AUTOMATED SYSTEM FOR EVALUATION OF THE MAMMARY GLANDS EXAMINATION RESULTS FOR CONTACT DIGITAL THERMOGRAPHY
DOI:
https://doi.org/10.11603/mie.1996-1960.2019.2.10315Keywords:
mammary gland diseases, thermography, fractal analysis, neural modelAbstract
Background. The problems of early diagnosis of breast cancer are related to the quality and life expectancy of women. One of the ways to solve this problem is to conduct screening — a preventive examination of women, starting from 35 years.
The contact digital thermography of the mammary glands meets the requirements for the primary examination of the mammary gland, but evaluation of the results of thermography requires the training of qualified specialists.
Purpose. Solving the problem of simplifying and accelerating the evaluation of the results of thermography data can be accomplished by developing a software package for the automated evaluation of thermograms.
Materials and methods. 685 records of thermograms of women aged 18-86 years, which have the final diagnosis based on a comprehensive examination was analyzed. To estimate the distribution of the temperature of the mammary glands, an algorithm for estimating the Hurst index for the high dimensional fractals was used.
Results. By the statistical analysis, significant indicators describing the field of temperature of the mammary glands, which allow discriminating the norm and pathology, were revealed. On the significant variables, a mathematical model of prediction of the risk of breast pathology was constructed. The automated system was implemented by mean of nonlinear neural network models, which allows 90.2 % sensitivity and 85.1 % specificity to predict the risk of pathology.
Conclusion. The automated system is developed that allows using the thermography method to detect breast pathology during screening studies by a trained medical professional with nursing or paramedic education or family doctors.
References
Ng, E. Y. (2009). A review of thermography as promising non-invasive detection modality for breast tumor. Int. J. Therm. Sci., 48(5), 849-859. DOI: https://doi.org/10.1016/j.ijthermalsci.2008.06.015
Koval'chuk, I. S., Dunayevskiy, V. I., Venger, Ye. F., Kotovskiy, V. I., Nazarchuk, S. S. (201З). Vozmozhnosti distantsionnoy infrakrasnoy termografii v diagnostike zabolevaniy molochnykh zhelez (dobrokachestvennyye izmeneniya) [Possibilities of remote infrared thermography in the diagnosis of diseases of the mammary glands (benign changes)]. Ukr. med. Chasopis, 3(95), 165-169. [in Russian].
Prikhodchenko, V. V., Prikhodchenko, O. V., Beloshenko, V. A., Doroshev, V. D., Karnachev, A. S. (2009). Povysheniye effektivnosti otborochnogo etapa selektivnogo skrininga zabolevaniy molochnoy zhelezy [Improving the effectiveness of the screening stage for selective screening of breast diseases]. Medyko-sotsialni problemy simi, Vol. 14, 4, 20-25 [in Russian].
Prikhodchenko, V. V., Dumanskiy, Yu. V., Prikhodchenko, O. V., Beloshenko, V. A., Doroshev, V. D., Karnachev, A. S. (2012). Primeneniye kontaktnogo tsifrovogo termografa TKTS-1 v diagnostike zabolevaniy molochnykh zhelez [The use of contact digital thermograph TKTS-1 in the diagnosis of diseases of the mammary glands]. Donetsk, 189. [in Russian].
Kozhevnikova, I. S., Pankov, M. N., Ermoshina, N. A. (2017). Metodyi obrabotki i analiza termogramm dlya ekspress-diagnostiki novoobrazovaniy molochnyih zhelez [Methods of processing and analysis of thermograms for the rapid diagnosis of breast tumors]. Zhurnal mediko-biologicheskih issledovaniy, Vol. 5, 2, 56-66. [in Russian].
Kozhevnikova, I. S., Pankov, M. N., Gribanov, A. V., Startseva, L. F., Ermoshina, N. A. (2017). Primenenie infrakrasnoy termografii v sovremennoy meditsine [The use of infrared thermography in modern medicine]. Ekologiya cheloveka, 2, 39-46. [in Russian]. DOI: https://doi.org/10.33396/1728-0869-2017-2-39-46
URL: https://www.imcs-4u.com/procedury/ thermografiya.html.
Rozenfel'd, L. G., Kolotilov, N. N. (2001). Distantsionnaya infrakrasnaya termografiya v onkologii [Remote infrared thermography in oncology]. Onkologiya, Vol. 3, 2-3, 103-106. [in Russian].
Markel', A. L., Vayner, B. G. (2005). Infrakrasnaya termografiya v diagnostike raka molochnoy zhelezy (obzor zarubezhnoy literatury) [Infrared thermography in the diagnosis of breast cancer (review of foreign literature)]. Terapevt. Arkhiv, Vol. 776, 57-61. [in Russian].
Prikhodchenko, V. V., Prikhodchenko, O. V. (2005). Diagnostika zabolevaniy molochnoy zhelezy s pomoshch'yu tsifrovogo kontaktnogo termografa [Diagnosis of breast disease using a digital contact thermograph]. Medyko-sotsialni problemy simi, Vol. 10, 3-4, 61-64. [in Russian].
