Breast Cancer Detection Using Low-Frequency Bioimpedance Device

Multifrequency electrical impedance tomography (Mf-EIT) for the detection of breast cancer phantom anomalies

Breast cancer is the most commonly diagnosed neoplasm and one of the most widespread cancers among women. The research advanced the Mf-EIT hardware through analogue discovery, component assessment, hardware integration, software creation, and data reconstruction utilizing Gauss-Newton and GREIT approaches. The breast cancer phantom consisted of a gelatin and sodium chloride solution. The position and number of anomalies in the reconstructed image correspond with the phantom. Anomalies in the reconstructed image are illustrated in red, indicating that they exhibit higher conductivity than their environment. The smallest percentage difference in conductivity between the reconstructed image of the cancer abnormality and the phantom is 0.18 %, recorded at a current of 0.35 mA and a frequency of 150 kHz. The smallest percentage difference in size between cancer abnormalities 1 and 2 in the reconstructed image and the phantom is 0.14 %, observed at a current of 0.22 mA and a frequency of 80 kHz. In brief,•This study proposes an innovative Electrical Impedance Tomography (EIT)•The designed and built the Mf-EIT hardware based on data reconstruction using Gauss-Newton and GREIT•The Electrical Impedance Tomography designed to detect the anomalies in the reconstructed image of Breast Cancer.

Evaluation of ABL90 and ABL800 Radiometer Blood Gas Analyzers: Challenges and Applications in Point-of-Care Cancer Diagnostics in Saudi Arabia

BACKGROUND

Point-of-care (POC) diagnostics is an innovative approach to healthcare analysis that brings the diagnostic process closer to the patient's immediate care setting. This study was conducted to assess POC testing devices' use in diagnosing cancer and detecting the main challenges facing laboratory specialists.

METHOD

A cross-sectional study was conducted on conveniently selected laboratory specialists working in the Prince Mohammed bin Abdulaziz Hospital in Riyadh for six weeks.

RESULT

A total of 187 study participants (51% males and 49% females) were enrolled. Around one-half of them (96, 51%) were less than 30 years old, and 85% had 1-5 years of experience, with 61% (124) having no previous cancer diagnosis devices training. Most of this study's cohort was using ABL 90 Radio meter/blood gases (45, 24%), followed by ABL 800 Radio meter/blood gases (39, 20.9%), as the main cancer diagnostic devices. Several challenges were faced by this study's participants during their work with cancer diagnosis devices. The participants shared that some time was needed to use most of the devices, and learning how to use them was a significantly steep learning curve (2.99 ± 0.07 of participants). Most participants (113, 60.4%) carried out all the control testing, and their results were compared completely (100%) with the central laboratory. They took special precautions to keep the instruments safe (162, 86.6%).

CONCLUSION

The correlation between type of devices used and the challenges faced during the use of POCT cancer diagnosis devices showed that there is a significant correlation between all challenges facing the participants and the type of devices (p = 0.001), except for the need for time to use these devices (p = 0.53). There are many challenges facing workers who operate point-of-care cancer diagnosis devices to a high degree.

Enhancing Breast Cancer Detection: A Machine Learning Approach Using Multielectrode Bioimpedance

Background

Early detection of cancerous tumors is a critical factor in improving treatment outcomes. To address this need, this study explores a simple, effective, and cost-efficient method for early cancer detection by measuring the bioimpedance of living tissues. Bioimpedance-based methods hold significant promise for the early detection of cancerous tumors.

Materials and Methods

The study begins by simulating the impedance behavior of the human breast under two conditions: healthy and containing cancerous tumors. The Cole-Cole model is used to simulate the dielectric properties of both breast and tumor tissues using finite element modeling. In the measurement phase, eight electrodes are evenly distributed around the breast model to ensure comprehensive data collection. Subsequently, a dataset is prepared encompassing three breast sizes (60, 70, and 80 mm) in both the healthy and tumor-afflicted states, with tumor sizes of 5, 8, and 10 mm radius. This dataset is utilized to develop machine learning models, including support vector machines (SVM), convolutional neural networks (CNN), and random forest (RF), for breast cancer detection.

