Multi-modal quantitative microwave and shear wave imaging for breast tumor identification

Date

2024-8

Author

Alptekin Soydan, Damla

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Currently, mammography is used as the standard method for breast cancer screening. However, mammography has drawbacks such as the use of ionizing radiation, low sensitivity in dense breasts, and patient discomfort. To improve the diagnostic and screening performance of existing breast cancer imaging systems, research on multi-modal breast imaging systems, which use different imaging methods together, has increased recently. In this thesis study, a multi-physics, multi-modal imaging technique that combines microwave and shear wave elasticity imaging has been proposed. This method estimates both electrical and mechanical parameters of the tissue quantitatively. The quantitative permittivity map obtained from microwave imaging serves as prior information, guiding shear wave imaging to the suspicious tissues. By utilizing the quantitative Young’s modulus values obtained from shear wave imaging, breast tumors can be identified. To investigate the feasibility of the proposed method, numerical studies were conducted to solve both electromagnetic and mechanical forward and inverse problems. To demonstrate the performance of the method experimentally, microwave imaging and shear wave imaging experiments were conducted using a phantom that has fibroglandular and tumor inclusions with a diameter of 20 mm. The results showed that tumor inclusion can be identified quantitatively with a maximum relative permittivity of 41.58 and maximum Young’s modulus of 48.5 kPa. The results were found consistent with the reference ground truth values (εref rtumor = 44.8, YMref tumor = 46.7 kPa). The tumor identification was achieved through the combined use of multi-modal quantitative microwave and shear wave elasticity imaging.

Subject Keywords

breast cancer detection, multi-modal imaging, quantitative microwave imaging, shear wave elasticity imaging

URI

https://hdl.handle.net/11511/110843

Collections

Graduate School of Natural and Applied Sciences, Thesis