Abstract
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.
Highlights
The complex permittivity of materials underlies their interaction with electromagnetic (EM)fields and provides information on how EM energy is absorbed and dissipated
Plane to the vector network analyser (VNA) test port, using only standard and repeatable coaxial we propose a shift of the calibration plane to the VNA test port, using open and short circuits as well as a matched load, which greatly simplifies the procedure and facilitates only standard and repeatable coaxial open and short circuits as well as a matched load, which greatly measurements in challenging scenarios such as sterile environments where in-vivo measurements are simplifies the procedure and facilitates measurements in challenging scenarios such as sterile sought
We evaluated the performance of the artificial neural networks (ANN) at
Summary
The complex permittivity of materials underlies their interaction with electromagnetic (EM)fields and provides information on how EM energy is absorbed and dissipated. Accurate knowledge of the complex permittivity of human tissues is crucial in the design and development of diagnostic and therapeutic EM medical devices which are gaining increasing attention. This is because RF and MW radiation is non-ionising and has potential application in developing non- or minimally invasive theranostic devices. Accurate knowledge of the dielectric properties of essential for the creation and use of pre-treatment planning protocols, involving patient-specific 3-D human tissue is required in the device design phase but is essential for the creation and EM field simulations. This is of the specific absorption rate (SAR) at various points around the MW applicator allows for the important in the case of microwave ablation, where an accurate estimate of the specific absorption rate adjustment of input power, frequency, duration and insertion point in order to optimise the treatment (SAR) at various points around the MW applicator allows for the adjustment of input power, frequency, outcome
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