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.
This proposal seeks to develop advanced ultrasound-scattering models to enhance the standard of care of breast-cancer patients significantly. These new models will be obtained from processing quantitative acoustic microscopy data acquired at 250 MHz. The models will be used to generate improved quantitative ultrasound images of dissected human lymph nodes and the potential of these models for the sensitive and specific detection of metastatic tissues will be evaluated.