Renewal: Terahertz Polarization Imaging for Detecting Breast Tumor Margins

项目摘要/摘要 保乳治疗(肿块切除术)是最常用的乳腺癌手术之一。 在美国。肿瘤切除手术的最佳效果是在手术切缘达到 没有癌症。当第一次手术后在手术边缘检测到癌症残留时，第二次 需要做手术才能摘除癌症。不幸的是，相当多的患者接受了乳房手术 无法获得即时现场病理的当地医院的保守性手术(BCS)，导致 再次切除或再手术率高(超过30%)。因此，有很大的需要新的 可供当地医院和门诊使用的术中技术。我们以前的 研究结论是，虽然在临床前模型中进行的太赫兹研究表明， 癌组织和脂肪组织，癌症和健康非脂肪组织之间临床上更相关的区分 组织仍然具有挑战性。在以往获奖成果的基础上进一步提高敏感度 在手术边缘的太赫兹成像癌症检测方面，我们已经确定了我们可以 显著改进仪器、动物模型和图像分析算法。 作为更新应用的一部分，我们将重新设计我们的仪器以开发太赫兹偏振- 灵敏的成像方法。在这种新的方法中，波的所有四个极化都将被合并到 增加不同类型肿瘤组织的空间和光谱信息(目标1)。我们将测试 体内系统在致癌物诱导的大鼠乳腺癌模型中的应用并使用生物组织模拟 用模体来确定太赫兹图像中的信号源(目标2)。最后，我们将改善 利用太赫兹图像中嵌入的空间信息进行检测的算法精度 统计(目标3)。目标是更好地检测健康纤维组织的存在，因为它们有潜在的生长 肿瘤中癌组织旁的健康胶原蛋白。我们预计，新提议的方法将 增加癌旁组织与健康邻近组织的图像对比度，从而更好地区分 以及肿瘤边缘的癌症分类。此续订应用程序将允许我们开发优化的 利用多极化的方法，在太赫兹图像中编码的空间信息用于 分析，并验证我们的方法对大鼠乳腺肿瘤的作用。建议的成功 研究将允许我们将工作扩展到临床试验，使用临床转换和兼容的太赫兹 技术

Project Summary/Abstract Breast-conserving therapy (lumpectomy) is one of the most commonly performed breast cancer surgeries in the United States. The best outcome of the lumpectomy surgery is achieved when the surgical margins are free of cancer. When remnants of cancer are detected at the surgical margins after the initial operation, a second operation will be required to remove the cancer. Unfortunately, a significant number of patients undergo breast conserving surgery (BCS) at local hospitals that do not have access to immediate on-site pathology leading to high rates of re-excision or reoperation (greater than 30%). Therefore, there is a significant need for new intraoperative technology that can be made available for local hospitals and outpatient clinics. Our previous research concludes that while terahertz studies in pre-clinical models have shown strong differentiation between cancerous and fatty tissues, the more clinically relevant differentiation between cancerous and healthy non-fatty tissue remains challenging. To further build upon the successes of our previous award and improve the sensitivity of terahertz imaging cancer detection on the surgical margins, we have identified areas where we can significantly improve the instrumentation, the animal model, and the image analysis algorithms. As part of this renewal application, we will re-design our instrumentation to develop terahertz polarization- sensitive imaging methodology. In this new approach, all four polarizations of the waves will be incorporated to increase the spatial and spectral information about different types of tumor tissues (Aim 1). We will test the system in vivo in a carcinogen-induced model of breast cancer in rats and use biological tissue simulating phantoms to determine the sources of signal generation in the THz images (Aim 2). Finally, we will improve the detection algorithm accuracy by exploiting the spatial information embedded in the terahertz images with spatial statistics (Aim 3). The goal is to better detect the presence of healthy fibrous tissue due to their potential growth of healthy collagen adjacent to cancerous tissues in tumors. We anticipate that the new proposed approach will increase the image contrast between cancerous and healthy adjacent tissues, leading to better differentiation and classification of cancer on the tumor margins. This renewal application will allow us to develop an optimized approach that leverages multiple polarizations, the spatial information encoded in the terahertz images for analysis, and the validation of our approach on mammary tumors from rats. The success of the proposed research will allow us to expand our work to clinical trials using clinically translational and compatible terahertz technology.