Ultrasound Scattering Models for Detection of Metastases in Axillary Lymph Nodes

描述（由申请人提供）：Riverside Research和夏威夷大学以及Kuakini Medical Center提议开发新的超声散射模型，以提高定量超声（QUS）方法区分乳腺癌患者含癌和无癌淋巴结的灵敏度和特异性。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著减少现有组织病理学方法在所有解剖淋巴结中检测转移的25%至30%和在微转移淋巴结中检测转移的50%的不可接受的失败。在一个目前资助的项目中，基于qbased的成像方法在病理实验室使用高频超声来识别需要仔细组织学检查的淋巴结清扫区域。到目前为止，我们的研究结果已经显示出在广泛的胃肠道癌症中，在清扫淋巴结中检测癌症的卓越能力。当淋巴结含有微转移性疾病时，我们所提出的方法可以潜在地减少假阴性测定的发生，而微转移性疾病很容易被当前的组织病理学方法所忽视。然而，在更复杂的乳腺癌患者腋窝淋巴结中获得的结果不太令人满意。我们认为，使用简单的散射模型来推导QUS估计，癌症检测性能受到限制。使用这些简单的模型是因为它们易于应用，但它们并不特定于所研究的组织。因此，我们建议发展先进的超声散射模型，以更敏感和特异性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获取250兆赫的定量声学显微镜数据来开发，以精细的空间分辨率生成其声学组织特性的精确3D地图。最终，该项目有助于淋巴结评估，分期预后和治疗乳腺癌。此外，我们从定量声学显微镜数据中开发新的超声散射模型的方法可能会使QUS目前使用的许多临床应用受益。

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.