Ultrasonic Measurement of Temperature Rise in Breast Cyst and in Neighbouring Tissues as a Method of Tissue Differentiation

• Autorzy: Gambin B. , Byra M. , Kruglenko E. , Doubrovina O. , Nowicki A.

Identyfikatory

DOI

10.1515/aoa-2016-0076

• Języki publikacji: EN

Abstrakty

EN

Texture of ultrasound images contain information about the properties of examined tissues. The analysis of statistical properties of backscattered ultrasonic echoes has been recently successfully applied to differentiate healthy breast tissue from the benign and malignant lesions. We propose a novel procedure of tissue characterization based on acquiring backscattered echoes from the heated breast. We have proved that the temperature increase inside the breast modifies the intensity, spectrum of the backscattered signals and the probability density function of envelope samples. We discuss the differences in probability density functions in two types of tissue regions, e.g. cysts and the surrounding glandular tissue regions. Independently, Pennes bioheat equation in heterogeneous breast tissue was used to describe the heating process. We applied the finite element method to solve this equation. Results have been compared with the ultrasonic predictions of the temperature distribution. The results confirm the possibility of distinguishing the differences in thermal and acoustical properties of breast cyst and surrounding glandular tissues.

Słowa kluczowe

EN

medical ultrasound; temperature changes in vivo; breast tissue; ultrasonic temperature measurement

• Wydawca: Instytut Podstawowych Problemów Techniki PAN ; Komitet Akustyki PAN ; Polskie Towarzystwo Akustyczne
• Czasopismo: Archives of Acoustics
• Rocznik: 2016
• Tom: Vol. 41, No. 4
• Strony: 791--798
• Opis fizyczny: Bibliogr. 17 poz., fot., rys., tab., wykr.

Twórcy

autor

Gambin B.

• Institute of Fundamental Technological Research, Polish Academy of Sciences Pawińskiego 5B, 02-106 Warsaw, Poland

autor

Byra M.

• Institute of Fundamental Technological Research, Polish Academy of Sciences Pawińskiego 5B, 02-106 Warsaw, Poland

autor

Kruglenko E.

• Institute of Fundamental Technological Research, Polish Academy of Sciences Pawińskiego 5B, 02-106 Warsaw, Poland

autor

Doubrovina O.

• Belarussian State University, Kurchatova 5, 220045 Minsk, Belarus

autor

Nowicki A.

• Institute of Fundamental Technological Research, Polish Academy of Sciences Pawińskiego 5B, 02-106 Warsaw, Poland

Bibliografia

• 1. Balusu K., Suganthi S. S., Ramakrishnan S. (2014), Modelling Bio-heat transfer in Breast Cysts using Finite Element analysis, International Conference on Informatics, Electronics and Vision, ICIEV, 1-4, Dhaka, Bangladesh.
• 2. Byra M., Gambin B. (2015), Temperature detection based on nonparametric statistics of ultrasound echoes, Hydroacoustics, 18, 17–23.
• 3. Byra M., Nowicki A., Piotrzkowska-Wróblewska H., Dobruch-Sobczak K. (2016), Classification of breast lesions using segmented quantitative ultrasound maps of homodyned K distribution parameters, Med. Phys. 43, 5561–5569, DOI: 10.1118/1.4962928.
• 4. Doubrovina O., Gambin B., Kruglenko E. (2014), Temperature level and properties of wavelet approximation of backscattered ultrasound, Hydroacoustics, 17, 37–46.
• 5. Gambin B., Kruglenko E., Wójcik J. (2015a), Relationship between thermal and ultrasound fields in breast tissue in vivo, Hydroacoustics, 18, 53–58.
• 6. Gambin B., Kruglenko E., Byra M., Nowicki A., Piotrzkowska-Wroblewska H., Dobruch-Sobczak K. (2015b), Changes in ultrasound echoes of a breast tissue in vivo after exposure to heat-a case study, Proceedings of 3rd Congress of Mechanics, 1, pp. 217–218, Gdańsk, Poland.
• 7. Gambin B., Kruglenko E. (2015), Temperature Measurement by Statistical Parameters of Ultrasound Signal Backscattered from Tissue Samples, Acta Physica Polonica, 128, A-72–A-78.
• 8. González F. J. (2007), Thermal simulation of breast tumors, Revista Mexicana de F´ısica, 53, 4, 323–326.
• 9. Kruglenko E., Gambin B. (2014), RF signal amplitudę statistics during temperature changes in tissue phantoms, Hydroacoustics, 17, 115–122.
• 10. Kwok J., Krzyspiak J. (2007), Thermal Imaging and Analysis for Breast Tumor Detection, BEE 453: Computer-Aided Engineering: Applications to Biomedical Processes.
• 11. Lewis M. A., Staruch R. M., Chopra R. (2015), Thermometry and Ablation Monitoring with Ultrasound, Int. J. Hyperthermia, 31, 2, 163–181.
• 12. Mamou J., Oelze M. L. [Eds.], (2013), Quantitative Ultrasound in Soft Tissues, Dortrecht-Heilderberg-New York-London, Springer.
• 13. Ng E. Y. K., Sudharsan N. M. (2001), An improved three-dimensional direct numerical modelling and thermal analysis of a female breast with tumour, Proceedings of the Institution of Mechanical Engineers, 215, 25–37.
• 14. Nowicki A., Piotrzkowska-Wroblewska H., Litniewski J., Byra M., Gambin B., Kruglenko E., Dobruch-Sobczak K. (2015), Differentiation of normal tissue and tissue lesions using statistical properties of backscattered ultrasound in breast, in Ultrasonics Symposium (IUS), 2015 IEEE International, DOI: 10.1109/ULTSYM.2015.0417.
• 15. Subhadeep M. Balaji C. (2010), A Neural Network Based Estimation of Tumor Parameters from a Breast Thermogram, International Journal of Heat and Mass Transfer, 53, 4714–4727.
• 16. Tsui P. H., Shu Y. C., Chen W. S., Liu H. L., Hsiao I. T., Chien Y. T. (2012), Ultrasound temperaturę estimation based on probability variation of backscatter data, Med. Phys., 39, 2369–2385, http://dx.doi.org/10.1118/1.3700235.
• 17. Wu W.-J., Shih-Wei Lin, Woo Kyung Moon (2015), An Artificial Immune System-Based Support Vector Machine Approach for Classifying Ultrasound Breast Tumor Images, J. Digit Imaging, 28, 5, 576–585, DOI: 10.1007/s10278-014-9757-1.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.