Combinations of BI-RADS lesion descriptors can predict the probability of malignancy for breast MRI masses but not for NMLE. If our model is validated, masses with a low probability of malignancy may be eligible for short-interval follow-up rather than biopsy. Further research focused on predictive features of NMLE is needed.

Increased background parenchymal enhancement on breast MRI is associated with younger patient age and higher abnormal interpretation rate. However, it is not related to significant differences in positive biopsy rate, cancer yield, sensitivity, or specificity of MRI.

The characteristics of BI-RADS 3 lesions were highly variable in our population, and the risk of malignancy was low (0.85%). Assigning foci with 100% persistent enhancement to the BI-RADS 2 category can decrease the frequency of BI-RADS 3 assessment and maintain a likelihood of malignancy in less than 2% of cases.

Purpose:To develop a model incorporating dynamic contrast material-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance (MR) imaging features to differentiate high-nuclear-grade (HNG) from non-HNG ductal carcinoma in situ (DCIS) in vivo. Materials and Methods:This HIPAA-compliant study was approved by the institutional review board and requirement for informed consent was waived. A total of 55 pure DCIS lesions (19 HNG, 36 non-HNG) in 52 women who underwent breast MR imaging at 1.5 T with both DCE and DW imaging (b = 0 and 600 sec/mm 2 ) were retrospectively reviewed. The following lesion characteristics were recorded or measured: DCE morphology, DCE maximum lesion size, peak initial enhancement at 90 seconds, worst-curve delayed enhancement kinetics, apparent diffusion coefficient (ADC), contrast-to-noise ratio (CNR) at DW imaging with b values of 0 and 600 sec/mm 2 , and T2 signal effects (measured with CNR at b = 0 sec/mm 2 ). Univariate and stepwise multivariate logistic regression modeling was performed to identify MR imaging features that optimally discriminated HNG from non-HNG DCIS. Discriminative abilities of models were compared by using the area under the receiver operating characteristic curve (AUC). Results:HNG lesions exhibited larger mean maximum lesion size (P = .02) and lower mean CNR for images with b value of 600 sec/mm 2 (P = .004), allowing discrimination of HNG from non-HNG DCIS (AUC = 0.71 for maximum lesion size, AUC = 0.70 for CNR at b = 600 sec/mm 2 ). Differences in CNR for images with b value of 0 sec/mm 2 (P = .025) without corresponding differences in ADC values were observed between HNG and non-HNG lesions. Peak initial enhancement was the only kinetic variable to approach significance (P = .05). No differences in lesion morphology (P = .11) or worst-curve delayed enhancement kinetics (P = .97) were observed. A multivariate model combining CNR for images with b value of 600 sec/ mm 2 and maximum lesion size most significantly discriminated HNG from non-HNG (AUC = 0.81). Conclusion:The preliminary findings suggest that DCE and DW MR imaging features may aid in identifying patients with highrisk DCIS. Further study may yield a model combining MR characteristics with histopathologic data to facilitate lesion-specific targeted therapies.q RSNA, 2012