It is well-documented in literature that benign breast lesions, such as fibroadenomas, are loosely bonded to their surrounding tissue and tend to slip under a small quasi-static compression, whereas malignant lesions being firmly bonded to their surrounding tissue do not slip. Recent developments in quasi-static ultrasound elastography have shown that an image of the axial-shear strain distribution can provide information about the bonding condition at the lesion-surrounding tissue boundary. Further studies analyzing the axial-shear strain elastograms revealed that nonzero axial-shear strain values appear inside the lesion, referred to as fill-in, only when a lesion is loosely bonded and asymmetrically oriented to the axis of compression. It was argued that the fill-in observed in axial-shear strain elastogram is a surrogate of the actual rigid-body rotation undergone by such a benign lesion due to slip boundary condition. However, it may be useful and perhaps easy to interpret, if the actual rigid-body rotation of the lesion can itself be visualized directly. To estimate this rotation tensor and its spatial distribution map (called a Rotation Elastogram [RE]), it would be necessary to improve the quality of lateral displacement estimates. Recently, it has been shown in the context of Non-Invasive Vascular Elastography (NIVE) that the Synthetic Transmit Aperture (STA) technique can be adapted for elastography to improve the lateral displacement estimates. Therefore, the focus of this work was to investigate the feasibility of employing the STA technique to improve the lateral displacement estimation and assess the resulting improvement in the RE quality. This investigation was done using both simulation and experimental studies. The image quality metric of contrast-to-noise ratio (CNR) was used to evaluate the quality of rotation elastograms. The results demonstrate that the contrast appeared in RE only in the case of loosely bonded inclusion, and the quality of RE improved considerably by employing the STA technique. © The Author(s) 2016.