REVIEW ARTICLE Diffusion MRI of the Breast: Current Status and Future Directions Mami Iima, MD, PhD, 1,2 * Maya Honda, MD, 1 Eric E. Sigmund, PhD, 3,4 Ayami Ohno Kishimoto, MD, 1 Masako Kataoka, MD, PhD, 1 and Kaori Togashi, MD, PhD 1 Diffusion-weighted imaging (DWI) is increasingly being incorporated into routine breast MRI protocols in many institutions worldwide, and there are abundant breast DWI indications ranging from lesion detection and distinguishing malignant from benign tumors to assessing prognostic biomarkers of breast cancer and predicting treatment response. DWI has the potential to serve as a noncontrast MR screening method. Beyond apparent diffusion coefficient (ADC) mapping, which is a commonly used quantitative DWI measure, advanced DWI models such as intravoxel incoherent motion (IVIM), non- Gaussian diffusion MRI, and diffusion tensor imaging (DTI) are extensively exploited in this field, allowing the characteriza- tion of tissue perfusion and architecture and improving diagnostic accuracy without the use of contrast agents. This review will give a summary of the clinical literature along with future directions. Level of Evidence: 5 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2019. D IFFUSION MAGNETIC RESONANCE IMAGING (MRI), which allows the mapping of the diffusion of water molecules in biological tissues, has been found to be highly useful for lesion detection, distinguishing between malignant and benign lesions, and assessing prognostic bio- markers of breast tumors. The uniqueness of diffusion MRI is its ability to observe tumor cell density and microstructure or microvasculature at the cellular level without the use of contrast agents. The apparent diffusion coefficient (ADC) is a measure of water diffusion in tissue, and can be calculated using diffusion-weighted images. The nomenclature "appar- ent" diffusion coefficient reflects the presence of various effects on the water diffusion coefficient in tissues, such as perfusion in capillary networks (intravoxel-incoherent motion, IVIM) or non-Gaussian diffusion. There has been abundant evidence suggesting the importance of ADC measurements in distinguishing between malignant and benign breast tumors. 1–3 Correlation of ADC values with prognostic bio- markers such as subtypes or hormone receptor status has been reported to some degree. 4–23 However, because ADC values in tissues (especially in cancer tissues, which are heteroge- neous) depend on the choice of b values 1 or diffusion times, 24,25 there is some variability between the reported ADC value thresholds to distinguish malignant from benign tumors across sites. 2 Diffusion-weighted imaging (DWI) pro- tocols differ among studies, scanners, or systems, so standardi- zation of DWI and ADC values is an essential step for the ADC to become as a truly clinically applicable quantitative biomarker. In this review, building upon recent surveys of this field, 1–3,26,27 we will summarize the evidence connecting ADC with malignancy, prognostic factors, treatment response, and nodal status; consider its potential role in screening; discuss ongoing standardization efforts; and assess progress and evidence of advanced techniques going beyond ADC quantification. Dynamic contrast-enhanced MRI (DCE-MRI) has been established as a standard diagnostic technique incorporated into the Breast Imaging Reporting and Data System (BI-RADS), with high sensitivity and variable specificity for characterization of breast lesions. 28,29 Several publications have already suggested View this article online at wileyonlinelibrary.com. DOI: 10.1002/jmri.26908 Received Jun 10, 2019, Accepted for publication Aug 12, 2019. *Address reprint requests to: M.I., Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin-kawa- haracho, Sakyo-ku, Kyoto, Kyoto, Japan 606-8507. E-mail: mamiiima@kuhp.kyoto-u.ac.jp From the 1 Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan; 2 Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan; 3 Department of Radiology, NYU Langone Health, New York, New York, USA; and 4 Center for Advanced Imaging and Innovation (CAI2R), New York, New York, USA © 2019 International Society for Magnetic Resonance in Medicine 1