Ultrasound Scattering Models for Detection of Metastases in Axillary Lymph Nodes

用于检测腋窝淋巴结转移的超声散射模型

• 批准号: 8424731
• 负责人: JONATHAN MAMOU
• 金额: $ 21.27万
• 依托单位: RIVERSIDE RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-12-15 至 2014-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8424731
• 关键词: Abdomen; Acoustic Microscopy; Acoustics; Algorithms; Axillary lymph node group; Breast; Breast Cancer Treatment; Cancer Detection; Cancer Patient; Cancerous; Cardiac; Classification; Colon; Complex; Custom; Data; Databases; Detection; Disease; Disseminated Malignant Neoplasm; Equipment; Evaluation; Failure; Frequencies; Funding; Goals; Hawaii; Histologic; Histopathology; Human; Kidney; Laboratories; Liver; Malignant Neoplasms; Malignant neoplasm of gastrointestinal tract; Maps; Mechanics; Medical center; Methods; Micrometastasis; Modeling; Modification; Musculoskeletal; Neoplasm Metastasis; New York; Partner in relationship; Pathology; Performance; Procedures; Process; Property; Research; Resolution; Sampling; Sensitivity and Specificity; Sentinel Lymph Node; Source; Specific qualifier value; Specimen; Staging; Stomach; System; Techniques; Testing; Tissues; Ultrasonography; Universities; base; clinical application; clinically significant; data acquisition; design; imaging modality; improved; lymph nodes; malignant breast neoplasm; malignant stomach neoplasm; novel; outcome forecast; public health relevance; quantitative ultrasound; standard of care; treatment planning

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.

描述（由申请人提供）：Riverside Research 与夏威夷大学和 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) 方法区分含癌淋巴结和无癌淋巴结的灵敏度和特异性的乳腺癌患者。淋巴结转移癌的检测对于准确的分期、预后和治疗计划绝对至关重要。我们的总体目标是显着减少现有组织病理学方法在检测所有解剖节点中 25% 至 30% 的转移以及 50% 微转移节点中检测转移的不可接受的失败。在目前资助的一个项目中，在病理实验室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节点区域。迄今为止，我们的结果显示出在解剖淋巴结中检测多种胃肠道癌症的卓越能力。当节点含有微转移性疾病时，我们提出的方法所证明的查明转移性癌症的能力可能会大大减少假阴性测定的发生，而使用当前的组织病理学程序很容易忽视这种疾病。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，使用简单的散射模型得出 QUS 估计值会限制癌症检测性能。采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，我们建议开发先进的超声散射模型，以更灵敏、更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获取 250 MHz 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 图。最终，该项目可以有利于淋巴结评估以进行分期预后和乳腺癌治疗。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。