Numerical prediction of breast skin temperature based on thermographic and ultrasonographic data in healthy and cancerous breasts

• Autorzy: Korczak Ilona , Romowicz Agnieszka , Gambin Barbara , Palko Tadeusz , Kruglenko Eleonora , Dobruch-Sobczak Katarzyna

Identyfikatory

DOI

10.1016/j.bbe.2020.10.007

• Języki publikacji: EN

Abstrakty

EN

Breast cancer is one of the most common women's cancers, so an available diagnostic modality, particularly non-invasive, is important. Infrared thermography (IRT) is a supporting diagnostic modality. Until now, many finite element methods (FEM) numerical models have been constructed to evaluate IRT's diagnostic value and to relate breast skin temperature characteristics with breast structural disorder presence, particularly to distinguish between cancerous types and normal structures. However, most of the models were not based on any clinical data, except for several papers based on clinical magnetic resonance imaging (MRI) data, wherein a three-dimensional (3D) breast model was studied. In our paper, we propose a very simplified numerical two-dimensional FEM model constructed based on clinical ultrasound data of breasts, which is much cheaper and available in real-time as opposed to MRI data. We show that our numerical simulations enabled us to distinguish between types of healthy breasts in agreement with the clinical classification and with thermographic results. The numerical breast models predicted the possibility of differentiation of cancerous breasts from healthy breasts by significantly different skin temperature variation ranges. The thermal variations of cancerous breasts were in the range of 0.5 °C–3.0 °C depending on the distance of the tumor from the skin surface, its size, and the cancer type. The proposed model, due to its simplicity and the fact that it was constructed based on clinical ultrasonographic data, can compete with the more sophisticated 3D models based on MRI.

Słowa kluczowe

EN

nonInvasive cancer detection; Pennes' bioheat transfer equation; finite element method; breast thermography; ultrasonography

PL

nieinwazyjne wykrywanie raka; metoda elementów skończonych; termografia piersi; ultrasonografia piersi

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2020
• Tom: Vol. 40, no. 4
• Strony: 1680--1692
• Opis fizyczny: Bibliogr. 40 poz., rys., tab., wykr.

Twórcy

autor

Korczak Ilona

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

autor

Romowicz Agnieszka

• Institute of Metrology and Biomedical Engineering Faculty of Mechatronics of the Warsaw University of Technology, Warsaw, Poland

autor

Gambin Barbara

• Institute of Fundamental Technological Research of the Polish Academy of Sciences, Warsaw, Poland

autor

Palko Tadeusz

• Institute of Metrology and Biomedical Engineering Faculty of Mechatronics of the Warsaw University of Technology, Warsaw, Poland

autor

Kruglenko Eleonora

• Institute of Fundamental Technological Research of the Polish Academy of Sciences, Warsaw, Poland

autor

Dobruch-Sobczak Katarzyna

• Institute of Fundamental Technological Research of the Polish Academy of Sciences, Warsaw, Poland

