We assessed the usefulness and limitations of utilizing apparent diffusion coefficient (ADC) values on diffusion-weighted imaging (DWI) for the differential diagnosis of benign and malignant non-mass-like breast lesions. We retrospectively reviewed 27 such lesions (16 malignant, 11 benign) detected on magnetic resonance (MR) imaging and analyzed the enhancing patterns of dynamic contrast-enhanced DCE-MRI (distribution and internal enhancement), kinetic curve patterns, and ADC values. All images were obtained with a 1.5-tesla MR unit, with patients supine. On DCE-MRI, malignant lesions tended to show either segmental or branching-ductal distribution, and when lesions with these patterns were considered malignant, sensitivity was 68.8%; specificity, 63.6%; positive predictive value (PPV), 73.3%; negative predictive value (NPV), 58.3%; and accuracy, 66.7%. Kinetic curve analysis did not reliably differentiate benign and malignant non-mass-like lesions. There was no significant difference between the mean ADC value of the malignant lesions, 0.968×10⁻³ mm²/s at b=1000 s/mm², and that of benign lesions, 1.207×10⁻³ mm²/s (P=0.109). Receiver operating characteristic (ROC) analysis revealed the most effective threshold of ADC value for differentiating tumors as 1.1×10⁻³ mm²/s; values lower than this were observed more often in malignant than benign lesions (P=0.054). Us of this threshold yielded sensitivity of 68.8%; specificity, 72.7%; PPV, 78.6%; NPV, 61.5%; and accuracy, 70.4%. Combining the ADC value criteria with the analysis of DCE-MRI pattern increased sensitivity to 93.8%, negative predictive value (NPV) to 85.7%, and accuracy to 77.8% but decreased specificity to 54.5%. Use of ADC values does not adequately improve DCE-MRI performance for differential diagnosis of non-mass-like breast lesions, but adding the ADC value criteria to the DCE-MRI pattern analysis improves sensitivity, NPV, and accuracy.