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Results from EM breast examinations provide statistical evidence of a mean increase in image contrast of 150%-200% between abnormal (benign and malignant) and normal breast tissue.

We have developed a microwave tomography system for experimental breast imaging. In this paper we illustrate a strategy for optimizing the coupling liquid for the antenna array based on in vivo measurement data. We present representative phantom experiments to illustrate the imaging system's ability to recover accurate property distributions over the range of dielectric properties expected to be encountered clinically. To demonstrate clinical feasibility and assess the microwave properties of the normal breast in vivo, we summarize our initial experience with microwave breast exams of 43 women categorized as BIRADS 1. The clinical results show a high degree of bilateral symmetry in the whole breast average microwave properties. Focal assessments of microwave properties are associated with breast tissue composition evaluated through radiographic density categorization verified through MR image correlation in selected cases. Specifically, both whole breast average and local microwave properties increase with increasing radiographic density where the latter exhibits a more substantial rise. These findings support our hypothesis that water content variations in the breast play an influential role in dictating the overall dielectric property distributions and indicate that the microwave properties in the breast are more heterogeneous than previously believed based on ex vivo property measurements reported in the literature.

This paper describes an inverse reconstruction technique based on a modified Newton Raphson iterative scheme and the finite element method, which has been developed for computing the spatial distribution of Young's modulus from within soft tissues. Computer simulations were conducted to determine the relative merits of reconstructing tissue elasticity using knowledge of (a) known displacement boundary conditions (DBC), and (b) known stress boundary conditions (SBC). The results demonstrated that computing Young's modulus using knowledge of SBC allows accurate quantification of Young's modulus. However, the quality of the images produced using this reconstruction approach was dependent on the Young's modulus distribution assumed at the start of the reconstruction procedure. Computing Young's modulus from known DBC provided relative estimates of tissue elasticity which, despite the disadvantage of not being able to accurately quantify Young's modulus, formed images that were generally superior in quality to those produced using the known SBC, and were not affected by the trial solution. The results of preliminary experiments on phantoms demonstrated that this reconstruction technique is capable in practice of improving the fidelity of tissue elasticity images, reducing the artefacts otherwise present in strain images, and recovering Young's modulus images that possess excellent spatial and contrast resolution.

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