Breast Cancer Risk Stratification with Resonant Electrical Impedance Spectroscopy

描述（由申请人提供）：虽然早期患乳腺癌的风险在人年损失的很大一部分中是低的，但这是由于40岁以下的妇女死于这种疾病。不幸的是，筛查性乳房x光检查作为40岁以上乳腺癌检测的“金标准”和公认做法，在年轻女性中表现不佳，再加上辐射风险和预期的低收益，因此建议不建议在40岁以下的普通人群中进行年度筛查。存在替代成像方式（例如MRI， US），然而，由于各种原因，这些技术并未用于此目的。如果有一种廉价、易于使用、广泛可用的技术对妇女进行预先筛查，并确定哪些人最有可能从更全面的基于成像的研究中受益，将极大地促进年轻妇女的乳腺癌检测。目前，在年轻女性中唯一普遍使用的筛查工具是临床乳腺检查（CBE）。然而，CBE的灵敏度低，假阳性率高，并且依赖于检查者。电阻抗谱（EIS）是一种很有前途的技术，可以用于筛查前的风险识别，因为它依赖于相对便宜的设备，可以广泛传播到医生的办公室，并且在检测乳腺癌方面具有一定的有效性，无论年龄或乳房密度如何。不幸的是，当需要高特异性（约90%）时，EIS技术的灵敏度相对较低（约25 - 35%）。最近开发了一种新的EIS测量方法，并在非医疗应用中相当成功地使用了这种方法。当组织成为RLC电路的一部分时，这种新方法测量了谐振频率附近阻抗的变化。我们把这种新方法称为共振电阻抗谱（REIS）。EIS在谐振频率附近的灵敏度非常高，我们相信使用这种方法（REIS）可以比以前使用EIS获得更大的诊断性能。在本研究的R21阶段，我们将构建一个原型REIS设备，用于快速评估乳房（不到10分钟），并演示使用REIS设备对女性进行预筛查的可行性，以确定谁将从诊断成像检查中受益。这不是一种乳腺癌检测设备，而是一种风险分层方法。也就是说，最终目标是开发和测试一种方法，将年轻妇女人口（< 40岁）分为两组。一种（REIS阴性）是指患乳腺癌的风险正常，另一种（REIS阳性）是指一组妇女患乳腺癌的风险大大高于目前常规筛查的老年妇女（40 - 49岁）。在R33阶段，将招募更多的患者，并将用于优化分类算法。将与现有的环境影响评估系统技术进行比较。在这个应用程序中，我们建议建立和评估一种设备，用于识别乳腺癌风险增加的绝经前妇女，从而受益于基于乳房成像的评估。这将通过一种低成本、安全的技术来实现，这种技术可以用于未接受乳房x光检查的年轻女性的常规办公室就诊。如果成功，这一建议将通过增加乳腺癌的早期发现，对公共卫生产生重大影响。

DESCRIPTION (provided by applicant): Although risk for developing breast cancer at an earlier age is low in a substantial fraction of person-years lost it is attributed to women under the age of 40 who die from this disease. Unfortunately, screening mammography, the "gold standard" and accepted practice over the age of 40 for breast cancer detection, performs poorly in younger women and combined with radiation risk and expected low yield resulted in the recommendation that annual screening in the general population is not recommended below this age. Alternative imaging modalities exist (e.g. MRI, US), however, these techniques are not being used for this purpose for a variety of reasons. It would greatly facilitate breast cancer detection in younger women if an inexpensive, easy to use, widely available technology was available to pre-screen women and determine who would most likely benefit from more comprehensive imaging based studies. Currently, the only generally used screening tool in young women is Clinical Breast Exam (CBE). However, CBE has low sensitivity, high false- positive rate and is examiner dependent. Electrical Impedance Spectroscopy (EIS) is a promising technology for fulfilling a pre-screening risk identification role as it relies on relatively inexpensive equipment that could be widely disseminated to practitioners' offices and it has demonstrated some effectiveness in detecting breast cancer regardless of age or breast density. Unfortunately, EIS technologies have demonstrated a relatively low sensitivity (~ 25 - 35%) when a high specificity (>90%) is required. Recently a new approach to EIS measurements has been developed and used quite successfully in non-medical applications. This new approach measures shifts in impedance near the resonant frequency when tissue is made a part of an RLC electric circuit. We refer to this new approach as Resonant Electrical Impedance Spectroscopy (REIS). The sensitivity of EIS near the resonant frequency is extremely high and we believe that using this approach (REIS) a much greater diagnostic performance can be achieved than was previously obtainable with EIS. In the R21 phase of this study we will build a prototype REIS device for rapidly evaluating (less than 10 minues) the breast and demonstrate feasibility for pre-screening women with the REIS device to determine who would benefit from a diagnostic imaging workup. This is not a breast cancer detection device but rather a risk stratification approach. Namely, the ultimate objective is to develop and test an approach that would segment the younger women population (< 40 years old) into two groups. One (REIS negative) that is expected to have normal risk of having breast cancer and the other (REIS positive) which identifies a group of women in which the risk of having breast cancer is substantially higher than in older women (40 - 49 years old) who are currently routinely screened. In the R33 phase a much larger patient population will be recruited and will be used to optimize the classification algorithm. Comparisons will be made with existing EIS technology. In this application we are proposing building and evaluating a device for identifying pre-menopausal women who are at increased risk for breast cancer and would thus benefit from an imaging based evaluation of the breast. This would be achieved using a low cost, safe technology that could be used during routine office visits of young women who are not screened with mammography. If successful, this proposal will have a large public health impact via increased early detection of breast cancer.