The Electromagnetic Acoustic (EMA) technique is a novel multi-modal technique for medical imaging. It is sensitive, in principle, to contrast in mechanical properties and electrical properties and has potential in a number of applications such as breast tumour detection where there will be contrast between diseased and healthy tissue and high intensity focused ultrasound monitoring, where there will be contrast when tissue is ablated. A complete computational model for the EMA imaging is developed. The model considers the linear or nonlinear propagation of ultrasound in soft tissue, the dynamic response of the viscoelastic soft tissue to acoustic radiation force (ARF) stimulation and scattering of electromagnetic waves with and without the Doppler effect. The suitability of the EMA imaging for breast tumour detection is evaluated, modelling a tumour as a spherical inclusion in an infinite homogeneous background tissue with clinically relevant material properties. The results show that variations of the mechanical properties of underlying healthy breast tissue and tumour tissue in clinically feasible range should result in a change in the amplitude of the first Doppler component (FDC) of up to 50%, and varying the electrical contrast leads to a change in the ratio of the FDC and unshifted component (UC) of less than 1 dB. The relative difference between the first Doppler component and the unshifted component is greater than 68 dB and therefore the frequency demodulation may pose a significant challenge if EMA imaging is used for breast tumour detection. The feasibility of using the EMA imaging for real-time monitoring of High Intensity Focused Ultrasound (HIFU) therapy is also investigated. Simulations conducted with realistic liver tissue properties show that the induced Doppler effect in the scattered EM wave is not well correlated with the growth of thermal lesion, therefore it is unlikely to be a good indicator of the lesion size. EMA imaging may not be appropriate for monitoring HIFU therapy.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:712429 |
| Date | January 2015 |
| Creators | Zhang, Ning |
| Contributors | Cleveland, Robin ; Edwards, David |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://ora.ox.ac.uk/objects/uuid:2c4c9946-b90c-43a3-9039-1c7df2dcd976 |
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