JOphir R21 Imaging the Shear Strain at Breast

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DESCRIPTION (provided by applicant): The long term goal of this line of research is to expand the development and testing of novel ultrasound methodologies to elucidate the mechanical phenomena occurring at and near soft tissue boundaries that may be specific to the behavior of benign vs. malignant tumors in the breast and elsewhere. The overall hypothesis of this work is that quantitative metrics from axial-shear strain elastograms (ASSEs), which are related to tissue bonding at internal boundaries in inhomogeneous tissues, could serve as features that may become important in the noninvasive differentiation between benign and malignant breast tumors in vivo. To test this hypothesis we propose the following aims: Aim 1: Develop a Graphical User Interface (GUI) software tool that will aid in extracting, estimating, and analyzing features from axial-shear strain elastograms; and Aim 2: Conduct a retrospective study on a previously-acquired elastographic data base to investigate the use of axial-shear strain elastograms to discriminate pathologically-confirmed benign from malignant breast tumors in-vivo. The term 'bonding' will be used in a generic sense (as used in the literature) to describe the mechanical properties of the tumor boundary. This may refer to the mechanical interlocking at the inclusion-background boundary. PUBLIC HEALTH RELEVANCE The research we propose in this application is aimed at testing a novel ultrasound technology based on a new contrast mechanism for breast tumor classification. This technology may eventually find applications in various areas of medicine such as tumor detection, tumor classification, cardiovascular muscle function, wound healing and vulnerable plaque characterization. The application of this novel technology may provide powerful tool that complement and overcome some of the limitations of existing ultrasound imaging techniques while maintaining the advantages of low costs, and high safety and accessibility typical of ultrasound-based modalities.