? DESCRIPTION (provided by applicant): Assessment of breast masses is a critical step in selection of masses to be biopsied. The low specificity of traditional imaging methods, e.g., mammography and ultrasound, leads to a great number of unnecessary (i.e. benign) biopsies, resulting in high cost as well as significant trauma and anxiety for the patients due to this invasive procedure. In recent years, ultrasound elasticity imaging has been of interest as an adjunct to breast sonography to improve the specificity. This method is based on the premise that malignant masses are often significantly stiffer than benign masses and normal tissue. However, evidence shows that elasticity alone is not always specific, and there are significant overlaps in the elasticity of benign and malignant masses. This poses a fundamental limitation of the diagnostic value of elasticity parameter, i.e., elasticity information alone is not specific enough to completely differentiate between benign and malignant masses. Therefore, to improve differentiation of breast masses, it is imperative to develop new methods that provide additional and complementary information. To accomplish this task, our vision is to employ a multi-parameter approach. As we will show in our promising preliminary studies, nonlinearity of elasticity and heterogeneity in elasticity distribution are two parameters that are relevant to the breast malignancy and can be used to differentiate breast masses. Our goal is to further develop and test a novel multi-parameter technique for assessment of breast masses. In this technique, which is called Nonlinear Elasticity Mapping (NEM), we quantitatively measure 3 parameters: the (linear) elasticity, the nonlinear elasticity parameter, and the heterogeneity of elasticity distribution. In this project, we plan to conduct a clinical study to evaluate the efficcy of a NEM technology for classification/diagnosis of breast masses. To our knowledge, our proposed method is the only breast evaluation method that explores the combination of the 3 above-mentioned parameters for differentiation of breast masses. Our Specific Aims include: (1) Determine the diagnostic performance of the combination of linear and nonlinear elasticity parameters by correlating its results with pathology, and (2) Determine the diagnostic performance of elasticity heterogeneity in combination with linear and nonlinear elasticity parameters. Both Aims are tested in a population of patients with suspicious breast masses. This proposal is the result of collaboration among several experts in the field. Also, the projects benefits from the world-class clinical research and facilities at the Mayo Clinic. Successful completion of this research will open the door for a new technology for differentiation of breast masses in clinic. NEM is noninvasive, low cost, easy to use, and compatible with current ultrasound technology, which means that this technology can be readily translated to clinic and become available to a wide range of breast patients. Consequently, this research has potential to provide significant impact in breast cancer diagnosis and in reducing unnecessary biopsies.
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