A Combined Experiment and Modeling Approach for Advancing Terahertz Imaging of Three Dimensional Breast Cancer Tumors

提案题目：一种推进乳腺肿瘤三维太赫兹成像的联合实验与建模方法。该项目将在癌组织的成像和传感应用方面做出重要贡献，并将在诊断癌性切除乳腺样本方面取得重大进展。它将产生重大的社会影响，并将导致医疗保健方面的大量节省。推进太赫兹成像算法将影响太赫兹技术在国防、国家安全和工业中的其他应用。许多被诊断为早期乳腺癌的妇女选择保乳乳房肿瘤切除术。不幸的是，在20-70%的乳房肿瘤切除术中，肿瘤边缘呈阳性，在第一次手术中无法发现，必须进行第二次手术以切除剩余的肿瘤。手术之间的这种延迟增加了乳腺癌治疗的成本和风险。拟议中的研究将对女性产生重大影响？通过推进肿瘤边缘的评估，降低肿瘤复发率和死亡率，从而提高乳腺癌患者的生活质量。如果这项研究成功，将减少第二次手术的比率，从而减少健康保险费用。该项目还将通过让研究生和本科生参与太赫兹技术的实践培训，影响教育和研究项目，并将为从阿肯色大学建立的多元化项目中招募的代表性不足和少数民族学生提供独特的培训机会。推进太赫兹成像算法将极大地有利于国防、国家安全和半导体工业的其他潜在应用。本研究的目的是推进太赫兹成像在保乳乳房肿瘤切除术中对切除的乳腺癌肿瘤边缘的实时评估。太赫兹技术最近成为一种很有前途的医学成像方式，因为它提供了对生物组织的非破坏性、非侵入性和实时评估。太赫兹成像使用电磁辐射，可以检索癌症组织的结构和化学属性信息，这可能是其他技术无法看到的。提出的方法将结合电磁建模、太赫兹测量和图像重建算法，以提供肿瘤边缘的定量分析。时域有限差分法将作为主要的电磁模型来模拟太赫兹与癌组织的相互作用。德拜模型将使用各种组织样本的实验光谱测量来开发。该模型的使用将促进对太赫兹波与现实的、三维的、高度异质的肿瘤组织相互作用的基本物理学的理解。太赫兹技术在乳腺癌肿瘤边缘评估中的成功应用，将为未来术中使用的稳健、准确的成像技术奠定基础。拟议的研究将为整合工程知识和医学成像研究开辟未来的机会。

Proposal Title: A Combined Experiment and Modeling Approach for Advancing Terahertz Imaging of Three Dimensinal Breast Cancer Tumors.Institution: Unniversity of ArkansasThis project will make important contributions in imaging and sensing applications of cancerous tissue and will result in major advances in diagnosing cancerous excised breast samples . It will have a major societal impact and will result in significant savings in health care. Advancing THz imaging algorithms will impact other applications of THz technology in defense, national security and industry.Many women diagnosed with early stage breast cancer choose to have a breast-conserving lumpectomy. Unfortunately, in 20-70% of lumpectomy surgeries, the tumor has positive margins that cannot be identified during the first surgery, and a second surgery must be performed to remove the remaining cancer. This delay between surgeries adds to both the cost and risk of breast cancer treatment. The proposed research will significantly impact women?s health by advancing the assessment of tumor margins, reducing cancer recurrence and mortality, and thereby improving the quality of life for breast cancer patients. The success of this research will lead to a decrease in the rate of second surgeries and hence a reduction in health insurance cost. The project will also impact education and research programs by involving graduate and undergraduate students in hands-on training with terahertz technology and will provide unique training opportunities for underrepresented and minority students who will be recruited from well-established diversity programs at the University of Arkansas. Advancing terahertz imaging algorithms will greatly benefit other potential applications in defense, national security, and the semiconductor industry. The goal of this research is to advance terahertz imaging for real-time assessment of excised breast cancer tumor margins in breast-conserving lumpectomy surgery. Terahertz technology has recently emerged as a promising medical imaging modality as it provides non-destructive, non-invasive, and real-time evaluation of biological tissue. Terahertz imaging uses electromagnetic radiation that can retrieve information of the structural and chemical attributes of cancer tissue that may not be visible with other techniques. The proposed approach will incorporate electromagnetic modeling, terahertz measurements, and image reconstruction algorithms to offer quantitative analysis of tumor margins. The finite difference time domain method will be employed as the primary electromagnetic model to simulate the terahertz interaction with cancer tissue. The Debye model will be developed using the experimental spectroscopy measurements of various tissue samples. The use of this model will advance the understanding of the fundamental physics involved in terahertz wave interaction with realistic, three dimensional, highly heterogeneous tumor tissues. The success of using terahertz technology in the assessment of breast cancer tumor margins will lay the groundwork for future robust and accurate imaging techniques than can be used intraoperatively. The proposed research will open future opportunities for integrating engineering knowledge and medical imaging research.