Axial shear strain imaging for breast mass differentiation

Abstract

Breast cancer remains the second-leading cause of cancer deaths in women, and over 200,000 new cases of invasive breast cancer are expected in the USA this year. Very promising data demonstrate that axial strain imaging has an important role in breast tissue classification However, another important parameter; the shear strain has only recently been recognized as having great potential. We examine the feasibility of utilizing in-vivo axial shear strain imaging for differentiating benign from malignant breast masses. A VFX13-5 linear array transducer was utilized to acquire in-vivo radiofrequency echo data on 41 patients using a Siemens SONOLINE Antares real-time clinical scanner at the University of Wisconsin Breast Center. Free-hand palpation imaging with deformation up to 10% was utilized to acquire radiofrequency data loops to generate strain images. In this study, we report on 8 malignant tumors and 33 fibroadenomas to demonstrate the potential of shear strain imaging, compared to biopsy results that were considered the diagnostic standard. Axial strain and axial component of shear strain are estimated using an algorithm based on 2D cross-correlation. Areas of the axial-shear strain, normalized to the lesion size, applied strain and strain contrast was utilized for differentiating benign from malignant masses. Our results on 40 patients indicate that the normalized axial-shear strain area is significantly larger for malignant tumors when compared to benign fibroadenomas. Axial-shear strain pixel values greater than a specified threshold, including only those with correlation coefficient values greater than 0.75, were overlaid on the corresponding B-mode image to aid in diagnosis. Scatter plot of the normalized area feature demonstrate the feasibility of developing a linear classifier to differentiate benign from malignant masses. The area under the Receiver Operating Characteristic curve using the normalized shear strain area parameter was 0.996.