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

How much do we know about the metastatic process?

Cancer cells can leave their primary sites and travel through the circulation to distant sites, where they lodge as disseminated cancer cells (DCCs), even during the early and asymptomatic stages of tumor progression. In experimental models and clinical samples, DCCs can be detected in a non-proliferative state, defined as cellular dormancy. This state can persist for extended periods until DCCs reawaken, usually in response to niche-derived reactivation signals. Therefore, their clinical detection in sites like lymph nodes and bone marrow is linked to poor survival. Current cancer therapy designs are based on the biology of the primary tumor and do not target the biology of the dormant DCC population and thus fail to eradicate the initial or subsequent waves of metastasis. In this brief review, we discuss the current methods for detecting DCCs and highlight new strategies that aim to target DCCs that constitute minimal residual disease to reduce or prevent metastasis formation. Furthermore, we present current evidence on the relevance of DCCs derived from early stages of tumor progression in metastatic disease and describe the animal models available for their study. We also discuss our current understanding of the dissemination mechanisms utilized by genetically less- and more-advanced cancer cells, which include the functional analysis of intermediate or hybrid states of epithelial-mesenchymal transition (EMT). Finally, we raise some intriguing questions regarding the clinical impact of studying the crosstalk between evolutionary waves of DCCs and the initiation of metastatic disease.

A low-cost, portable 32-channel EIT system with four rings based on AFE4300 for body composition analysis

A proposed low-cost, portable, 32-channel (4 rings of 8-channel) Electrical Impedance Tomography (EIT) system based on the AFE4300 analog front-end for body composition measurement. Each ring allows obtaining the conductivity distribution of 4 cross sections, 4 cm apart; to analyze the behavior of conductivity in a volume. The switching of the 4 rings and the current injection and voltage measurement patterns are done with three Texas Instruments 74HC4067 multiplexers, which are managed by an ESP32 board. The proposed system has an average signal-to-noise ratio of 74.71 dB and a frame rate of 50 fps. The sensitivity tests to impedance and volume changes consisted of introducing 4 tubes of different diameters (2 steel and 2 polyvinyl chloride) into a tank with saline solution; then conductivity distribution images were generated in 4 cross-sections of the tank, using the algorithms Gauss-Newton and Noser. Finally, the global impedance index (GI) is calculated to estimate the volume of each tube inside the tank. The results show that the proposed system is highly sensitive to impedance and volume changes, being a promising system for monitoring tissues, and fluids biological.

Automated Computer-Assisted Medical Decision-Making System Based on Morphological Shape and Skin Thickness Analysis for Asymmetry Detection in Mammographic Images

Breast cancer is a significant health concern for women, emphasizing the need for early detection. This research focuses on developing a computer system for asymmetry detection in mammographic images, employing two critical approaches: Dynamic Time Warping (DTW) for shape analysis and the Growing Seed Region (GSR) method for breast skin segmentation. The methodology involves processing mammograms in DICOM format. In the morphological study, a centroid-based mask is computed using extracted images from DICOM files. Distances between the centroid and the breast perimeter are then calculated to assess similarity through Dynamic Time Warping analysis. For skin thickness asymmetry identification, a seed is initially set on skin pixels and expanded based on intensity and depth similarities. The DTW analysis achieves an accuracy of 83%, correctly identifying 23 possible asymmetry cases out of 20 ground truth cases. The GRS method is validated using Average Symmetric Surface Distance and Relative Volumetric metrics, yielding similarities of 90.47% and 66.66%, respectively, for asymmetry cases compared to 182 ground truth segmented images, successfully identifying 35 patients with potential skin asymmetry. Additionally, a Graphical User Interface is designed to facilitate the insertion of DICOM files and provide visual representations of asymmetrical findings for validation and accessibility by physicians.

Case-Specific Focal Sensor Design for Cardiac Electrical Impedance Tomography

Electrical impedance tomography (EIT) is a non-invasive detection technology that uses the electrical response value at the boundary of an observation field to image the conductivity changes in an area. When EIT is applied to the thoracic cavity of the human body, the conductivity change caused by the heartbeat will be concentrated in a sub-region of the thoracic cavity, that is, the heart region. In order to improve the spatial resolution of the target region, two sensor optimization methods based on conformal mapping theory were proposed in this study. The effectiveness of the proposed method was verified by simulation and phantom experiment. The qualitative analysis and quantitative index evaluation of the reconstructed image showed that the optimized model could achieve higher imaging accuracy of the heart region compared with the standard sensor. The reconstruction results could effectively reflect the periodic diastolic and systolic movements of the heart and had a better ability to recognize the position of the heart in the thoracic cavity.