The purpose of this research is to optimize and evaluate the efficacy of a hybrid imaging and quantitative viscoelasticity measurement tool for breast cancer detection and monitoring. The general goal of this project is to apply vibroacoustography (VA) and the Shearwave Dispersion Ultrasound Vibrometry (SDUV) technique for characterizing breast lesions in specific applications where there is a need for improved imaging with higher specificity. Our hypothesis is that by using combined VA-SDUV, we will be able to improve pre biopsy breast lesion characterization. The hybrid VA-SDUV prototype provides imaging as well as viscoelasticity properties of tissue using the same ultrasound probe. The proposed method will be a low-cost noninvasive tool that is anticipated to offer higher specificity than conventional breast imaging methods; thus, it will reduce unnecessary breast biopsies and improve breast patient care. This project includes the following Specific Aims: (1) Optimize the VA-SDUV prototype for breast imaging and viscoelasticity measurement. (2) Determine diagnostic accuracy of combined use of VA and SDUV in breast lesion detection and, (3) Assess the response to preoperative chemotherapy in breast cancer patients using the combined information from VA and SDUV. Approach:
For Aim 1, we will optimize the VA-SDUV prototype that is implemented on a programmable ultrasound system.
For Aim 2, we will perform VA and SDUV on patients with breast masses identified on MRI. Since MRI has a high sensitivity in detecting breast lesions, estimation of VA sensitivity based on MRI is expected to be a good estimation of its true sensitivity. We will then identify common features associated with breast cancer lesions, such as spiculation, architectural distortion, microlobulated lesion or ill defined lesion, and presence of pleomorphic calcifications. SDUV provides quantitative estimate of lesion elasticity and viscosity, which are important markers of malignancy. Combined information from VA and SDUV will be used to differentiate breast lesions. Sensitivity and specificity of the proposed method will be calculated based on MRI and the result of pathology.
For Aim 3 of the project, we will perform VA and SDUV on newly diagnosed breast cancer patients who are scheduled for preoperative chemotherapy. VA imaging and SDUV will be repeated in the middle and after completion of the preoperative chemotherapy. The pre-, mid- and post- chemotherapy VA images will be compared to the corresponding MRI images to verify the capability of VA in estimating lesion downsizing. Changes in lesion appearance and viscoelastic parameters will be correlated to lesion size changes. We will verify the results using the results of MRI and biopsy.
The goal of this project is to develop a new tool for detection and evaluation of breast masses. Specifically, the new combined method will have a significant impact on breast cancer care by reducing the numbers of unnecessary breast biopsies, improving detection in high risk women who have mammographically dense parenchyma, and better assessing the response to preoperative chemotherapy in breast cancer patients. Successful completion of this research will lead to a tool for breast cancer detection and monitoring.
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