This proposed technique, called "Nonlinear Elasticity Mapping (NEM)", is an innovative approach to estimate (i.e., linear and nonlinear) elasticity to provide complementary and relevant information for identification and characterization of breast masses.

The proposed technique includes imaging the (nonlinear) elasticity parameter in a quantitative manner and measuring two new and relevant parameters. These parameters, together with linear elasticity, are used to differentiate breast masses. The first parameter is the nonlinearity of the elasticity.

Measuring the nonlinearity of elasticity is obtained by recording ultrasound scans of object under different values of externally applied compression, and processing the resulting data. The central element of the proposed method is the solution of an inverse problem by which the linear and nonlinear parameters are estimated and a map of tissue nonlinearity is produced, in which the malignant masses can be identified. In addition to estimating the elasticity, will also evaluate the heterogeneity of the (linear) elasticity parameter distribution within the mass as an indicator of malignancy. In a previously performed pilot study, tested the proposed method on a small group of patients.

The goal of this project is to take the next logical step, which is to test this method in a clinical study on a larger population of patients to obtain statistically meaningful results. Assuming that the proposed method continues to demonstrate high specificity, this technique can have a significant impact on breast cancer diagnosis and management.

Inclusion Criteria:

• Without a history of mastectomy or implants, which are identified to have findings on their clinical breast ultrasound.

Exclusion Criteria:

• Previous mastectomy or implants
• Any condition that does not allow proper use of imaging devices.

Female and male patient volunteers, aged 18 years and older, without a history of mastectomy or implants, which are identified to have findings on their clinical breast ultrasound