Abstract

KASHINA, Svetlana; GUZMAN CABRERA, Rafael  and  BALLEZA ORDAZ, José Marco. Advanced Electrical Modeling of Biological Tissues: New Trends and their Impact on Bioimpedance Interpretation. Comp. y Sist. [online]. 2025, vol.29, n.2, pp.967-970.  Epub Apr 20, 2026. ISSN 2007-9737.  https://doi.org/10.13053/cys-29-2-5750.

Bioimpedance is a non-invasive technique that measures the electrical properties of biological tissues to assess composition and functional states, such as water content and hydration status. Widely applied in clinical settings (e.g., dialysis, heart failure monitoring) and research (e.g., tissue engineering, tumor characterization), it is valued for its simplicity, low cost, and repeatability. However, traditional models like the Cole model and RC circuits assume tissue homogeneity and isotropy, leading to errors in heterogeneous, anisotropic tissues. Recent advancements in electrical modeling, including multilayer, anisotropic, and image-based approaches, address these limitations. Multilayer models improve heterogeneity representation in muscles and tumors, while anisotropic models using conductivity tensors enhance accuracy in electrical impedance tomography (EIT). Imaging techniques like X-ray microtomography provide 3D structural data, aiding diagnostics in skin tumors, and tools like singular perturbation theory and stereology model small inclusions and quantify tissue properties. These advances reduce extracellular fluid volume estimation errors by up to 15% and measurement errors in heterogeneous tissues by 20– 30%, improving applications like lung ventilation mapping and early pathology detection (e.g., 88% sensitivity in breast cancer). AI integration further enhances precision, achieving over 90% accuracy in heart failure fluid predictions. Clinical applications include optimized dialysis protocols and sports training, while portable EIT wearables enable real-time monitoring. Challenges persist, including standardization issues causing 10% result variability and limited AI datasets. Future efforts should focus on international standards, AI-driven diagnostics, and EIT- ultrasound integration to strengthen bioimpedance’s role in personalized medicine. These advancements revolutionize bioimpedance interpretation, enhancing diagnostic accuracy and clinical accessibility.

Keywords : Bioimpedance; interpretation; modeling; biomedicine.

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