Bibliografia

• [1] Burzynska M, Maniecka-Bryla I, Pikala M. Trends of mortality due to breast cancer in Poland, 2000-2016. BMC Public Health 2020;20:120.
• [2] Brem RF, Lenihan MJ, Lieberman J, Torrente J. Screening breast ultrasound: past, present, and future. AJR Am J Roentgenol 2015;204(2):234–40.
• [3] Nowikiewicz T, Nowak A, Wisniewska M, Wisniewski M, Nowikiewicz M, Zegarski W. Analysis of the causes of false negative and false positive results of preoperative axillary ultrasound in patients with early breast cancer - a single- centre study. Contemp Oncol (Pozn) 2018;22(4):247–51. http://dx.doi.org/10.5114/wo.2018.82644.
• [4] Suman S, Suman G, Mishra S. Current advances in breast cancer research: a molecular approach. Bentham Science Publishers; 2020 [chapter 2: sumam G, Patra A. Current imaging techniques in breast cancer: an overview]; 2020.
• [5] Byra M, Dobruch-Sobczak K, Klimonda Z, Piotrzkowska- Wroblewska H, Litniewski J. Early prediction of response to neoadjuvant chemotherapy in breast cancer sonography using Siamese convolutional neural networks. IEEE J Biomed Health Inform 2020. http://dx.doi.org/10.1109/JBHI.2020.3008040.
• [6] Ng EYK, Ung LN, Ng FC, Sim LSJ. Statistical analysis of healthy and malignant breast thermography. J Med Eng Tech 2001;25(6):253–63.
• [7] Ng EY, Sudharsan NM. An improved three-dimensional direct numerical modelling and thermal analysis of a female breast with tumour. Proc Inst Mech Eng H 2001;215 (1):25–37.
• [8] Ng EY, Sudharsan NM. Computer simulation in conjunction with medical thermography as an adjunct tool for early detection of breast cancer. BMC Cancer 2004;4:17.
• [9] Ng EYK. A review of thermography as promising non-invasive detection modality for breast tumor. Int J Therm Sci 2009;48(5):849–59.
• [10] Singh D, Singh AK. Role of image thermography in early breast cancer detection- Past, present and future. Comput Methods Programs Biomed 2020;183105074. http://dx.doi.org/10.1016/j.cmpb.2019.105074.
• [11] González FJ. Thermal simulation of breast tumors. Rev mexfis 2007;53(4):323–6.
• [12] González FJ. Non-invasive estimation of the metabolic heat production of breast tumors using digital infrared imaging. Quant Infrared Thermogr J 2011;8(2):139–48.
• [13] Kwok J, Krzyspiak J. Thermal imaging and analysis for breast tumor detection. BEE 4530: computer-Aided Engineering: applications to Biomedical Processes; 2007.
• [14] Chanmugam A, Hatwar R, Herman C. Thermal analysis of cancerous breast model. Int Mech Eng Congress Expo 2012;2012:134–43.
• [15] Mital M, Pidaparti RM. Breast tumor simulation and parameters estimation using evolutionary algorithms. Model SimulatEng 2008;2008:1–6.
• [16] Ghayoumi Zadeh H, Haddadnia J, RahmaniSeryasat O, MostafaviIsfahani SM. Segmenting breast cancerous regions in thermal images using fuzzy active contours. EXCLI J 2016;15:532–50.
• [17] Pennes HH. Analysis of tissue and arterial blood temperatures in the resting human forearm. J Appl Physiol 1998;85(1):5–34.
• [18] Figueiredo AAA, do Nascimento JG, Malheiros FC, da Silva Ignacio LH, Fernandes HC, Guimaraes G. Breast tumor localization using skin surface temperatures from a 2D anatomic model without knowledge of the thermophysical properties. Comput Methods Programs Biomed 2019;172: 65–77.
• [19] Gonçalves CB, Leles ACQ, Oliveira LE, Guimaraes G, Cunha JR, Fernandes H. Machine learning and infrared thermography for breast Cancer detection. Proceedings 2019;27(1):45.
• [20] Singh D, Singh A. Role of image thermography in early breast Cancer detection- past, present and future. Comput Meth Prog Bio 2019;183105074.
• [21] Abdel-Nasser M, Moreno A, Puig D. Breast Cancer detection in thermal infrared images using representation learning and texture analysis methods. Electronics 2019;8(1):100.
• [22] Dua G, Mulaveesala R. Applicability of active infrared thermography for screening of human breast: a numerical study. J Biomed Opt 2018;23(3):1–9.
• [23] Chanmugam A, Hatwar R, Herman C. Thermal analysis of cancerous breast model. Proceedings of ASME 2012 IMECE; 2012.
• [24] Bakker JF, Paulides MM, Obdeijn IM, van Rhoon GC, van Dongen KW. An ultrasound cylindrical phased array for deep heating in the breast: theoretical design using heterogeneous models. Phys Med Biol 2009;54(10):3201–15.
• [25] Okita K, Narumi R, Azuma T, Furusawa H, Shidooka J, Takagi S, et al. Effects of breast structure on high- intensity focused ultrasound focal error. J Ther Ultrasound 2018;6:4.
• [26] de Holanda AA, Gonçalves AK, de Medeiros RD, de Oliveira AM, Maranhão TM. Ultrasound findings of the physiological changes and most common breast diseases during pregnancy and lactation. Radiol Bras 2016;49(6):389–96.
• [27] Wang L. Early diagnosis of breast Cancer. Sensors 2017;17 (7):1572.
• [28] Paruch M. Mathematical modeling of breast tumor destruction using fast heating during radiofrequency ablation. Materials 2019;13(1):136.
• [29] Manohar S, Dantuma M. Current and future trends in photoacoustic breast imaging. Photoacoustic 2019;16100134.
• [30] Bezerra LA, Ribeiro RR, Lyra PRM, Lima RCF. An empirical correlation to estimate thermal properties of the breast and of the breast nodule using thermographic images and optimization techniques. Int J Heat Mass Transf 2020;149119215.
• [31] Gambin B, Kruglenko E, Wójcik J. Relationship between thermal and ultrasound fields in breast tissue in?vivo. Hydroacoustics 2015;18:53–8.
• [32] Gambin B, Byra M, Kruglenko E, Doubrovina O, Nowicki A. Ultrasonic measurement of temperature rise in breast cyst and in neighboring tissues as a method of tissue differentiation. Arch Acoust 2016;41(4):791–8.
• [33] Jakubowski W, Dobruch-Sobczak K, Migda B. Standards of the polish ultrasound society – update. Sonomammography examination. JUltrason 2012;12 (50):245–61. DOI:10.15557/JoU.2012.0010.
• [34] Wolfe JN. Risk for breast cancer development determined by mammographic parenchymal pattern. Cancer 1976;37 (5):2486–92.
• [35] Piotrzkowska-Wróblewska H, Dobruch-Sobczak K, Byra M, Nowicki A. Open access database of raw ultrasonic signals acquired from malignant and benign breast lesions. Med Phys 2017;44(11):6105–9. http://dx.doi.org/10.1002/mp.12538.
• [36] Popiela TJ, C´wierz A, Pypkowska A, Trzyna M. Atlas termograficzny: rak Piersi. Warszawa: Wydawnictwo Lekarskie PZWL; 2015.
• [37] Gambin B, Kujawska T, Kruglenko E, Mizera A, Nowicki A. Temperature fields induced by low power focused ultrasound during gene therapy. Numerical predictions and experimental results. Arch Acoust 2009;34(4):445–60.
• [38] Gambin B, Kruglenko E, Kujawska T, Michajlow M. Modeling of tissues in?vivo heating induced by exposure to therapeutic ultrasound. Acta Phys Pol A 2011;119(6):950–6.
• [39] Balusu K, Suganthi SS, Ramakrishnan S. Modelling bio-heat transfer in breast cysts using finite element analysis.2014 International Conference on Informatics, Electronics & Vision (ICIEV), Dhaka; 2014;1–4. http://dx.doi.org/10.1109/ICIEV.2014.6850842.
• [40] Lozano A, Hayes JC, Compton LM, et al. Determining the thermal characteristics of breast cancer based on highresolution infrared imaging, 3D breast scans, and magnetic resonance imaging. Sci Rep 2020;10(10105). doi.org/10.1038/ s41598-020-66926-6.