The development of ultrafast dynamic contrast‐enhanced (UF‐DCE) MRI has occurred in tandem with fast MRI scan techniques, particularly view‐sharing and compressed sensing. Understanding the strengths of each technique and optimizing the relevant parameters are essential to their implementation. UF‐DCE MRI has now shifted from research protocols to becoming a part of clinical scan protocols for breast cancer. UF‐DCE MRI is expected to compensate for the low specificity of abbreviated MRI by adding kinetic information from the upslope of the time‐intensity curve. Because kinetic information from UF‐DCE MRI is obtained from the shape and timing of the initial upslope, various new kinetic parameters have been proposed. These parameters may be associated with receptor status or prognostic markers for breast cancer. In addition to the diagnosis of malignant lesions, more emphasis has been placed on predicting and evaluating treatment response because hyper‐vascularity is linked to the aggressiveness of breast cancers. In clinical practice, it is important to note that breast lesion images obtained from UF‐DCE MRI are slightly different from those obtained by conventional DCE MRI in terms of morphology. A major benefit of using UF‐DCE MRI is avoidance of the marked or moderate background parenchymal enhancement (BPE) that can obscure the target enhancing lesions. BPE is less prominent in the earlier phases of UF‐DCE MRI, which offers better lesion‐to‐noise contrast. The excellent contrast of early‐enhancing vessels provides a key to understanding the detailed pathological structure of tumor‐associated vessels. UF‐DCE MRI is normally accompanied by a large volume of image data for which automated/artificial intelligence‐based processing is expected to be useful. In this review, both the theoretical and practical aspects of UF‐DCE MRI are summarized.Evidence Level: 5Technical Efficacy: Stage 2

A multiparametric approach to breast cancer imaging offers the advantage of integrating the diverse contributions of various parameters. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is the most important MRI sequence for breast imaging. The vascularity and permeability of lesions can be estimated through the use of semiquantitative and quantitative parameters. The increased use of ultrafast DCE-MRI has facilitated the introduction of novel kinetic parameters. In addition to DCE-MRI, diffusion-weighted imaging provides information associated with tumor cell density, with advanced diffusion-weighted imaging techniques such as intravoxel incoherent motion, diffusion kurtosis imaging, and time-dependent diffusion MRI opening up new horizons in microscale tissue evaluation. Furthermore, T2-weighted imaging plays a key role in measuring the degree of tumor aggressiveness, which may be related to the tumor microenvironment. Magnetic resonance imaging is, however, not the only imaging modality providing semiquantitative and quantitative parameters from breast tumors. Breast positron emission tomography demonstrates superior spatial resolution to whole-body positron emission tomography and allows comparable delineation of breast cancer to MRI, as well as providing metabolic information, which often precedes vascular and morphological changes occurring in response to treatment. The integration of these imaging-derived factors is accomplished through multiparametric imaging. In this article, we explore the relationship among the key imaging parameters, breast cancer diagnosis, and histological characteristics, providing a technical and theoretical background for these parameters. Furthermore, we review the recent studies on the application of multiparametric imaging to breast cancer and the significance of the key imaging parameters.