Magnetic resonance imaging (MRI) is a noninvasive method that reveals anatomical details in vivo and detects lesions for diagnosis. Although standard breast MRI cannot clearly delineate breast cancer, contrast-enhanced MRI enables the detection of breast masses with high sensitivity. Dynamic studies demonstrated that malignant lesions were characterized by a faster signal enhancement rate than benign ones. Dynamic MRI of human breast cancer in mice revealed high heterogeneity in the distribution of contrast-enhanced curves and derived pathophysiological features, indicating the importance of high spatial resolution. With clinical MRI, it is difficult to achieve simultaneously high spatial and temporal resolution. In previous dynamic studies, the emphasis was on high temporal resolution and mainly empiric analyses. We describe here a new model-based method that optimizes spatial resolution by using only three time points, and yet characterizes tumor heterogeneity in terms of microvascular permeability and extracellular fraction. Mapping these pathophysiological features may aid diagnosis and prognosis assessment, while the high spatial resolution may improve the capacity to detect smaller lesions. The method was tested in human breast tumors implanted in mice and in a limited number of benign and malignant breast lesions of patients.