Diagnostic System in Electrical Impedance Mammography: Background

Karpov, A; Kolobanov, Andrey; Korotkova, M

doi:10.5772/intechopen.69195

Cited by 3 publications

(7 citation statements)

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“…The results of 3D EIT imaging were analyzed independently based on visual interpretation and quantitative evaluation of breast tissues and according to the main diagnostic criteria previously reported from Russia (13)(14)(15). The breast's structure, contour, focal changes of electrical conductivity, and bilateral breast conductivity differences were evaluated to analyze the possibility of pathological changes in the patient's breast.…”

Section: Image Analysismentioning

confidence: 99%

Diagnostic accuracy and prognostic value of three-dimensional electrical impedance tomography imaging in patients with breast cancer

et al. 2021

Gland Surg

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Background: Three-dimensional electrical impedance tomography (3D EIT) is a novel, non-invasive, radiationfree imaging technology for breast cancer screening. This study aimed to identify characteristics and classification of 3D EIT breast cancer imaging that could provide diagnostic accuracy and prognostic value for breast cancer patients.Methods: A total of 645 suspicious breast lesions [Breast Imaging Reporting and Data System (BI-RADS) III, IV, V] identified by mammography or ultrasound were examined with 3D EIT (MEIK, SIM-Technika, Yaroslavl, Russia). Breast tissue conductivity was quantified using MEIK 5.6 software. Diagnostic performance of visually interpreted 3D EIT was assessed using histology (surgical excision or vacuum core biopsy) and clinical follow-up. Kaplan-Meier analysis was used to calculate progression-free survival (PFS) and overall survival (OS) rates. Hazard ratio (HR) with a 95% confidence interval (95% CI) for various clinicopathological variables were determined using univariate and multivariate Cox regression models.Results: Breast cancer was confirmed in 272 of 645 patients by histopathology and other diagnostic imaging modalities. Among the confirmed cases, 218 patients had positive 3D EIT findings. The sensitivity, specificity, accuracy, positive likelihood, and negative likelihood ratios of 3D EIT were 80.1%, 75.1%, 77.2%, 70.1%, and 83.8%. There were no significant differences in the diagnostic accuracy, sensitivity, or specificity between 3D EIT and mammography, ultrasound, or combined mammography and ultrasound. 3D EIT breast cancer images were classified into 3 different types, including Ia [non-complicated breast cancer (NCBC), 62 cases], Ib [complicated breast cancer (CBC), 131 cases], and Ic [edematous-infiltrative breast cancer (EIBC), 25 cases], which were associated with tumor size (P<0.001), TNM stage (P<0.001), and lymph node metastasis (P=0.012). At 5-year follow-up, multivariate analysis demonstrated that breast cancer 3D EIT imaging classification was an independent predictor for decreased OS (HR: 2.399, 95% CI: 1.035, 5.564, P=0.041) and PFS (HR: 2.836, 95% CI: 1.555, 5.172, P=0.012) in patients with breast cancer. Conclusions: 3D EIT breast cancer images were classified into 3 types based on different image characteristics. 3D EIT appeared to be useful in clinical diagnostic performance and prognostic evaluation in patients with breast cancer.

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Section: Image Analysismentioning

confidence: 99%

Diagnostic accuracy and prognostic value of three-dimensional electrical impedance tomography imaging in patients with breast cancer

et al. 2021

Gland Surg

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“…This unique information is used for diagnostic purposes. All other factors equal, the electrical conductivity will depend on the concentration of ions and the amount of cellular elements, and it will decrease as the concentration grows [28]. The electrical conductivity index [IC], which is received during electric impedance scanning, is a quantitative characteristic of breast structure.…”

Section: Formation Of Survey Groupmentioning

confidence: 99%

“…The results of the researches confirm that electrical conductivity is an appropriate parameter for the differentiation between healthy tissue and tumor tissue. The fundamental difference of electrical impedance scanning from other tomographic methods is that besides visual evaluation of the image, the electrical impedance mammography offers quantitative information [28]. If the diagnostic method under discussion yields a quantitative result, a value is defined, the overpassing of which is deemed to be a sufficient cause for qualitative evaluation, i.e.…”

