The variability of dielectric permittivity of biological tissues with water content

2021 ◽  
pp. 1-21
Author(s):  
S. Di Meo ◽  
J. Bonello ◽  
I. Farhat ◽  
L. Farrugia ◽  
M. Pasian ◽  
...  
Keyword(s):  
Dielectric Permittivity ◽  
Water Content ◽  
Biological Tissues

scholarly journals Numerical Sensitivity Analysis for Dielectric Characterization of Biological Samples by Open-Ended Probe Technique

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3756
Author(s):  
Marta Cavagnaro ◽  
Giuseppe Ruvio
Keyword(s):  
Water Content ◽  
Ex Vivo ◽  
High Water ◽  
Biological Tissues ◽  
Fundamental Aspect ◽  
High Water Content ◽  
Insertion Depth ◽  
Dielectric Characterization

Dielectric characterization of biological tissues has become a fundamental aspect of the design of medical treatments based on electromagnetic energy delivery and their pre-treatment planning. Among several measuring techniques proposed in the literature, broadband and minimally-invasive open-ended probe measurements are best-suited for biological tissues. However, several challenges related to measurement accuracy arise when dealing with biological tissues in both ex vivo and in vivo scenarios such as very constrained set-ups in terms of limited sample size and probe positioning. By means of the Finite Integration Technique in the CST Studio Suite® software, the numerical accuracy of the reconstruction of the complex permittivity of a high water-content tissue such as liver and a low water-content tissue such as fat is evaluated for different sample dimensions, different location of the probe, and considering the influence of the background environment. It is found that for high water-content tissues, the insertion depth of the probe into the sample is the most critical parameter on the accuracy of the reconstruction. Whereas when low water-content tissues are measured, the probe could be simply placed in contact with the surface of the sample but a deeper and wider sample is required to mitigate biasing effects from the background environment. The numerical analysis proves to be a valid tool to assess the suitability of a measurement set-up for a target accuracy threshold.

Variation of Electrical Conductivity With Water Content in Agarose Gel

2002 ◽  
Author(s):  
Adriana L. Vega ◽  
Hai Yao ◽  
Marc-Antoine Justiz ◽  
Weiyong Gu
Keyword(s):  
Electrical Conductivity ◽  
Water Content ◽  
Normal Tissue ◽  
Tumor Tissue ◽  
Biological Tissues ◽  
Specific Electrical Conductivity ◽  
Agarose Gel ◽  
Similar Relationship ◽  
Ion Concentrations ◽  
The Relationship

Specific electrical conductivity, a material property of biological tissues, has been found to be greater in tumor tissue than in normal tissue on account of its higher water content [1]. Its value is related to water content, ion concentrations, and ion diffusivities within biological tissues [e.g., 1,2,3]. The variation in conductivity with water content is hypothesized to be related to the change in ion diffusivities [5,6]. The objective of this study is to investigate the relationship between conductivity and water content in hydrogels. The main goal is to develop a similar relationship for biological tissues and to understand deformation-dependent ion diffusivity in tissues under mechanical loading.

Enhancing modelled water content by dielectric permittivity in stony soils

Soil Research ◽  
2016 ◽  
Vol 54 (3) ◽  
pp. 360 ◽  
Author(s):  
M. Pakparvar ◽  
W. Cornelis ◽  
D. Gabriels ◽  
Z. Mansouri ◽  
S. A. Kowsar
Keyword(s):  
Dielectric Permittivity ◽  
Water Content ◽  
Mixture Model ◽  
Model Performance ◽  
Time Domain Reflectometry ◽  
Soil Conditions ◽  
Probe Type ◽  
Regression Equations ◽  
Deep Well ◽  
Reflection Time

Applicability of time domain reflectometry (TDR) under naturally distributed stone fragments in soils has seldom been investigated. A multilayer profile of a 30-m-deep well was sampled and the natural distribution of stone fragments in the soils was replicated in the laboratory. Gravimetric soil water content (SWC) was measured simultaneously with TDR dielectric permittivity (Ka) readings and bulk densities in three subsamples as replications. Two connector and buriable probes and three reflection-time capture windows (10, 20 and 40 ns) were used for the measurements. These were repeated for sieved soil samples <2 mm with fixed, pre-measured bulk densities. Measurements of Ka and observed SWC were repeated for extension-cable lengths of 3–30 m. All measurements were taken in samples saturated from the bottom. A semi-empirical mixture model was applied for different fractions of stony samples in order to convert bulk Ka to bulk volumetric SWC (θv) by the mixture model (θvmx), to be compared with θv by the conventional Topp equation (θvTp). An improvement in model performance was observed with lower root-mean-square error (RMSE, 0.02–0.04 v. 0.07–0.1) and ratio of RMSE to observation standard deviation (0.32–0.87 v. 1.07–3.05) for θvmx compared with θvTp. This approach for converting the in-situ measured dielectric permittivity to the θv of the bulk soil can be applied based on the determined stoniness. The 15-cm, 2-rod (connector) probe type with capture windows 20 ns resulted in a better performance than the 20-cm, 3-rod (buriable) probe type with capture windows 10 and 40 ns. Development of regression equations for the stone-free samples resulted in calibrated equations for converting the measured Ka to θv with better results (RMSE ~0.002 m3 m–3) than those obtained using the Topp equation. In contrast to the traditional equation, new sets of coefficients for the Topp equation were also capable of estimating extremely low θv values of ≤0.02 m3 m–3 where the minimum calculated θv values were adequately similar to the observed ones. Noticeable effects of cable length on measured Ka were found for lengths exceeding 10 m. Accurate Ka values might be obtained in similar soil conditions if the suggested regression equations are employed, provided a correction is made for the extension cables.

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