Graduate Thesis Or Dissertation


Exploring Novel Contrast Agents with Anthropomorphic Mesh Models in MCNP Public Deposited

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  • Breast cancer is the leading cancer in women with an estimated 13% of women in the United States developing a form of invasive breast cancer in her lifetime. The survival rate is estimated to be 85%, but the American Cancer Society estimates that early detection of breast cancer in the localized stage increases the breast cancer survival rate to 99%. However, early detection is dependent on the sensitivity of breast imaging techniques and currently, the sensitivity is suboptimal for women with dense breasts and obscure cancers. Recently, studies have indicated that exploring new contrast agents can provide access to improved sensitivity because of their potential to increase the effective Z of the target tissue. Furthermore, contrast-enhanced tomosynthesis is a viable imaging method that can provide a 3D view of the breast while providing tumor enhancement for improved visibility. This project aims to facilitate the search for practical contrast agents that can improve sensitivity during breast imaging. More specifically, the objective of this project is to find novel ways to improve the differentiation between tumor and glandular tissue by creating a realistic anthropomorphic model that not only considers the geometry of the breast but its physiological components as well. This project aims to combine tomosynthesis breast imaging methods with novel contrast agents to explore their efficacy and limitations. To achieve the goals of this project, several techniques are employed. A realistic tomosynthesis environment is created by constructing a detailed Hologic tomosynthesis breast imaging machine, including the source, flat-panel detector, and support equipment, using MCNP. Realistic breast phantoms that consider geometric and biophysical accuracy are created by incorporating a time dependency into the model. Once the contrast agents are incorporated, their efficacy is calculated by quantifying tumor visibility as a function of breast size, density, tumor location, tumor stage, and tumor type. After running simulations, this project will generate clear and accurate radiographs demonstrating the structural components of the breast and the effects of contrast enhancement on any embedded tumors. The results will provide an indication of the contrast agents that provide promise. The data acquired in this project will provide insight on the process of creating an anthropomorphic breast phantom for tomosynthesis studies, as well as insight on setbacks that are identified with the methods used. Contrast-enhanced tomosynthesis is clinically possible and is a promising technique for improving sensitivity. This project explores this technique and provides insight on possible ways to improve breast imaging sensitivity.
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