Prykhodchenko, V. V., Prykhodchenko, O. V., Biloshenko, V. O., Karnachov, O. S., Doroshev, V. D., Kalinina, O. I. (2009). Mozhlyvosti kontaktnoyi tsyfrovoyi termohrafiyi u ranniy doklinichniy diahnostytsi raku molochnoyi zalozy [Possibilities of contact digital thermography in the early preclinical diagnosis of breast cancer]. Onkolohiya, Vol. 13, 2, 125-129. [in Ukranian].
Venger, E. F., Gordienko, V. I., Dunaevskiy, V. I., Kotovskiy, V. Y., Maslov, V. P. (2015). Zastosuvannya termografii v Ukraini [Application of thermography in Ukraine]. Nauka ta Innovatsii, Vol. 11, 6. 5-15. [in Ukranian].
Etehadtavakol, M., Ng, E. Y. K. (2013). Breast thermography as a potential non-contact method in the early detection of cancer: A review. J. Mech. Med. Biol., 13(2), Art. № 1330001. DOI: https://doi.org/10.1142/S0219519413300019
Beloshenko, V. A., Doroshev, V. D., Karnachev, A. S., Prikhodchenko, V. V. (2007). Kompleks apparatury dlya ranney diagnostiki onkologicheskikh zabolevaniy metodom kontaktnoy tsifrovoy termografii [Complex of equipment for early diagnosis of oncological diseases by the method of contact digital thermography]. Nauka ta innovatsii, Vol. 3, 5, 11-25. [in Russian].
Bubnov, R. V., Melnyk, I. M. (2011). The methods of fractal analysis of diagnostic images. Initial clinical experience. Lik. Sprava, 3-4, 108-113.
Bubnov, R. V., Melnyk, I. M. (2014). Hepatic oncology diagnosis based on imaging fractal analysis: preliminary results. EPMA Journal, 5, A43. URL: https://link.springer.com/article/10.1186%2F1878-5085-5-S1-A43.
Etehadtavakol, M., Lucas, C., Sadri, S., Ng, E. Y. K. (2010). Analysis of breast thermography using fractal dimension to establish possible difference between malignant and benign patterns. J. Healthcare Eng., Vol. 1, 1, 27-43. DOI: https://doi.org/10.1260/2040-2295.1.1.27
Baish, J. W., Jain, R. K. (2000). Fractals and cancer. Cancer Res., Vol. 60, 3683-3688.
Ramirez-Cobo, P., Vidakovic, B. (2013). A 2D wavelet-based multiscale approach with applications to the analysis of digital mammograms. Computational Statistics and Data Analysis, Vol. 58, 2, 71-81.
Dumansky, Y. V., Lyakh, Yu. Ye., Gorshkov, O. G., Gurianov, V. G., Prihodchenko, V. V. (2012). Fractal dimensionality analysis of normal and cancerous mammary gland thermograms. Chaos, Solitons and Fractals, Vol. 45, 1494-1500. DOI: https://doi.org/10.1016/j.chaos.2012.07.006
Carbone, A. (2007). Algorithm to estimate the Hurst exponent of highdimensional fractals. Phys. Rev. E., Vol. 76, 056703. DOI: https://doi.org/10.1103/PhysRevE.76.056703
Petrie, A., Sabin, C. (2005). Medical Statistics at a Glance. 2nd ed. Blackwell Publishing.
Gur'yanov, V. G., Lyah, Yu. Ye., Pariy, V. D. et al. (2018). Posibnik z biostatistiki. Analiz rezultativ medichnih doslidzhen u paketi EZR (R-statistics) [Biostatistics guide. Analysis of the results of medical research in the package EZR (R-statistics)]. Navchalniy posibnik. K.: Vistka, 208. [in Ukranian].
Kanda, Y. (2013). Investigation of the freely available easy-to-use software 'EZR' for medical statistics. Bone Marrow Transplant, Vol. 48, 452-458. DOI: https://doi.org/10.1038/bmt.2012.244
Haykin, S. (1999). Neural Networks: A Comprehensive Foundation. 2nd ed. - Prentice-Hall, Englewood Cliffs, NJ.
Lyakh, Yu. Ye., Hufyanov V. H. (2012). Matematycheskoe modelyrovanye pry reshenyy zadach klassyfykatsyy v byomedytsyne [Mathematical modeling for solving classification problems in biomedicine]. Ukrayins'kyy zhurnal telemedytsyny ta medychnoyi telematyky, 2(10), 69-76 [in Russian].
Downloads
Published
How to Cite
Issue
Section
License
Journal Medical Informatics and Engineering allows the author(s) to hold the copyright without registration
The majority of Medical Informatics and Engineering Open Access journals publish open access articles under the terms of the Creative Commons Attribution (CC BY) License which permits use, distribution and reproduction in any medium, provided the original work is properly cited. The remaining journals offer a choice of licenses.
This journal is available through Creative Commons (CC) License CC-BY 4.0