Results

The results of this study demonstrate the practicality of integrating machine learning techniques with multielectrode bioimpedance measurements to achieve precise and automated breast cancer detection. Notably, the RF model outperformed both SVM and CNN in terms of cancer detection accuracy.

Conclusions

This study underscores the potential of bioimpedance-based methods, coupled with machine learning algorithms, for early cancer detection. The findings suggest that RF models hold promise for accurate and automated breast cancer detection, offering a valuable tool for improving patient outcomes.

Portable noninvasive technologies for early breast cancer detection: A systematic review

Breast cancer remains a leading cause of cancer mortality worldwide, with early detection crucial for improving outcomes. This systematic review evaluates recent advances in portable non-invasive technologies for early breast cancer detection, assessing their methods, performance, and potential for clinical implementation. A comprehensive literature search was conducted across major databases for relevant studies published between 2015 and 2024. Data on technology types, detection methods, and diagnostic performance were extracted and synthesized from 41 included studies. The review examined microwave imaging, electrical impedance tomography (EIT), thermography, bioimpedance spectroscopy (BIS), and pressure sensing technologies. Microwave imaging and EIT showed the most promise, with some studies reporting sensitivities and specificities over 90 %. However, most technologies are still in early stages of development with limited large-scale clinical validation. These innovations could complement existing gold standards, potentially improving screening rates and outcomes, especially in underserved populations, whiles decreasing screening waiting times in developed countries. Further research is therefore needed to validate their clinical efficacy, address implementation challenges, and assess their impact on patient outcomes before widespread adoption can be recommended.

Effects of temperature on electrical impedance of biological tissues: ex-vivo measurements

Bioelectrical impedance techniques have been useful in various applications, including body composition analysis, impedance plethysmography, impedance cardiography, lung ventilation, perfusion, and tissue characterization. Electrical impedance methods have also been useful in characterizing different foods like meat, fruits, and beverages. However, the temperature of tissue samples can change their dielectric properties, affecting their impedance. This research investigated the effects of temperature on the impedance of various biological tissues over the frequency range of 10 Hz to 5 MHz. Freshly excised animal tissues (lamb, cow, chicken), fish, fruits, and plants were considered as biological samples. The samples were placed in a test cell and submerged in a water bath heated by a hot plate to vary the temperature. Impedance measurements were conducted using a bioimpedance spectrometer in 2 °C steps within the temperature range of 20 °C to 50 °C. Impedance values decreased with increased temperature across all measurement frequencies for all biological samples. Curve fitting indicated that impedance decreased linearly with temperature, with a mean correlation coefficient of 0.972 for all samples. For all biological samples under investigation, the relative impedance change ranged from -0.58% to -2.27% per °C, with a mean and standard deviation of (-1.42±0.34) %/°C. On average, animal samples exhibited a higher relative temperature coefficient of -1.56% per °C (±0.41) across the frequency range, compared to -1.31% per °C (±0.26) for fruit and vegetable samples. Additionally, the relative temperature coefficient values were generally higher at lower frequencies than at higher frequencies. The findings of this research can be valuable for studies or biomedical applications involving variable tissue temperatures.

Determination of a Measurement Procedure for the Study of Cells' Dielectric Properties through Descriptive Statistic

This paper presents a measurement procedure for analyzing the dielectric properties of cells using descriptive statistics. The study focuses on four cancer cell lines (MDA-MB-231 and MCF-7 breast cancer, SaOS-2, and 143B osteosarcoma) and DMEM culture medium, utilizing the Lorentzian fit model of the return-loss function. The measurements are performed using a circular patch resonator with a 40 mm diameter, powered by a miniVNA operating in the frequency range of 1 MHz to 3 GHz. Eight specimens are prepared for each group to ensure reliability, and the return loss is recorded ten times for each specimen. Various statistical parameters are calculated and evaluated, including the average value, standard deviation, coefficient of variation, and relative error between the average and the first values. The results demonstrate that one single acquisition highly represents the entire set of ten data points, especially for the resonant frequency, with an accuracy error lower than 0.05%. These findings have significant implications for the methodological approach to detecting cells' dielectric properties, as they substantially reduce time and preserve the specimens without compromising the accuracy of the experimental results.

