A Water Dependent Tissue Dielectric Model for Estimation of in-vivo Dielectric Properties

Author(s):  
Atif Shahzad ◽  
Adnan Elahi ◽  
Paidrig Donlon ◽  
Martin O'Halloran
Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7644
Author(s):  
Gertjan Maenhout ◽  
Tomislav Markovic ◽  
Bart Nauwelaers

In order to design electromagnetic applicators for diagnostic and therapeutic applications, an adequate dielectric tissue model is required. In addition, tissue temperature will heavily influence the dielectric properties and the dielectric model should, thus, be extended to incorporate this temperature dependence. Thus, this work has a dual purpose. Given the influence of temperature, dehydration, and probe-to-tissue contact pressure on dielectric measurements, this work will initially present the first setup to actively control and monitor the temperature of the sample, the dehydration rate of the investigated sample, and the applied probe-to-tissue contact pressure. Secondly, this work measured the dielectric properties of porcine muscle in the 0.5–40 GHz frequency range for temperatures from 20 ∘C to 45 ∘C. Following measurements, a single-pole Cole–Cole model is presented, in which the five Cole–Cole parameters (ϵ∞, σs, Δϵ, τ, and α) are given by a first order polynomial as function of tissue temperature. The dielectric model closely agrees with the limited dielectric models known in literature for muscle tissue at 37 ∘C, which makes it suited for the design of in vivo applicators. Furthermore, the dielectric data at 41–45 ∘C is of great importance for the design of hyperthermia applicators.


2019 ◽  
Vol 68 (2) ◽  
pp. 512-524 ◽  
Author(s):  
Yuan Gao ◽  
Mohammad Tayeb Ghasr ◽  
Michael Nacy ◽  
Reza Zoughi

Author(s):  
Saqib Salahuddin ◽  
Alessandra La Gioia ◽  
Muhammad Adnan Elahi ◽  
Emily Porter ◽  
Martin O'Halloran ◽  
...  

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Emre Onemli ◽  
Sulayman Joof ◽  
Cemanur Aydinalp ◽  
Nural Pastacı Özsobacı ◽  
Fatma Ateş Alkan ◽  
...  

AbstractMammary carcinoma, breast cancer, is the most commonly diagnosed cancer type among women. Therefore, potential new technologies for the diagnosis and treatment of the disease are being investigated. One promising technique is microwave applications designed to exploit the inherent dielectric property discrepancy between the malignant and normal tissues. In theory, the anomalies can be characterized by simply measuring the dielectric properties. However, the current measurement technique is error-prone and a single measurement is not accurate enough to detect anomalies with high confidence. This work proposes to classify the rat mammary carcinoma, based on collected large-scale in vivo S$$_{11}$$ 11 measurements and corresponding tissue dielectric properties with a circular diffraction antenna. The tissues were classified with high accuracy in a reproducible way by leveraging a learning-based linear classifier. Moreover, the most discriminative S$$_{11}$$ 11 measurement was identified, and to our surprise, using the discriminative measurement along with a linear classifier an 86.92% accuracy was achieved. These findings suggest that a narrow band microwave circuitry can support the antenna enabling a low-cost automated microwave diagnostic system.


2016 ◽  
Vol 44 (4) ◽  
pp. 293-318
Author(s):  
Everette C. Burdette ◽  
Joseph Seals ◽  
Stephen P. Auda ◽  
Aishwarya D. Ambhire ◽  
Richard L. Magin

Sign in / Sign up

Export Citation Format

Share Document