Ultrasound Scattering Models for Detection of Metastases in Axillary Lymph Nodes

描述（由申请人提供）：滨江研究和夏威夷大学和Kuakini医学中心提议开发新型超声散射模型，以提高定量超声（QUS）方法的灵敏度和特异性，用于区分乳腺癌患者的含癌和无癌淋巴结。淋巴结转移癌的检测对于准确的分期、预后和治疗计划至关重要。我们的总体目标是显着减少现有的组织病理学方法检测转移的不可接受的失败，在25%至30%的所有解剖的节点和50%的节点与微转移。在目前资助的项目中，在病理实验室中使用高频超声的基于QUS的成像方法用于识别需要仔细组织学检查的解剖淋巴结区域。迄今为止，我们的研究结果显示了在广泛的胃肠道癌症的淋巴结清扫中检测癌症的显著能力。我们提出的方法所证明的精确定位转移性癌症的能力可能会大大减少当淋巴结包含微转移性疾病时假阴性确定的发生，而使用当前的组织病理学程序很容易忽略微转移性疾病。然而，在乳腺癌患者更复杂的腋窝淋巴结中获得的结果不太令人满意。我们认为，癌症检测性能是有限的，通过使用简单的散射模型来获得QUS估计。采用这些简单的模型是因为它们可以很容易地应用，但它们并不特定于所研究的组织。因此，我们建议开发先进的超声散射模型，以更敏感和特异地检测腋窝淋巴结转移。这些新模型将通过从解剖的腋窝淋巴结中获取250 MHz的定量声学显微镜数据来开发，以高空间分辨率生成其声学组织特性的准确3D地图。最终，该项目可以有利于淋巴结评估分期预后和乳腺癌的治疗。此外，我们从定量声学显微镜数据开发新的超声散射模型的方法可能有利于目前使用QUS的许多临床应用。

DESCRIPTION (provided by applicant): Riverside Research and the University of Hawaii and Kuakini Medical Center propose to develop novel ultrasound scattering models to improve the sensitivity and specificity of quantitative ultrasound (QUS) methods for discriminating between cancer-containing and cancer-free lymph nodes of breast-cancer patients. Detection of metastatic cancer in lymph nodes is absolutely crucial for accurate staging, prognosis, and treatment planning. Our overall objective is to reduce markedly the unacceptable failure of existing histopathological methods to detect metastases in 25% to 30% of all dissected nodes and 50% in nodes with micrometastases. In a currently funded project, QUS-based imaging methods using high-frequency ultrasound in the pathology laboratory are used to identify regions of dissected nodes that warrant careful histologic examination. Our results to date have shown a remarkable ability to detect cancer in dissected lymph nodes for a broad range of gastrointestinal cancers. The demonstrated ability of our proposed methods to pinpoint metastatic cancer potentially can reduce the occurrence of false-negative determinations drastically when nodes contain micrometastatic disease, which easily can be overlooked using current histopathology procedures. Nevertheless, less satisfactory results were obtained in the more-complex axillary lymph nodes of breast-cancer patients. We believe that cancer-detection performance is limited by the use of simple scattering models to derive QUS estimates. These simple models are employed because they can be applied easily, but they are not specific to the tissue being studied. Therefore, we propose to develop advanced ultrasound- scattering models for more sensitive and specific detection of metastases in axillary lymph nodes. These new models will be developed by acquiring quantitative acoustic-microscopy data at 250 MHz from dissected axillary lymph nodes to produce accurate 3D maps of their acoustic tissue properties at fine spatial resolution. Ultimately, this project can benefit lymph-node evaluations for staging prognosis, and treatment of breast cancer. Additionally, our methods to develop new ultrasound-scattering models from quantitative acoustic- microscopy data potentially can benefit many clinical applications where QUS currently is used.