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; 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）：河滨研究以及夏威夷大学和库基尼医学中心提议开发新型的超声散射模型，以提高定量超声（QUS）方法的敏感性和特异性，以区分癌症患者的癌症和无癌症淋巴结。淋巴结中转移性癌症的检测对于准确的分期，预后和治疗计划至关重要。我们的总体目标是明显减少现有组织病理学方法的不可接受的失败，以检测所有解剖淋巴结的25％至30％的转移，而在带有微转移的淋巴结中，转移量为50％。在当前资助的项目中，使用病理实验室中使用高频超声检查的基于QUS的成像方法用于识别保管淋巴结的区域，以保证仔细的组织学检查。迄今为止，我们的结果表明，对于广泛的胃肠道癌症，在解剖的淋巴结中检测癌症的能力显着。当节点含有微转移性疾病时，我们提出的方法可能会大大减少假阴性确定的发生能力，从而大大降低错误 - 阴性确定的发生，而这种疾病可以使用当前的组织病理学程序很容易忽略。然而，在乳腺癌患者的更复杂的腋窝淋巴结中获得了较少的令人满意的结果。我们认为，癌症检测性能受到使用简单散射模型得出QUS估计的限制。这些简单的模型之所以使用，是因为它们可以轻松应用，但不是针对正在研究的组织的特定特定的。因此，我们建议开发高级超声散射模型，以更灵敏，更特异性地检测腋窝淋巴结中的转移。这些新模型将通过从解剖的腋窝淋巴结以250 MHz获取250 MHz的定量听觉微观镜数据来开发这些新模型。最终，该项目可以使淋巴结评估有益于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发模型的方法可能会受益于当前使用QU的许多临床应用。