The Effect of Contrasts in Electrical and Mechanical Properties between Breast Tissues on Harmonic Motion Microwave Doppler Imaging Signal

Irgin U., Top C. B., GENÇER N. G.

IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, vol.5, pp.362-370, 2021 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 5
  • Publication Date: 2021
  • Doi Number: 10.1109/jerm.2021.3075343
  • Journal Name: IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus
  • Page Numbers: pp.362-370
  • Keywords: Hidden Markov models, Microwave theory and techniques, Microwave imaging, Microwave oscillators, Mathematical model, Computational modeling, Doppler effect, Breast cancer detection, Discrete Dipole Approximation, Harmonic Motion Microwave Doppler Imaging (HMMDI), tissue dielectric and elastic properties, DISCRETE-DIPOLE APPROXIMATION, WAVE-PROPAGATION, DIELECTRIC-PROPERTIES, ELASTIC-MODULI, LARGE-SCALE, EX-VIVO, SIMULATION, SCATTERING
  • Middle East Technical University Affiliated: Yes


IEEEHarmonic Motion Microwave Doppler Imaging (HMMDI) method employs concurrent tissue excitation with focused ultrasound radiation force and microwaves to obtain information on malignancy, based on the dielectric and mechanical properties of the tissues. In this study, we analyze the effect of dielectric and elastic contrasts between a small (tumor) inclusion (3 mm) and the surrounding normal tissue on the HMMDI signal as functions of inclusion position and vibration frequency (from 10 Hz to 95 Hz) using simulations. To solve the forward problem of HMMDI, we developed a Discrete Dipole Approximation (DDA) based simulation method, and analyzed the received HMMDI signal for low to medium dielectric contrast (1:1.17, 1:2.6, 1:3.5) and elastic contrast (1:1.5, 1:2.5, 1:5) levels. DDA solver decreased the simulation time by a factor of 146 compared to the Finite Difference Time Domain method and facilitated the extensive number of simulations required for the analysis. The results of this study provide useful information for the development of the HMMDI method as a tool for breast cancer detection in dense tissues.