Developing a quantitative ultrasound breast scanner for identifying early response of breast cancer to chemotherapy

项目摘要 在本提案中，我们将在QT Ultrasound®断层乳腺扫描仪上开发新的图像模式， 证明具有新图像模式的扫描仪可以准确地识别乳腺癌的反应， 患者化疗。乳腺癌治疗中的临床需求未得到充分满足， 在治疗过程中早期确定患者对化疗反应的准确方法。对于许多乳房 在癌症中，患者对初始治疗缺乏反应预示着不良结局，而病理学完全缓解则预示着不良结局。 反应与延长生存期密切相关。传统的临床反应替代物， 解剖学信息，如身体评估、乳房X射线照相术和标准临床超声， 对治疗反应的早期评估不佳。我们证明了超声定量分析 使用常规手持式临床扫描仪的反向散射（QUSB）可以提供有希望的响应度量 新辅助化疗（NAC/AC）治疗开始后一周内的乳腺癌。这些QUSB 结果将大大受益于常规扫描平台所不能实现的改进的体积精度 支持，如信号中的传输和衰减损耗。 我们建议通过将QUSB与最新推出的QT Ultrasound®乳腺 扫描仪这款FDA批准并上市的扫描仪可提供乳房的3D定量图像，包括声音 速度、（SOS）反射率（R）和衰减（A）值。QT Ultrasound®乳腺扫描仪可矫正屈光 和界面衰减损耗。它还提供了多个视角的复合，这将进一步改善 QUSB方差。扫描仪的SOS、R、A和mm 3体积测量精度参数提供了 补充的定量特征可能有助于早期识别响应的稳健性。 我们相信QUSB+QT Ultrasound®乳腺扫描仪可以比MRI更好地识别反应。 即使响应识别仅具有可比性，QUSB+QT Ultrasound®也可节省成本，易用性， 非侵入性的天然造影剂和患者的接受将显著简化乳腺癌的管理 治疗和提供相当大的实际优势和增加的准确性。因此，我们的科学前提 QT Ultrasound®乳腺扫描仪上集成的QUSB将提供更好的早期识别， 乳腺癌患者对NAC的反应。我们的初步数据表明，QUSB技术可以识别 无应答者和预测患者结局。我们的初步结果还表明，QUSB技术， 与QT Ultrasound®平台集成，并从改进的QUSB偏差和方差中获益。因此 该提案包括三个目标。第一个具体的目标是实现，测试和验证QUSB技术上 最新的QT Ultrasound®乳腺扫描仪用于临床数据采集。第二个具体目标是量化 QUSB+QT Ultrasound®定量数据识别无应答者的能力。最后的具体目标是 量化QUSB+QT Ultrasound®定量数据预测患者结局的能力。

PROJECT SUMMARY In this proposal, we will develop new images modes on the QT Ultrasound® tomographic breast scanner and demonstrate that the scanner with the new image modes can accurately identify the response of breast cancer patients to chemotherapy. A poorly met clinical need in breast cancer therapy is providing inexpensive and accurate ways to identify patient responses to chemotherapy early during the course of therapy. For many breast cancers, lack of patient response to initial therapy is predictive of poor outcome, whereas pathological complete response strongly correlates with extended survival. Conventional clinical surrogates of response based on anatomical information such as physical assessments, mammography and standard clinical ultrasound provide poor early assessments of treatment response. We demonstrated that quantitative analysis of ultrasound backscatter (QUSB) using conventional hand-held clinical scanners can provide promising metrics of response of breast cancer to neoadjuvant chemotherapy (NAC/AC) within one week of therapy initiation. These QUSB results would benefit greatly from improved volumetric accuracy that conventional scanning platforms do not support, such as transmission and attenuation losses in the signals. We propose to solve these issues by integrating QUSB with the newly available QT Ultrasound® breast scanner. This FDA cleared and marketed scanner delivers 3D quantitative images of the breast including sound speed, (SOS) reflectivity (R) and attenuation (A) values. The QT Ultrasound® breast scanner corrects refractive and interface attenuation losses. It also provides compounding of multiple angles of view that will further improve QUSB variance. The scanner’s parameters of SOS, R, A, and mm3 volume measuring accuracy provide supplementary quantitative features likely to contribute robustness to early identification of response. We believe that the QUSB+QT Ultrasound® breast scanner can identify response at a level better than MRI. Even if response identification is only comparable, QUSB+QT Ultrasound® savings in costs, ease of use, noninvasive native contrast, and patient acceptance would markedly simplify management of breast cancer therapy and deliver considerable practical advantage and increased accuracy. Therefore, our scientific premise is that QUSB integrated on the QT Ultrasound® breast scanner will provide improved identification of early response of breast cancer patients to NAC. Our preliminary data demonstrate that QUSB techniques can identify nonresponders and predict patient outcomes. Our preliminary results also demonstrate that QUSB techniques integrate with the QT Ultrasound® platform and benefit from improved QUSB bias and variance. Therefore, the proposal consists of three aims. The first specific aim is to implement, test and validate QUSB techniques on the latest QT Ultrasound® breast scanner for clinical data acquisition. The second specific aim is to quantify the capacity of QUSB+QT Ultrasound® quantitative data to identify nonresponders. The final specific aim is to quantify the capacity of QUSB+QT Ultrasound® quantitative data to predict patient outcomes.