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Journal Nanotechnology : the development , application - XXI Century №3 for 2023 г.
Article in number:
Microwave radiometry of breast: current state and ways of improvement
Type of article: scientific article
DOI: https://doi.org/10.18127/j22250980-202303-02
UDC: 621.382
Authors:

S.G. Vesnin1, M.K. Sedankin2

1,2 Bauman Moscow State Technical University (National Research University) (Moscow, Russia)
1 LLC “Firm “RES” (Moscow, Russia)
2 NIA “Moscow Power Engineering Institute” (Moscow, Russia)
 

Abstract:

Detection of breast cancer using microwave radiometry is still the most important area of application of the method of considerable interest. It is necessary to deepen research in the field of microwave radiometry of the breast and increase the effectiveness of diagnosis and control of treatment of diseases of the breast.

Objective – to acquaint the reader with the current situation in the field of microwave radiometry of the breast, the results achieved and the tasks of future research.

The description of the microwave radiothermograph, which was used for research and clinical trials to detect breast cancer, technical aspects of measuring the breast's own radiation in the microwave range, ways to solve the tasks and development prospects are presented.

Numerous studies conducted in the last 20 years have demonstrated the significant potential of microwave radiometry in the field of breast oncology. Microwave radiometry is an effective method of functional diagnosis and control of treatment of various diseases of the breast.

Pages: 11-22

Vesnin S.G., Sedankin M.K. Microwave radiometry of breast: current state and ways of improvement. Nanotechnology: development and applications – XXI century. 2023. V. 15. № 3. P. 11–22. DOI: https://doi.org/10.18127/j22250980-202303-02 (in Russian)

References
  1. Gautherie m. temperature and blood flow patterns in breast cancer during natural evolution and following radiotherapy. Biomedical Thermology. 1982. P. 21–64.
  2. Gautherie M., Gros C.M. Breast thermography and cancer risk prediction. Cancer. 1980. V. 45. P. 51–56.
  3. Vesnin S.G., Kaplan M.A., Avakyan R.S. Sovremennaya mikrovolnovaya radiotermometriya molochnyh zhelez. Opuholi zhenskoj reproduktivnoj sistemy. 2008. № 3. S. 28–35 (in Russian).
  4. Yahara T., Koga T., Yoshida S., Nakagawa S., Deguchi H., Shirouzu K. Relationship between microvessel density and thermographic hot areas in breast cancer. Surgery Today. 2003. V. 33. P. 243–248.
  5. Losev A.G. i dr. Problemy izmereniya i modelirovaniya teplovyh i radiacionnyh polej v biotkanyah: analiz dannyh mikrovolnovoj termometrii. Matematicheskaya fizika i komp'yuternoe modelirovanie. 2015. № 6. S. 31–71 (in Russian).
  6. Barrett A.H., Myers P.C. Subcutaneous temperature: a method of noninvasive sensing. Science. 1975. V. 90. P. 669–671.
  7. Barrett A.H., Myers Ph. C., Sadovsky N.L. Microwave thermography in the detection of breast cancer. AJR. 1980. № 134. R. 365–368.
  8. Leroy Y., Bocquet B., Mammouni A. Non-invasive microwave radiometry thermometry Physiol. Means. 1998. V.19. P. 127–148.
  9. Carr C K. L. Microwave radiometry: Its importance to the detection of cancer. IEEE Trans. Microw. Theory Techn. 1989. V. 37. № 12. P. 1862–1869.
  10. Lüdeke K.M, Köhler J. Microwave radiometric system for biomedical true temperature and emissivity measurements. J. Microw. Power. 1983. V. 18. № 3. P. 277–283.
  11. Troickij V.S. K teorii kontaktnyh radiotermometricheskih izmerenij vnutrennej temperatury tel.. Izv. vuzov. Ser.: Radiofizika. 1981.
    T. 24. № 9. S. 1054 (in Russian).
  12. Rahlin V.L., Alova S.E. Radiotermometriya v diagnostike patologii molochnyh zhelez, genitalij, predstatel'noj zhelezy i pozvonochnika. Preprint № 253. Gor'kij: NIRFI. 1988 (in Russian).
  13. Terent'ev I.G., Komov D.V., Ozherel'ev A.S., Orinovskij M.B. Radiotermometriya v kompleksnoj diagnostike i ocenke effektivnosti lecheniya opuholej molochnoj zhelezy. N. Novgorod: Nizhegorodskaya yarmarka. 1996. S. 9–35 (in Russian).
  14. Esepkina N.A., Korol'kov D.V., Parijskij Yu.N. Radiometry i radioteleskopy. 1973 (in Russian).
  15. Vesnin S.G. i dr. Mikrovolnovaya radiotermometriya: Ucheb. posobie. M.: RUDN. 2021. 145 s. (in Russian).
  16. Andreuccetti D., Fossi R., Petrucci C. An Internet resource for the calculation of the dielectric properties of body tissues in the frequency range 10 Hz–100 GHz. IFAC-CNR. Florence (Italy). 1997. [Online]. Available at: http://niremf.ifac.cnr.it/tissprop/ accessed 10.07.22.
  17. Fear E.C. et al. Enhancing breast tumor detection with near-field imaging. IEEE Microwave magazine. 2002. V. 3. № 1. P. 48–56.
  18. Meaney P.M., Fanning M.W., Li D., Poplack S.P., Paulsen K.D. 2000 A clinical prototype for active microwave imaging of the breast. IEEE Trans. Microw. Theory Tech. V. 48. P. 1841–1853.
  19. AlSawaftah N. et al. Microwave imaging for early breast cancer detection: Current state, challenges, and future directions. Journal of Imaging. 2022. V. 8. № 5. P. 123.
  20. Lazebnik M. et al. A large-scale study of the ultrawideband microwave dielectric properties of normal breast tissue obtained from reduction surgeries. Phys. Med. Biol. 2007. V. 52. P. 2637–2656.
  21. Lazebnik M. et al. A large-scale study of the ultrawideband microwave dielectric properties of normal, benign and malignant breast tissues obtained from cancer surgeries. Physics in medicine & biology. 2007. V. 52. № 20. P. 6093–6115.
  22. Vesnin S.G., Sedankin M.K. Razrabotka serii antenn-applikatorov dlya neinvazivnogo izmereniya temperatury tkanej organizma cheloveka pri razlichnyh patologiyah. Vestnik MGTU im. N.E. Baumana. Ser.: Estestvennye nauki. 2012. № S6. S. 43–61 (in Russian).
  23. Sedankin M.K. et al. System of rational parameters of antennas for designing a multi-channel multi-frequency medical radiometer. 2020 International Conference on Actual Problems of Electron Devices Engineering (APEDE). IEEE. 2020. P. 154–159.
  24. Li J. et al. Dynamic weight agnostic neural networks and medical microwave radiometry (MWR) for breast cancer diagnostics. Diagnostics. 2022. V. 12. № 9. P. 2037.
  25. Losev A.G. et al. Some Methods for Substantiating Diagnostic Decisions Made Using Machine Learning Algorithms. Biomedical Engineering. 2022. V. 55. № 6. P. 442.
  26. Losev A.G., Popov I.E., Gudkov A.G., Chizhikov S.V. Intellektual'nyj analiz dannyh mikrovolnovoj radiotermometrii v medicinskoj diagnostike. Nanotekhnologii: razrabotka, primenenie – XXI vek. 2023. T. 15. № 1. S. 5–22 (in Russian).
Date of receipt: 11.07.2023
Approved after review: 25.07.2023
Accepted for publication: 31.08.2023