System Performance and User Feedback Regarding Wearable Bioimpedance System for Multi-Site Knee Tissue Monitoring: Free-Living Pilot Study With Healthy Adults

Knee-focused wearable devices have the potential to support personalized rehabilitation therapies by monitoring localized tissue alterations related to activities that reduce functional symptoms and pain. However, supporting these applications requires reported data to be reliable and accurate which can be challenging in the unsupervised free-living conditions that wearable devices are deployed. This pilot study has assessed a knee-focused wearable sensor system to quantify 1) system performance (operation, rates of data artifacts, environment impacts) to estimate realistic targets for reliable data with this system and 2) user experiences (comfort, fit, usability) to help inform future designs to increase usability and adoption of knee-focused wearables. Study data was collected from five healthy adult participants over 2 days, with 84.5 and 35.9% of artifact free data for longitudinal and transverse electrode configurations. Small to moderate positive correlations were also identified between changes in resistance, temperature, and humidity with respect to acceleration to highlight how this system can be used to explore relationships between knee tissues and environmental/activity context.

Electrical Impedance Tomography Technical Contributions for Detection and 3D Geometric Localization of Breast Tumors: A Systematic Review

Impedance measuring acquisition systems focused on breast tumor detection, as well as image processing techniques for 3D imaging, are reviewed in this paper in order to define potential opportunity areas for future research. The description of reported works using electrical impedance tomography (EIT)-based techniques and methodologies for 3D bioimpedance imaging of breast tissues with tumors is presented. The review is based on searching and analyzing related works reported in the most important research databases and is structured according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) parameters and statements. Nineteen papers reporting breast tumor detection and location using EIT were systematically selected and analyzed in this review. Clinical trials in the experimental stage did not produce results in most of analyzed proposals (about 80%), wherein statistical criteria comparison was not possible, such as specificity, sensitivity and predictive values. A 3D representation of bioimpedance is a potential tool for medical applications in malignant breast tumors detection being capable to estimate an ap-proximate the tumor volume and geometric location, in contrast with a tumor area computing capacity, but not the tumor extension depth, in a 2D representation.

A Multi-Frequency Focused Impedance Measurement System Based on Analogue Synchronous Peak Detection

Monitoring of anatomical structures and physiological processes by electrical impedance has attracted scientists as it is noninvasive, nonionizing and the instrumentation is relatively simple. Focused Impedance Method (FIM) is attractive in this context, as it has enhanced sensitivity at the central region directly beneath the electrode configuration minimizing contribution from neighboring regions. FIM essentially adds or averages two concentric and orthogonal combinations of conventional Tetrapolar Impedance Measurements (TPIM) and has three versions with 4, 6, and 8 electrodes. This paper describes the design and testing of a multi-frequency FIM (MFFIM) system capable of measuring all three versions of FIM at 8 frequencies in the range 10 kHz—1 MHz. A microcontroller based multi-frequency signal generator and a balanced Howland current source with high output impedance (476 kΩ at 10 kHz and 58.3 kΩ at 1 MHz) were implemented for driving currents into biological tissues with an error <1%. The measurements were carried out at each frequency sequentially. The peak values of the amplified voltage signals were measured using a novel analogue synchronous peak detection technique from which the transfer impedances were obtained. The developed system was tested using TPIM measurements on a passive RC Cole network placed between two RC networks, the latter representing skin-electrode contact impedances. Overall accuracy of the measurement was very good (error <4% at all frequencies except 1 MHz, with error 6%) and the resolution was 0.1 Ω. The designed MFFIM system had a sampling rate of >45 frames per second which was deemed adequate for noninvasive real-time impedance measurements on biological tissues.

Electrical Impedance Tomography - Recent Applications and Developments

Electrical impedance tomography (EIT) is a low-cost noninvasive imaging method. The main purpose of this paper is to highlight the main aspects of the EIT method and to review the recent advances and developments. The advances in instrumentation and in the different image reconstruction methods and systems are demonstrated in this review. The main applications of the EIT are presented and a special attention made to the papers published during the last years (from 2015 until 2020). The advantages and limitations of EIT are also presented. In conclusion, EIT is a promising imaging approach with a strong potential that has a large margin of progression before reaching the maturity phase.