Fluorescent diagnostics of benign breast diseases and breast cancer
| Autor: | Yulia S. Korneva, Igor V. Chekurov, V. S. Maryakhina, Oksana A. Shisterova |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
lcsh:Applied optics. Photonics
Pathology medicine.medical_specialty lcsh:Medical technology Acoustics and Ultrasonics Fibrocystic Breast Disease optical biomedical diagnostics Biomedical Engineering chemistry.chemical_element Malignant transformation law.invention Biomaterials Breast cancer breast cancer law benign breast disease medicine skin and connective tissue diseases Cancer lcsh:TA1501-1820 medicine.disease Fibroadenoma Atomic and Molecular Physics and Optics Autofluorescence chemistry lcsh:R855-855.5 fluorescence Electron microscope Selenium |
| Zdroj: | Journal of Biomedical Photonics & Engineering, Vol 3, Iss 4 (2017) |
| ISSN: | 2411-2844 |
| Popis: | In the study the spectra of fluorescence excitation and autofluorescence of histological sections with different pathological processes in breast were measured. Additionally, element composition of the tissues was investigated by scanning electron microscopy. It has been shown that spectra of fluorescence excitation of benign breast diseases (fibroadenoma and fibrocystic breast disease) have low maximum at 232 nm and high maximum at 260 nm. Also, fluorescence spectra of histological samples change during tumor growth and have two maxima (335 and 420 nm). The registered spectra are result of emission of such fluorophores as fatty acids, tryptophan, NADH, vitamin B6, collagen and bilirubin. The obtained spectral data correlate well with data of element analysis. Selenium status of the tissues was investigated by scanning electronic microscope. High concentration if selenium was detected only in fibroadenoma. In breast cancer samples and fibrocystic breast disease low selenium content was detected. It may confirm higher risk for malignant transformation of fibrocystic breast disease than fibroadenoma. Our results may be helpful for cancer diagnostics and for prognosis prediction. |
| Databáze: | OpenAIRE |
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