Section: Fricke Et Al [29] 1926 20 Khzmentioning

confidence: 99%

“…The detection of areas with high electrical conductivity exceeding 3 std. outside the lactiferous sinus in electrical impedance mammograms, which differs greatly from the electrical conductivity of normal breast tissue, is used as a diagnostic criteria for the detection of breast cancer [28]. Moreover, sizes of tumors as a rule do not exceed 10 mm.…”

Section: Fricke Et Al [29] 1926 20 Khzmentioning

confidence: 99%

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Electrical Impedance Mammography: Screening and Basic Principles

Karpov¹,

Korotkova²,

Шиферсон³

et al. 2020

Breast Cancer and Breast Reconstruction

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Nowadays, screening uses the method of X-ray mammography for the early diagnosis of breast cancer. However, as a screening method, X-ray mammography has its limitations, such as age, periodicity of screening, 'dense' mammary gland and dynamic survey (repeated radiation). In order to overpass these limitations, more advanced alternative methods of breast examination should be used, which would be as effective as the 'golden standard.' Characteristics of electroimpedance diagnostics are given. The aim of screening is to detect breast cancer including early breast cancer (tumor size below 1 cm) and to form a survey of high-risk group. In order to reach these aims, the following actions need to be undertaken: search for areas with anomalous conductivity, detection of distorted mammographic scheme and evaluation of age-related electrical conductivity. The application of a scale for age-related breast conductivity with defined percentile limits allows to organize a survey group. Electrical properties of a cancerous tumor differ significantly from those of the surrounding tissues. Statistics of anomalous conductivity in cases of breast cancer is given. The disease development connected with the destruction of epithelial basement membrane is linked with various phenomena occurring in the tumor and the surrounding tissues. Statistics of disrupted mammographic scheme in cases of cancer is given.

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“…EIT can be considered as a functional diagnostic technique that provides data from the mammary gland, its physiological state, and that it is sensitive to changes in the electrical conductivity of the tissues. Because of its high sensitivity in the primary diagnosis of benign tumors, EIT helps to give a dynamic followup of patients with diffuse and nodular types of mastopathy [19]. In this paper, we will refer to the use of EIT medical images for breast cancer detection as Electrical Impedance Mammography (henceforth denoted as EIM).…”

Section: Introductionmentioning

confidence: 99%

Machine Learning for the Analysis of Conductivity From Mono Frequency Electrical Impedance Mammography as a Breast Cancer Risk Factor

et al. 2021

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Computational approaches have been used for analyzing risk factors together with conventional mammograms for breast cancer detection. Currently, other screening methods like electro-impedance mammography are available. Notwithstanding, as far as we know there is not related work evaluating the role of electrical-conductivity index of the mammary gland as a quantitative factor for early detection of breast cancer. This paper aims to demonstrate the importance of including breast conductivity index as a quantitative local risk-factor by analyzing a dataset of Mexican patients from a machine learning perspective. There are 12 attributes distributed into two groups: electrical-conductivity (3) and medical records (9). According to the obtained results with unsupervised methods, the performance in terms of accuracy of using only electrical-conductivity (43%) is better than using all available features (38%) and the medical records (33%). On the other hand, we identified that SVM achieves higher results in comparison with other algorithms when only the electrical-features are used. The obtained results demonstrate the important role of conductivity index as a quantitative local risk-factor for being considered in screening processes. Besides, it emerges as an important aspect to be included in the development of automatic tools for experts to perform breast cancer diagnosis.INDEX TERMS Electro-impedance, conductivity, machine learning, mammography MEIK, risk factor.

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Diagnostic System in Electrical Impedance Mammography: Background

Cited by 3 publications

References 20 publications

Diagnostic accuracy and prognostic value of three-dimensional electrical impedance tomography imaging in patients with breast cancer

Diagnostic accuracy and prognostic value of three-dimensional electrical impedance tomography imaging in patients with breast cancer

Electrical Impedance Mammography: Screening and Basic Principles

Machine Learning for the Analysis of Conductivity From Mono Frequency Electrical Impedance Mammography as a Breast Cancer Risk Factor

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