The use of prior studies to complement the information in Breast Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) can help to reduce the currently high false positive ratios. Registration is a fundamental part of this process, as registration algorithms provide automatic correspondences between current and prior studies. The deformable nature of the breast and differences in acquisition protocols make this a particularly challenging problem. In this paper we study three registration algorithms (Affine, SyN and Demons) applied to DCE-MRI images obtained from clinical practice. The methodology followed for this study included using segmentation algorithms in order to focus on the area of the breast. Anatomical landmarks were also added by an expert for evaluation purposes. This allowed us to use an anatomical-landmark-based measure in order to evaluate the quality of registration. Additionally, an image metric was also used for the same purpose. Results, shown to be statistically significant indicate how SyN obtains the best results in terms of the two measures considered.