Open-ended coaxial technique for detection of masses and microcalcifications in breast phantoms - Mohamed, Tity Nazleen (2017)
This project examined the viability of detecting masses and microcalcifications in breast phantoms using open ended coaxial technique (OEC) in the frequency range between 1 GHz and 4 GHz. The accuracy and flexibility of the OEC were tested on tomatoes and potatoes samples due to their symmetrical and non-symmetrical shapes, respectively. Both circular OEC and square OEC were used in this work. Calibration equations to predict moisture content from the measured reflection coefficient have been established. The OEC was found to be accurate within 4% in the determination of moisture content in both crops. The calculation of the reflection coefficient of tomatoes were accomplished using finite element method (FEM). Good agreement between FEM and measurement results were found for samples with 91.56% m.cat the frequency 2.5 GHz. Four phantoms were used in this work to demonstrate the feasibility of using OEC to detect masses and microcalcifications. One of the phantom was made by diluting Triton X100 with water. The other two were commercial phantoms CIRS models 052A and Model 010A designed for ultrasound and X-Ray mammography measurements. The OEC was found to have the ability to differentiate between dense and cystic masses in CIRS 052A when compared to ultrasound results. Dense masses have ԑԢ higher than 9.28 whilst the |S11|greater than 0.54. The OEC was also found to be able to distinguish specifics specks of breast phantom CIRS Model 010A based on the values of permittivity. This can be evinced by the X-ray attenuation data proportionate increased with ԑ' ,ԑ'' and |S₁₁| for the three different glandular-adipose compositions. Increasing CaCo3grain size only for the linearly distributed specks would increase the values of both the ԑ' and ԑ''. The ԑ' and ԑ'' of the epoxy cast matrix were 2.0 and 0.001 whilst the respective values for pure CaCO3 were 2.4 and 0.02 The Triton X-100 phantom allows OEC prediction of ԑ′ and ԑ′′ based on the amount of m.c which in turn can be used to identify the type of tissue which can be categorized either low, medium or high risk tissues. It is possible to detect the cancerous tissue based on the dielectric properties or m.c as the dielectric properties of normal and cancerous tissue are not similar.