, b) Superficial, c) Pigmented, and d) Morpheaform, and differentiation of these types using statistical parameters of texture analysis of OCT images:: e) Skewness and Mean and f) Entropy and Homogeneity.
Our results demonstrated the ability of these modalities to quantitatively assess tissue biochemical, structural, and physiological parameters that can be used to determine tissue pathology. This work was supported by the grant of RFBR # 20-52-56005.
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