The ability to visualize breast lesion vascularity and quantify the vascular heterogeneity using contrast-enhanced 3-D nonlinear ultrasound imaging was investigated in a clinical population. Patients (n = 236) identified with breast lesions on mammography were scanned using power Doppler imaging, contrast-enhanced 3D HI, and 3D SHI on a modified Logiq 9 scanner (GE Healthcare). Time-intensity curve volumes were developed corresponding to ultrasound contrast agent flow in the lesions after being identified in 4DView (GE Medical Systems). Time-points corresponding to baseline, peak intensity and complete washout of contrast were identified to generate vascular heterogeneity plots of the lesion volume (in the center and periphery as well as the ratio of the two). Vascularity was observed with power Doppler imaging in 93 lesions (69 benign and 24 malignant). The 3D HI showed flow in 8 lesions (5 benign and 3 malignant), whereas 3D SHI visualized flow in 83 lesions (58 benign and 25 malignant). Parametric volumes, that contained a single parametric value for every voxel within the 3D volume, were generated based on perfusion (PER) and area under the curve (AUC). ROC analysis and reverse, step-wise logistical regression were used to assess diagnostic accuracy with biopsy results as the reference. Analysis of vascular heterogeneity in the 3D SHI volumes found benign lesions having a significant difference in vascularity between central and peripheral sections (1.8 ± 0.16 vs. 1.2 ± 0.09 dB, p = 0.0003, respectively), whereas malignant lesions showed no difference (1.7 ± 0.33 vs. 1.3 ± 0.21 dB, p = 0.23), indicative of more vascular coverage. Diagnostic accuracy (i.e., area under the ROC curve) for heterogeneity, PER and AUC ranged from 0.52 to 0.75. The best logistical regression model (heterogeneity ratio, PER central and AUC central) achieved an area of 0.88. In conclusion, 3D SHI is able to detect UCA flow in vascular breast masses. Evaluation of vascular heterogeneity and parametric maps suggests such quantitative parameters might aid in the characterization of breast lesions.