This paper demonstrates the importance of capturing SpatialTemporal Enhancement Pattern (STEP) for completely characterizing breast tumor in contrast-enhanced MR images. STEP captures not only the dynamic enhancement and architectural features of tumor, but also the spatial variations of pixel-wise temporal enhancement of tumor. Although the latter has been widely used by radiologist during diagnosis, it is rarely considered as important features for computer-aided tumor diagnosis. Notice that, by regarding serial contrast-enhanced images as a single spatial-temporal image, STEP can capture all types of the features within a single framework. In particular, a Fourier transformation is used to extract various temporal enhancement features, followed by moment invariants to capture spatial patterns of each temporal enhancement feature. Experimental results show the better performance of our designed STEP features than many other features available in the literature. The area under ROC curve can reach 0.96 with our STEP features in tumor diagnosis.