Complex Permittivity Of Biological Tissues Research Articles

The Complex Permittivity of Biological Tissues: A Practical Measurement Guideline

The Complex Permittivity of Biological Tissues: A Practical Measurement Guideline

Permittivity measurement of biological tissues using interdigital capacitor based resonator

A CPW resonator etched on the central conductor is presented to measure the complex permittivity of biological tissues. In the unloaded condition, the proposed structure works as a resonator with a resonant frequency of 5.625 GHz. The proposed sensor is able to cover a wide range of permittivity measurement from approximately 5 (fat tissue) to 70 (malignant tissue) with sensitivity of 4.01 % and FDR( Frequency Detection Resolution) of 270 MHz . Breast phantoms with high fidelity need to be fabricated to imitate the various layers of the breast like skin, fat, glandular tissue, and tumor tissue regarding permittivity with different chemicals in different proportions. The major challenge in fabricating such phantoms is in creating an appropriate combination of substances to get the required characteristics for these biological tissues. A sample of various tissue types was fabricated using Gelatin and safflower-based recipes. The complex permittivity tissue phantoms are measured using a fabricated resonator. The measured dielectric characteristics of biological tissues are in good agreement with the theoretical values from the database.

A Review of Magnetic Field Emissions From the Human Body: Sources, Sensors, and Uses

It has long been common practice to capture the electric fields emanated by the human body as a means of detecting and/or monitoring diverse health conditions. However, these electric fields are strongly impacted by the complex permittivity of biological tissues which deteriorates their waveforms and limits their diagnostic capabilities. As an alternative, recent progress has been made in the measurement of bio-magnetic fields occur from the natural currents flowing through the body. The advantage in this case is, since tissues are non-magnetic, magnetic fields propagate in an uninterrupted manner towards the skin surface where they are eventually collected. This unveils game-changing opportunities for future medical diagnostics. Nevertheless, a major challenge associated with sensing these naturally emanated magnetic fields is that they are extremely weak, and in fact orders of magnitude smaller than those generated by the Earth. To this end, extensive efforts have been pursued to realize sensing technology that is sensitive enough to collect bio-magnetic fields. Example fields of use include magnetomyography (MMG), magnetocardiography (MCG), magnetoencephalography (MEG), and Magnetoneurography (MNG) (including magnetospinography (MSG)). This review will provide an overview of technologies used to sense bio-magnetic fields, list their merits and limits in a critical manner, and discuss clinical applications.

Study of Freezing and Defrosting Effects on Complex Permittivity of Biological Tissues

In this letter we study the effect of freezing and defrosting on the dielectric properties of biological tissues. The electromagnetic characterization of tissues at microwave frequencies is crucial for the development of microwave-based biomedical devices. These measurements are often not practical, as tissue degradation restricts the time available between tissue excision and dielectric measurements. For this reason, measurement of tissues that underwent freezing and defrosting may provide researchers with more flexibility in setting measurement campaigns, thus speeding up the development of microwave-based biomedical devices. To this end, this letter presents dielectric measurement on frozen and defrosted tissue, which translates into the following objectives: first, investigate if the dielectric properties of defrosted tissues depend on frozen storage time; second, determine if defrosted tissue dielectric properties differ from those of fresh tissues. As a result, we measure the dielectric properties of ten samples of chicken muscle, bovine liver, and bovine fat, each before and after freezing (up to 14 days) and defrosting. The measurements are performed with the open-ended coaxial probe method at the frequency band of 0.5–8.5 GHz. We observe a slight increase—less than 10%—in complex permittivity of high-water-content tissues (muscle and liver) after defrosting, and negligible effect on fat tissues.

Application of Artificial Neural Networks for Accurate Determination of the Complex Permittivity of Biological Tissue.

Medical devices making use of radio frequency (RF) and microwave (MW) fields have been studied as alternatives to existing diagnostic and therapeutic modalities since they offer several advantages. However, the lack of accurate knowledge of the complex permittivity of different biological tissues continues to hinder progress in of these technologies. The most convenient and popular measurement method used to determine the complex permittivity of biological tissues is the open-ended coaxial line, in combination with a vector network analyser (VNA) to measure the reflection coefficient (S11) which is then converted to the corresponding tissue permittivity using either full-wave analysis or through the use of equivalent circuit models. This paper proposes an innovative method of using artificial neural networks (ANN) to convert measured S11 to tissue permittivity, circumventing the requirement of extending the VNA measurement plane to the coaxial line open end. The conventional three-step calibration technique used with coaxial open-ended probes lacks repeatability, unless applied with extreme care by experienced persons, and is not adaptable to alternative sensor antenna configurations necessitated by many potential diagnostic and monitoring applications. The method being proposed does not require calibration at the tip of the probe, thus simplifying the measurement procedure while allowing arbitrary sensor design, and was experimentally validated using S11 measurements and the corresponding complex permittivity of 60 standard liquid and 42 porcine tissue samples. Following ANN training, validation and testing, we obtained a prediction accuracy of 5% for the complex permittivity.

Evolution of the complex permittivity of biological tissue at microwaves ranges: correlation study with burn depth.

The evolution of the muscle tissue's complex permittivity represents a growing interest in terms of characterization in medicine and biology. The influence of a burned part on the permittivity is not very developed. In this work, an estimation of the complex permittivity of biological tissues is performed as a function of the depth of burn tissues. The sensor, an open-ended coaxial probe, is placed directly against each sample. The evolution of the complex permittivity is studied for two measurements conditions (in the air and in a physiological solution). A correlation study is attempted with the depth of burn tissue.

Dielectric properties of biological tissues in which cells are connected by communicating junctions

The frequency dependence of the complex permittivity of biological tissues has been simulated using a simple model that is a cubic array of spherical cells in a parallel plate capacitor. The cells are connected by two types of communicating junctions: one is a membrane-lined channel for plasmodesmata in plant tissues, and the other is a conducting patch of adjoining plasma membranes for gap junctions in animal tissues. Both junctions provided similar effects on the dielectric properties of the tissue model. The model without junction showed a dielectric relaxation (called β-dispersion) that was expected from an interfacial polarization theory for a concentrated suspension of spherical cells. The dielectric relaxation was the same as that of the model in which neighbouring cells were connected by junctions perpendicular to the applied electric field. When neighbouring cells were connected by junctions parallel to the applied electric field or in all directions, a dielectric relaxation appeared at a lower frequency side in addition to the β-dispersion, corresponding to the so called α-dispersion. When junctions were randomly introduced at varied probabilities Pj, the low-frequency (LF) relaxation curve became broader, especially at Pj of 0.2–0.5, and its intensity was proportional to Pj up to 0.7. The intensity and the characteristic frequency of the LF relaxation both decreased with decreasing junction conductance. The simulations indicate that communicating junctions are important for understanding the LF dielectric relaxation in tissues.