Breast Cancer Detection Using Electrical Impedance Measurements

描述(申请人提供)：这个项目的目标是开发一种计算机辅助系统，以检测乳腺异常，特别是癌症，使用电阻抗断层扫描(EIT)测量。本项目旨在开发替代和廉价的筛查工具，以帮助在乳房X光检查不确定的情况下进行诊断。我们假设不同的异常具有不同的电磁特性，因此可以使用阻抗数据来识别和分类这些特性。虽然有各种乳房成像技术可用，但我们的目标是从统计学上检测偏离正常的情况。因此，我们的项目旨在不仅获得乳房的图像，而且提供对感兴趣区域中乳房的电磁特性不同于组织的其余部分或对侧乳房中两侧对称位置的事实的概率评估。我们的项目将利用最近资助的另一种乳房成像模式项目的努力和活动。具体地说，我们将使用EIT患者数据，包括来自该项目的癌症数据。将探索三种用于统计乳房异常检测和识别的方法：(1)直接从Neumann-to-Dirichlet映射得到的乳房特征金字塔；(2)通过将潜在的Laplace偏微分方程组简化为一组耦合的常微分方程组来使用乘积-图像进行异常定位和检测；(3)利用EIT数据估计最佳正则化参数的混合模型图像重建方法。这些新的方法基于最近的数学发现，涉及魔术Toeplitz矩阵、使用表面测量对体内组织的电磁特性进行无图像重建、欧姆定律的推广形式，以及解决复杂逆问题的混合模型方法。公共卫生相关性这个项目的目标是开发一种计算机辅助系统，利用电阻抗断层扫描(EIT)测量来检测乳房异常，特别是癌症。拟议的项目旨在开发替代的、廉价的筛查工具，以帮助在乳房X光检查不确定的情况下进行诊断。我们预计，我们的方法将提高癌症检测的敏感度，特别是对于乳房组织致密的年轻女性。

DESCRIPTION (provided by applicant): The goal of this project is to develop a computer-aided system to detect abnormalities in breasts, cancer particularly, using electrical impedance tomography (EIT) measurements. The present project aims to develop alternative and inexpensive screening tools to assist in diagnosis in situations where mammography is inconclusive. We hypothesize that different abnormalities have different electromagnetic properties and therefore these properties may be identified and classified using electrical impedance data. Although various breast imaging techniques are available, our goal is to statistically detect a deviation from normality. Therefore, our project aims to not only obtain an image of the breast, but to provide a probabilistic assessment of the fact that in the region of interest, the electromagnetic properties of the breast differ from the rest of the tissue or from bilaterally symmetric locations in the contralateral breast. Our project will leverage the effort and activity from a recently funded program project on alternative breast imaging modalities. Specifically we will use, EIT patient data, including cancer data from this project. Three methods will be explored for statistical breast abnormality detection and discrimination: (1) a Breast Signature Pyramid derived directly from the Neumann-to-Dirichlet map, (2) abnormality localization and detection using the Product--Image by reducing the underlying Laplace partial differential equations into a set of coupled ordinary differential equations, (3) the Mixed Model approach to image reconstruction in which optimal regularization parameters will be estimated from the EIT data. These novel approaches are based on recent mathematical discoveries related to the magic Toeplitz matrix, imageless reconstruction of the electromagnetic properties of in vivo tissues using surface measurements, the generalized form of Ohm's law, and a mixed model approach to solving complex inverse problems. PUBLIC HEALTH RELEVANCE The goal of this project is to develop a computer-aided system to detect abnormalities in breasts, cancer particularly, using electrical impedance tomography (EIT) measurements. The proposed project aims to develop alternative and inexpensive screening tools to assist in diagnosis in situations where mammography is inconclusive. We anticipate that our methodology will improve the sensitivity of cancer detection especially for younger women with dense breast tissue.