Breast Cancer Risk Stratification with Resonant Electrical Impedance Spectroscopy

描述(由申请人提供)：尽管在失去的人年中，较早患乳腺癌的风险很低，但40岁以下的女性死于这种疾病的风险很低。不幸的是，筛查乳房X光检查是40岁以上乳腺癌检测的“黄金标准”和公认的做法，但在年轻女性中表现不佳，再加上辐射风险和预期的低收益，导致建议不建议在普通人群中进行低于40岁的年度筛查。存在其他成像方式(例如，美国的MRI)，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、易用、随处可得的技术对女性进行预筛查，并确定谁最有可能从更全面的基于成像的研究中受益，这将极大地促进年轻女性的乳腺癌检测。目前，年轻女性唯一常用的筛查工具是临床乳房检查(CBE)。然而，CBE敏感性低，假阳性率高，且依赖于检验者。电阻抗波谱(EIS)是一种很有前途的技术，可以完成筛查前的风险识别角色，因为它依赖于相对便宜的设备，可以广泛传播到从业者的办公室，而且它在检测乳腺癌方面已经证明了一些有效的方法，无论年龄或乳房密度如何。不幸的是，当需要高特异度(&gt；90%)时，EIS技术表现出相对较低的灵敏度(~25%-35%)。最近开发了一种新的EIS测量方法，并在非医疗应用中获得了相当成功的应用。当组织成为RLC电路的一部分时，这种新的方法测量在共振频率附近的阻抗移位。我们将这种新方法称为共振阻抗谱(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)可以实现比以前EIS更好的诊断性能。在这项研究的R21阶段，我们将建立一个原型REIS设备，用于快速评估(不到10分钟)乳房，并展示使用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，将年轻女性人口(40岁)分为两组。一种(REIS阴性)预计有患乳腺癌的正常风险，另一种(REIS阳性)识别出患乳腺癌风险大大高于目前常规筛查的老年女性(40-49岁)的一组女性。在R33阶段，将招募更大的患者群体，并将用于优化分类算法。将与现有的EIS技术进行比较。在这项应用中，我们建议建立和评估一种设备，用于识别绝经前乳腺癌风险增加的女性，因此将受益于基于成像的乳房评估。这将使用一种低成本、安全的技术来实现，这种技术可以在没有进行乳房X光检查的年轻女性的常规办公室访问中使用。如果成功，这项提议将通过增加乳腺癌的早期检测而对公众健康产生重大影响。

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.