Breast cancer detection in the early stages is of great importance since the prognosis, and the treatment depends more on this. Multiple techniques relying on the mechanical properties of soft tissues have been developed to help in early detection. In this study, we implemented a technique that measures the nonlinear shear modulus (NLSM) (μ(NL)) in vivo and showed its utility to detect breast lesions from healthy tissue. The technique relies on the acoustoelasticity theory in quasi-incompressible media. In order to recover μ(NL), static elastography and supersonic shear imaging are combined to subsequently register strain maps and shear modulus maps while the medium is compressed. Then, μ(NL) can be recovered from the relationship between the stress, deduced from strain maps, and the shear modulus. For this study, a series of five nonlinear phantoms were built using biological tissue (pork liver) inclusions immersed in an agar-gelatin gel. Furthermore, 11 in vivo acquisitions were performed to characterize the NLSM of breast tissue. The phantom results showed a very good differentiation of the liver inclusions when measuring μ(NL) with a mean value of -114.1 kPa compared to -34.7 kPa for the gelatin. Meanwhile, values for the shear modulus for the liver and the gelatin were very similar, 3.7 and 3.4 kPa, respectively. In vivo NLSM mean value for the healthy breast tissue was of -95 kPa, while mean values of the benign and the malignant lesions were -619 and -806 kPa with a strong v ariability, respectively. This study shows the potential of the acoustoelasticity theory in quasi-incompressible medium to bring a new parameter for breast cancer diagnosis.