The search for non-invasive, fast, and low-cost diagnostic tools has gained significant traction among many researchers worldwide. Dielectric properties calculated from microwave signals offer unique insights into biological tissue. Material properties, such as relative permittivity (εr) and conductivity (σ), can vary significantly between healthy and unhealthy tissue types at a given frequency. Understanding this difference in properties is key for identifying the disease state. The frequency-dependent nature of the dielectric measurements results in large datasets, which can be postprocessed using artificial intelligence (AI) methods. In this work, the dielectric properties of liver tissues in three mouse models of liver disease are characterized using dielectric spectroscopy. The measurements are grouped into four categories based on the diets or disease state of the mice, i.e., healthy mice, mice with non-alcoholic steatohepatitis (NASH) induced by choline-deficient high-fat diet, mice with NASH induced by western diet, and mice with liver fibrosis. Multi-class classification machine learning (ML) models are then explored to differentiate the liver tissue groups based on dielectric measurements. The results show that the support vector machine (SVM) model was able to differentiate the tissue groups with an accuracy up to 90%. This technology pipeline, thus, shows great potential for developing the next generation non-invasive diagnostic tools.

• Klíčová slova
• dielectric spectroscopy, fibrosis, machine learning, microwave, non-alcoholic steatohepatitis, relative permittivity,
• MeSH
• jaterní cirhóza MeSH
• játra patologie   MeSH
• myši inbrední C57BL MeSH
• myši MeSH
• nealkoholová steatóza jater * diagnóza   patologie   MeSH
• strojové učení MeSH
• umělá inteligence MeSH
• zvířata MeSH
• Check Tag
• myši MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH

PURPOSE: Computational models of microwave tissue ablation are widely used to guide the development of ablation devices, and are increasingly being used for the development of treatment planning and monitoring platforms. Knowledge of temperature-dependent dielectric properties of lung tissue is essential for accurate modeling of microwave ablation (MWA) of the lung. METHODS: We employed the open-ended coaxial probe method, coupled with a custom tissue heating apparatus, to measure dielectric properties of ex vivo porcine and bovine lung tissue at temperatures ranging between 31 and 150 ∘ C, over the frequency range 500 MHz to 6 GHz. Furthermore, we employed numerical optimization techniques to provide parametric models for characterizing the broadband temperature-dependent dielectric properties of tissue, and their variability across tissue samples, suitable for use in computational models of microwave tissue ablation. RESULTS: Rapid decreases in both relative permittivity and effective conductivity were observed in the temperature range from 94 to 108 ∘ C. Over the measured frequency range, both relative permittivity and effective conductivity were suitably modeled by piecewise linear functions [root mean square error (RMSE) = 1.0952 for permittivity and 0.0650 S/m for conductivity]. Detailed characterization of the variability in lung tissue properties was provided to enable uncertainty quantification of models of MWA. CONCLUSIONS: The reported dielectric properties of lung tissue, and parametric models which also capture their distribution, will aid the development of computational models of microwave lung ablation.

• Klíčová slova
• lung ablation, lung dielectric properties, microwave ablation, temperature dependence,
• MeSH
• ablace * MeSH
• biologické modely * MeSH
• elektrická impedance MeSH
• mikrovlny MeSH
• nejistota MeSH
• plíce cytologie   účinky záření   MeSH
• prasata MeSH
• skot MeSH
• teplota * MeSH
• zvířata MeSH
• Check Tag
• skot MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH

The knowledge of frequency and temperature dependent dielectric properties of tissue is essential to develop ultra-wideband diagnostic technologies, such as a non-invasive temperature monitoring system during hyperthermia treatment. To this end, we characterized the dielectric properties of animal liver, muscle, fat and blood in the microwave frequency range from 0.5 GHz to 7 GHz and in the temperature range between 30 °C and 50 °C. The measured data were modeled to a two-pole Cole-Cole model and a second-order polynomial was introduced to fit the Cole-Cole parameters as a function of temperature. The parametric model provides access to the dielectric properties of tissue at any frequency and temperature in the specified range.

• Klíčová slova
• M-sequence, dielectric spectroscopy, open-ended coaxial probe, temperature dependent dielectric properties of blood, fat, liver, muscle, ultra-wideband,
• MeSH
• algoritmy MeSH
• biologické modely MeSH
• elektrická impedance MeSH
• impedanční spektroskopie * MeSH
• játra fyziologie   účinky záření   MeSH
• krev účinky záření   MeSH
• lidé MeSH
• mikrovlny * MeSH
• prasata MeSH
• svaly fyziologie   účinky záření   MeSH
• teplota * MeSH
• tuky účinky záření   MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• tuky MeSH