Some image processing techniques for digital mammography (DM) and digital breast tomosynthesis (DBT) require or assume prior knowledge of the three-dimensional (3D) shape of the compressed breast. Our goal is to characterize the breast shape curvature during mechanical compression for DM and DBT acquisition, and to study its dependencies on relevant patient features to improve this prior knowledge. For this, patients were recruited to undergo 3D breast surface scanning during breast compression for their clinical DBT examination. This surface scanning system included two sets of a digital projector with a pair of stereoscopic structured light cameras, positioned at opposite sides of the DBT system. Features from the patients were extracted from the DBT images while the 3D surfaces were used as input to a previously developed principal component analysis (PCA) breast shape model. From the cases included in this study, 70 scans with full breast coverage and without artefacts were selected for this interim analysis. The enhanced coverage with the stereoscopic setup resulted in improved characterization of the breast shape curvature, yielding an asymmetry in the curvature between medial and lateral side. Linear correlation between the first PCA component and the thickness of the breast was found, but not for the other components. A multiple linear regression analysis was applied, finding no significant correlation between curve shape and patient characteristics. Searching for other factors that could be used to predict the breast shape when compressed, and testing for non-linear correlations will be addressed as a next step.